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breast 在英语-中文（简体）词典中的翻译

breastnoun uk

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/brest/

breast noun

(WOMAN)

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B1 [ C ] either of the two soft, rounded parts of a woman's chest that produce milk after she has a baby

乳房

When a woman becomes pregnant her breasts tend to grow larger.

女性怀孕后，乳房会增大。

breast cancer

乳腺癌

Do you think she's had breast implants?

你觉得她做过隆胸手术吗？

更多范例减少例句Antibodies found in breast milk protect newborn babies against infection.The study showed that one in twelve women is likely to develop breast cancer.A lot of mothers find early weaning from breast milk more convenient.a silicone breast implantThey found a malignant tumour in her breast.

breast noun

(BIRD/ANIMAL)

[ C ] the front part of a bird's body

（鸟的）前胸，胸部

A robin is easy to identify because of its red breast.

知更鸟因其胸脯是红色的很容易辨认。

[ U or C ] the meat from the front part of the body of a bird or other animal

鸡脯肉;（动物的）胸脯肉

I had a cold chicken breast and a salad for lunch.

我午饭吃的是冷鸡脯肉和色拉。

breast of turkey

火鸡的前胸肉

pigeon breasts

鸽子前胸肉

breast noun

(CLOTHING)

[ C ] the part of a piece of clothing that covers a person's chest

上衣前部

He put a silk hanky in his breast pocket (= a pocket on the top front part of a shirt or coat).

他将一条丝绸手帕放入上衣口袋。

breast noun

(CHEST)

[ C ] literary a person's chest

（人的）胸部，胸膛

The dagger entered his breast.

匕首插入了他的胸膛。

[ C ] literary the centre of a person's feelings

心窝，胸怀

A feeling of love surged in his breast.

他心中涌起一阵爱意。

(breast在剑桥英语-中文（简体）词典的翻译 © Cambridge University Press)

breast的翻译

中文（繁体）

女性, 乳房, 鳥…

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pecho, seno, mama…

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seio, peito, mama…

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स्त्रीच्या छातीच्या दोन मऊ, गोलाकार भागांपैकी एक जो तिला बाळ झाल्यानंतर दूध तयार करतो…

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（女性の）胸, 乳房, （鶏などの）胸肉…

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göğüs, meme, kuşların göğüs kısmı…

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sein [masculine], blanc [masculine], sein…

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pit…

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borst, het hoofd bieden, boven op … komen…

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ஒரு குழந்தையைப் பெற்ற பிறகு பால் உற்பத்தி செய்யும் ஒரு பெண்ணின் மார்பின் இரண்டு மென்மையான, வட்டமான பகுதிகள்…

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bryst, stille sig op imod, nå toppen…

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bröst, gå (simma) rätt emot, möta…

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buah dada, dada, mengharungi…

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die Brust, ankämpfen gegen, bewältigen…

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bryst [neuter], pupp [masculine], bryststykke [neuter]…

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پستان, چھاتی…

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грудна залоза, груди, чинити опір…

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грудь, грудка…

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రొమ్ము…

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ثَدي, نَهْد, لَحم الصدْر…

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prs, prsa, hruď…

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เต้านมผู้หญิง, หน้าอก, เผชิญหน้า…

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vú, ngực, đối diện…

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pierś, stawiać czoło, wspiąć się…

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가슴, 가슴살…

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seno, petto, mammella…

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breakout room

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breast-beating, at breastbeating

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惯用语

beat your breast/chest idiom

make a clean breast of it idiom

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flexitarian

A flexitarian way of eating consists mainly of vegetarian food but with some meat.

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A spatially resolved single-cell genomic atlas of the adult human breast | Nature

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Article

Published: 28 June 2023

A spatially resolved single-cell genomic atlas of the adult human breast

Tapsi Kumar

ORCID: orcid.org/0000-0003-2825-33871,2 na1, Kevin Nee3 na1, Runmin Wei1 na1, Siyuan He1,2 na1, Quy H. Nguyen3 na1, Shanshan Bai1, Kerrigan Blake4,5, Maren Pein

ORCID: orcid.org/0000-0002-7906-59603,4, Yanwen Gong3,5, Emi Sei1, Min Hu1, Anna K. Casasent1, Aatish Thennavan1, Jianzhuo Li1, Tuan Tran1, Ken Chen

ORCID: orcid.org/0000-0003-4013-52796, Benedikt Nilges7, Nachiket Kashikar7, Oliver Braubach8, Bassem Ben Cheikh8, Nadya Nikulina8, Hui Chen9, Mediget Teshome10, Brian Menegaz

ORCID: orcid.org/0000-0002-3020-579011, Huma Javaid11, Chandandeep Nagi11, Jessica Montalvan11, Tatyana Lev4,5, Sharmila Mallya4, Delia F. Tifrea12, Robert Edwards12, Erin Lin12, Ritesh Parajuli12, Summer Hanson

ORCID: orcid.org/0000-0002-4106-981913, Sebastian Winocour14, Alastair Thompson14, Bora Lim

ORCID: orcid.org/0000-0002-4182-605815 na2, Devon A. Lawson

ORCID: orcid.org/0000-0003-1692-05174 na2, Kai Kessenbrock

ORCID: orcid.org/0000-0003-0410-61043 na2 & …Nicholas Navin

ORCID: orcid.org/0000-0002-2106-86241,2,6 na2 Show authors

Nature

volume 620, pages 181–191 (2023)Cite this article

30k Accesses

13 Citations

315 Altmetric

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Subjects

Gene expressionGene expression profilingGene regulatory networks

AbstractThe adult human breast is comprised of an intricate network of epithelial ducts and lobules that are embedded in connective and adipose tissue1,2,3. Although most previous studies have focused on the breast epithelial system4,5,6, many of the non-epithelial cell types remain understudied. Here we constructed the comprehensive Human Breast Cell Atlas (HBCA) at single-cell and spatial resolution. Our single-cell transcriptomics study profiled 714,331 cells from 126 women, and 117,346 nuclei from 20 women, identifying 12 major cell types and 58 biological cell states. These data reveal abundant perivascular, endothelial and immune cell populations, and highly diverse luminal epithelial cell states. Spatial mapping using four different technologies revealed an unexpectedly rich ecosystem of tissue-resident immune cells, as well as distinct molecular differences between ductal and lobular regions. Collectively, these data provide a reference of the adult normal breast tissue for studying mammary biology and diseases such as breast cancer.

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Fig. 1: Major cell types of the adult human breast.Fig. 2: Spatial analysis of major breast cell types.Fig. 3: Epithelial cells of the human breast.Fig. 4: Immune cell ecosystem in human breast tissues.Fig. 5: Breast fibroblasts and adipocytes.Fig. 6: Vascular, perivascular and lymphatic cells in the human breast.

Data availability

The HBCA website can be viewed at http://www.breastatlas.org. The data are available at the Gene Expression Omnibus (GSE195665). The data are also available from CZI in the CELLxGENE database (https://cellxgene.cziscience.com/collections/4195ab4c-20bd-4cd3-8b3d-65601277e731).

Code availability

The scripts associated with the analysis are available at GitHub (https://github.com/navinlabcode/HumanBreastCellAtlas).

ReferencesHassiotou, F. & Geddes, D. Anatomy of the human mammary gland: current status of knowledge. Clin. Anat. 26, 29–48 (2013).Russo, J., Rivera, R. & Russo, I. H. Influence of age and parity on the development of the human breast. Breast Cancer Res. Treat. 23, 211–218 (1992).Article

CAS

PubMed

Google Scholar

Gusterson, B. A. & Stein, T. Human breast development. Semin. Cell Dev. Biol. 23, 567–573 (2012).Article

PubMed

Google Scholar

Nguyen, Q. H. et al. Profiling human breast epithelial cells using single cell RNA sequencing identifies cell diversity. Nat. Commun. 9, 2028 (2018).Article

ADS

PubMed

PubMed Central

Google Scholar

Bach, K. et al. Differentiation dynamics of mammary epithelial cells revealed by single-cell RNA sequencing. Nat. Commun. 8, 2128 (2017).Article

ADS

PubMed

PubMed Central

Google Scholar

Bhat-Nakshatri, P. et al. A single-cell atlas of the healthy breast tissues reveals clinically relevant clusters of breast epithelial cells. Cell Rep. Med. 2, 100219 (2021).Article

CAS

PubMed

PubMed Central

Google Scholar

Russo, J. & Russo, I. H. Toward a physiological approach to breast cancer prevention. Cancer Epidemiol. Biomarkers Prev. 3, 353–364 (1994).CAS

PubMed

Google Scholar

Crawford, Y. G. et al. Histologically normal human mammary epithelia with silenced p16(INK4a) overexpress COX-2, promoting a premalignant program. Cancer Cell 5, 263–273 (2004).Article

CAS

PubMed

Google Scholar

Wu, S. Z. et al. A single-cell and spatially resolved atlas of human breast cancers. Nat. Genet. 53, 1334–1347 (2021).Article

CAS

PubMed

PubMed Central

Google Scholar

Shackleton, M. et al. Generation of a functional mammary gland from a single stem cell. Nature 439, 84–88 (2006).Article

ADS

CAS

PubMed

Google Scholar

Visvader, J. E. & Stingl, J. Mammary stem cells and the differentiation hierarchy: current status and perspectives. Genes Dev. 28, 1143–1158 (2014).Article

CAS

PubMed

PubMed Central

Google Scholar

Ewald, A. J., Brenot, A., Duong, M., Chan, B. S. & Werb, Z. Collective epithelial migration and cell rearrangements drive mammary branching morphogenesis. Dev. Cell 14, 570–581 (2008).Article

CAS

PubMed

PubMed Central

Google Scholar

Zwick, R. K. et al. Adipocyte hypertrophy and lipid dynamics underlie mammary gland remodeling after lactation. Nat. Commun. 9, 3592 (2018).Article

ADS

PubMed

PubMed Central

Google Scholar

Pal, B. et al. A single-cell RNA expression atlas of normal, preneoplastic and tumorigenic states in the human breast. EMBO J. 40, e107333 (2021).Article

CAS

PubMed

PubMed Central

Google Scholar

Gray, G. K. et al. A human breast atlas integrating single-cell proteomics and transcriptomics. Dev. Cell https://doi.org/10.1016/j.devcel.2022.05.003 (2022).Twigger, A. J. et al. Transcriptional changes in the mammary gland during lactation revealed by single cell sequencing of cells from human milk. Nat. Commun. 13, 562 (2022).Article

ADS

CAS

PubMed

PubMed Central

Google Scholar

Azizi, E. et al. Single-cell map of diverse immune phenotypes in the breast tumor microenvironment. Cell 174, 1293–1308 (2018).Article

CAS

PubMed

PubMed Central

Google Scholar

Pullan, S. et al. Requirement of basement membrane for the suppression of programmed cell death in mammary epithelium. J. Cell Sci. 109, 631–642 (1996).Polyak, K. & Kalluri, R. The role of the microenvironment in mammary gland development and cancer. Cold Spring Harb. Perspect. Biol. 2, a003244 (2010).Article

CAS

PubMed

PubMed Central

Google Scholar

Hanasoge Somasundara, A. V. et al. Parity-induced changes to mammary epithelial cells control NKT cell expansion and mammary oncogenesis. Cell Rep. 37, 110099 (2021).Article

CAS

PubMed

Google Scholar

Rozenblatt-Rosen, O., Stubbington, M. J. T., Regev, A. & Teichmann, S. A. The Human Cell Atlas: from vision to reality. Nature 550, 451–453 (2017).Article

ADS

CAS

PubMed

Google Scholar

Hovey, R. C. & Aimo, L. Diverse and active roles for adipocytes during mammary gland growth and function. J. Mammary Gland Biol. Neoplasia 15, 279–290 (2010).Article

PubMed

PubMed Central

Google Scholar

Emont, M. P. et al. A single-cell atlas of human and mouse white adipose tissue. Nature 603, 926–933 (2022).Article

ADS

CAS

PubMed

PubMed Central

Google Scholar

Aibar, S. et al. SCENIC: single-cell regulatory network inference and clustering. Nat. Methods 14, 1083–1086 (2017).Article

CAS

PubMed

PubMed Central

Google Scholar

Pellacani, D., Tan, S., Lefort, S. & Eaves, C. J. Transcriptional regulation of normal human mammary cell heterogeneity and its perturbation in breast cancer. EMBO J. 38, e100330 (2019).Article

PubMed

PubMed Central

Google Scholar

Stahl, P. L. et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science 353, 78–82 (2016).Article

ADS

CAS

PubMed

Google Scholar

Goltsev, Y. et al. Deep profiling of mouse splenic architecture with CODEX multiplexed imaging. Cell 174, 968–981 (2018).Article

CAS

PubMed

PubMed Central

Google Scholar

Menendez, J. A. & Lupu, R. Fatty acid synthase regulates estrogen receptor-α signaling in breast cancer cells. Oncogenesis 6, e299 (2017).Article

CAS

PubMed

PubMed Central

Google Scholar

Riese, D. J. 2nd & Cullum, R. L. Epiregulin: roles in normal physiology and cancer. Semin. Cell Dev. Biol. 28, 49–56 (2014).Article

CAS

PubMed

Google Scholar

Kannan, N. et al. The luminal progenitor compartment of the normal human mammary gland constitutes a unique site of telomere dysfunction. Stem Cell Rep. 1, 28–37 (2013).Article

CAS

Google Scholar

Zheng, L. et al. Pan-cancer single-cell landscape of tumor-infiltrating T cells. Science 374, abe6474 (2021).Article

PubMed

Google Scholar

Cheng, S. et al. A pan-cancer single-cell transcriptional atlas of tumor infiltrating myeloid cells. Cell 184, 792–809 (2021).Article

CAS

PubMed

Google Scholar

Hu, Q. et al. Atlas of breast cancer infiltrated B-lymphocytes revealed by paired single-cell RNA-sequencing and antigen receptor profiling. Nat. Commun. 12, 2186 (2021).Article

ADS

CAS

PubMed

PubMed Central

Google Scholar

Wherry, E. J. & Kurachi, M. Molecular and cellular insights into T cell exhaustion. Nat. Rev. Immunol. 15, 486–499 (2015).Article

CAS

PubMed

PubMed Central

Google Scholar

Milner, J. J. et al. Runx3 programs CD8+ T cell residency in non-lymphoid tissues and tumours. Nature 552, 253–257 (2017).Article

ADS

CAS

PubMed

PubMed Central

Google Scholar

Colleluori, G., Perugini, J., Barbatelli, G. & Cinti, S. Mammary gland adipocytes in lactation cycle, obesity and breast cancer. Rev. Endocr. Metab. Disord. 22, 241–255 (2021).Article

PubMed

PubMed Central

Google Scholar

Kalucka, J. et al. Single-cell transcriptome atlas of murine endothelial cells. Cell 180, 764–779 (2020).Article

CAS

PubMed

Google Scholar

Schupp, J. C. et al. Integrated single-cell atlas of endothelial cells of the human lung. Circulation 144, 286–302 (2021).Article

CAS

PubMed

PubMed Central

Google Scholar

Takeda, A. et al. Single-cell survey of human lymphatics unveils marked endothelial cell heterogeneity and mechanisms of homing for neutrophils. Immunity 51, 561–572 e565 (2019).Article

CAS

PubMed

Google Scholar

Sweeney, M. D., Ayyadurai, S. & Zlokovic, B. V. Pericytes of the neurovascular unit: key functions and signaling pathways. Nat. Neurosci. 19, 771–783 (2016).Article

CAS

PubMed

PubMed Central

Google Scholar

Armulik, A., Genove, G. & Betsholtz, C. Pericytes: developmental, physiological, and pathological perspectives, problems, and promises. Dev. Cell 21, 193–215 (2011).Article

CAS

PubMed

Google Scholar

Brozovich, F. V. et al. Mechanisms of vascular smooth muscle contraction and the basis for pharmacologic treatment of smooth muscle disorders. Pharmacol. Rev. 68, 476–532 (2016).Article

CAS

PubMed

PubMed Central

Google Scholar

Visvader, J. E. Keeping abreast of the mammary epithelial hierarchy and breast tumorigenesis. Genes Dev. 23, 2563–2577 (2009).Article

CAS

PubMed

PubMed Central

Google Scholar

Schmid, P. et al. Pembrolizumab for early triple-negative breast cancer. N. Engl. J. Med. 382, 810–821 (2020).Article

CAS

PubMed

Google Scholar

Choi, H. Y. et al. Preoperative axillary lymph node evaluation in breast cancer: current issues and literature review. Ultrasound Q. 33, 6–14 (2017).Article

PubMed

Google Scholar

Kothari, C., Diorio, C. & Durocher, F. The importance of breast adipose tissue in breast cancer. Int. J. Mol. Sci. https://doi.org/10.3390/ijms21165760 (2020).Garbe, J. C. et al. Accumulation of multipotent progenitors with a basal differentiation bias during aging of human mammary epithelia. Cancer Res. 72, 3687–3701 (2012).Article

CAS

PubMed

PubMed Central

Google Scholar

Pelissier Vatter, F. A. et al. High-dimensional phenotyping identifies age-emergent cells in human mammary epithelia. Cell Rep. 23, 1205–1219 (2018).Article

CAS

PubMed

PubMed Central

Google Scholar

Fraser, I. S., Critchley, H. O., Munro, M. G. & Broder, M. Can we achieve international agreement on terminologies and definitions used to describe abnormalities of menstrual bleeding? Hum. Reprod. 22, 635–643 (2007).Article

PubMed

Google Scholar

Murrow, L. M. et al. Mapping hormone-regulated cell-cell interaction networks in the human breast at single-cell resolution. Cell Syst. 13, 644–664 (2022).Article

CAS

PubMed

Google Scholar

Navin, N. et al. Tumour evolution inferred by single-cell sequencing. Nature 472, 90–94 (2011).Article

ADS

CAS

PubMed

PubMed Central

Google Scholar

Baslan, T. et al. Genome-wide copy number analysis of single cells. Nat. Protoc. 7, 1024–1041 (2012).Article

CAS

PubMed

PubMed Central

Google Scholar

Lander, E. S. et al. Initial sequencing and analysis of the human genome. Nature 409, 860–921 (2001).Article

ADS

CAS

PubMed

Google Scholar

Schneider, V. A. et al. Evaluation of GRCh38 and de novo haploid genome assemblies demonstrates the enduring quality of the reference assembly. Genome Res. 27, 849–864 (2017).Article

CAS

PubMed

PubMed Central

Google Scholar

Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888–1902 (2019).Article

CAS

PubMed

PubMed Central

Google Scholar

Aran, D. et al. Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage. Nat. Immunol. 20, 163–172 (2019).Article

CAS

PubMed

PubMed Central

Google Scholar

Tirosh, I. et al. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science 352, 189–196 (2016).Article

ADS

CAS

PubMed

PubMed Central

Google Scholar

Sergushichev, A. A. An algorithm for fast preranked gene set enrichment analysis using cumulative statistic calculation. Preprint at bioRxiv https://doi.org/10.1101/060012 (2016).Yu, G., Wang, L. G., Han, Y. & He, Q. Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 16, 284–287 (2012).Article

CAS

PubMed

PubMed Central

Google Scholar

Bankhead, P. et al. QuPath: open source software for digital pathology image analysis. Sci Rep. 7, 16878 (2017).Article

ADS

PubMed

PubMed Central

Google Scholar

Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675 (2012).Article

CAS

PubMed

PubMed Central

Google Scholar

A, L. & M, W. Classification and regression by randomForest. R News 3, 18–22 (2002).

Google Scholar

Wei, R. et al. Spatial charting of single-cell transcriptomes in tissues. Nat. Biotechnol. https://doi.org/10.1038/s41587-022-01233-1 (2022).Stringer, C., Wang, T., Michaelos, M. & Pachitariu, M. Cellpose: a generalist algorithm for cellular segmentation. Nat. Methods 18, 100–106 (2021).Article

CAS

PubMed

Google Scholar

Satija, R., Farrell, J. A., Gennert, D., Schier, A. F. & Regev, A. Spatial reconstruction of single-cell gene expression data. Nat. Biotechnol. 33, 495–502 (2015).Article

CAS

PubMed

PubMed Central

Google Scholar

Efremova, M., Vento-Tormo, M., Teichmann, S. A. & Vento-Tormo, R. CellPhoneDB: inferring cell–cell communication from combined expression of multi-subunit ligand–receptor complexes. Nat. Protoc. 15, 1484–1506 (2020).Article

CAS

PubMed

Google Scholar

Download referencesAcknowledgementsThis work was supported by major funding from the Chan-Zuckerberg Initiative (CZI) SEED Network Grant (CZF2019-002432); and grants to N. Navin from the NIH National Cancer Institute (RO1CA240526, RO1CA236864, 1R01CA234496, F30CA243419), the CPRIT Single Cell Genomics Center (RP180684), the American Cancer Society (132551-RSG-18-194-01-DDC). N. Navin is an AAAS Fellow, AAAS Wachtel Scholar, Damon-Runyon Rachleff Innovator, Andrew Sabin Fellow and Jack & Beverly Randall Innovator. T.K. is funded by the NCI T32 Translational Genomics Fellowship and Rosalie B. Hite fellowship. This study was supported by the MD Anderson Sequencing Core Facility Grant (CA016672). M.P. is supported by a fellowship from the CIRM Training Grant (EDUC4-12822). The work was also supported by a Damon-Runyon Quantitative Biology Postdoctoral Fellow to R.W. We thank B. Marshall, N. Tavares and J. Cool for their guidance and support; J. Waters, S. Stingley and L. Vann from for their support on this project; J. Wiley, A. Wood, A. Alexander and A. Contreras for clinical support; A. Longworth, S. Mallya and M. Curran for their advice; Y. Lin and R. Ye at MD Anderson for help with experiments; J. Zamanian and J. Yu-Sheng Chien for assistance with data depositing; and all of the women who participated in the HBCA and donated their breast tissue to this project. We thank Enable Medicine for their help with CODEX data generation. This publication is part of the HCA (www.humancellatlas.org).Author informationAuthor notesThese authors contributed equally: Tapsi Kumar, Kevin Nee, Runmin Wei, Siyuan He, Quy H. NguyenThese authors jointly supervised this work: Bora Lim, Devon A. Lawson, Kai Kessenbrock, Nicholas NavinAuthors and AffiliationsDepartment of Systems Biology, UT MD Anderson Cancer Center, Houston, TX, USATapsi Kumar, Runmin Wei, Siyuan He, Shanshan Bai, Emi Sei, Min Hu, Anna K. Casasent, Aatish Thennavan, Jianzhuo Li, Tuan Tran & Nicholas NavinGraduate School of Biomedical Sciences, University of Texas MD Anderson Cancer Center, Houston, TX, USATapsi Kumar, Siyuan He & Nicholas NavinDepartment of Biological Chemistry, University of California, Irvine, Irvine, CA, USAKevin Nee, Quy H. Nguyen, Maren Pein, Yanwen Gong & Kai KessenbrockDepartment of Physiology and Biophysics, University of California, Irvine, Irvine, CA, USAKerrigan Blake, Maren Pein, Tatyana Lev, Sharmila Mallya & Devon A. LawsonMath, Computational & Systems Biology, University of California, Irvine, Irvine, CA, USAKerrigan Blake, Yanwen Gong & Tatyana LevDepartment of Bioinformatics and Computational Biology, UT MD Anderson Cancer Center, Houston, TX, USAKen Chen & Nicholas NavinResolve Biosciences, Monheim am Rhein, GermanyBenedikt Nilges & Nachiket KashikarAkoya Biosciences, Menlo Park, CA, USAOliver Braubach, Bassem Ben Cheikh & Nadya NikulinaDepartment of Pathology, UT MD Anderson Cancer Center, Houston, TX, USAHui ChenDepartment of Breast Surgical Oncology, UT MD Anderson Cancer Center, Houston, TX, USAMediget TeshomeDepartment of Pathology and Immunology, Baylor Medical College, Houston, TX, USABrian Menegaz, Huma Javaid, Chandandeep Nagi & Jessica MontalvanChao Comprehensive Cancer Center, University of California, Irvine, Irvine, CA, USADelia F. Tifrea, Robert Edwards, Erin Lin & Ritesh ParajuliDepartment of Surgery, University of Chicago Medicine, Chicago, IL, USASummer HansonDepartment of Surgery, Baylor College of Medicine, Houston, TX, USASebastian Winocour & Alastair ThompsonDepartment of Medicine, Section of Hematology and Oncology, Baylor College of Medicine, Houston, TX, USABora LimAuthorsTapsi KumarView author publicationsYou can also search for this author in

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PubMed Google ScholarContributionsscRNA-seq experiments were performed by K.N., Q.H.N., S.B., T.K., E.S., J.L., M.P., T.T. and S.M. Spatial genomics experiments were performed by S.B., E.S., B.N., N.K., O.B., B.B.C. and N. Nikulina. Single-cell data analysis was performed by T.K., R.W., S. He., K.B., M.P., Y.G., M.H., A.K.C., B.N., N.K., K.C. and T.L. Spatial data analysis was performed by R.W., S. He and A. Thennavan. Tissue samples and clinical coordination was performed by O.B., B.B.C., H.C., A.K.C., M.T., B.M., H.J., J.M., R.E., D.F.T., C.N., E.L., R.P., S.W., S.M., A. Thompson, B.L. and S. Hanson. Tissue pathological analysis was performed by H.C., C.N. and A. Thennavan. Project management and manuscript writing was performed by B.L., D.A.L., N. Navin and K.K. N. Navin and K.K. are the coordinators for the Breast Atlas Bionetwork that is part of the HCA Project.Corresponding authorsCorrespondence to

Devon A. Lawson, Kai Kessenbrock or Nicholas Navin.Ethics declarations

Competing interests

N. Navin previously served on the scientific advisory board for Resolve Biosciences (2020–2022) but did not receive any compensation. O.B., B.B.C. and N. Nikulina are employees at Akoya Biosciences. B.N. and N.K. are employees of Resolve Biosciences. The other authors declare no competing interests.

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Nature thanks Itai Yanai and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional informationPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Extended data figures and tablesExtended Data Fig. 1 Frequency of Major Breast Cell Types Across Women and Sample Types.a, Experimental workflow for breast tissue processing for scRNA-seq, showing different conditions used for digestion times and trypsin treatments. b, Pie chart showing ethnic backgrounds of women who provided tissue samples for the breast atlas. c, Cell type frequencies for different tissue sources (reduction mammoplasties - RM, prophylactic mastectomies - PM and contralateral mastectomies - CM), cells vs nuclei single cell RNA-seq protocols, and experimental dissociation protocol. d, Major cell type frequencies of matched left and right breasts from 22 women (left) and averages across all left and all right breast tissues (right). e, Stacked barplot showing the variation of cell type frequencies across the 126 women in scRNA-seq data. The top annotation bar shows the experimental workflow used (short/medium/long). f, Top regulons identified with SCENIC for each cell type cluster from the snRNA-seq data. g, Top regulons identified with SCENIC for each cell type cluster from the scRNA-seq data. h, Multi-dimensional scaling and Procrustes analysis to determine the concordance of left and right breast cell type frequencies and Pearson correlations for 22 women with matched breast tissue samples. P-value was calculated based on a two-sided test.Extended Data Fig. 2 Ligand-receptor Interaction Analysis Between Cell Types.Ligand-receptor interaction plots predicted from scRNA-seq data using CellPhoneDB between the major breast cell types. a, Interaction plot between the epithelial (Basal, LumHR and LumSec) cell types. b, Interaction plot between the epithelial and immune (B-cells, T-cells, Myeloid cells) cell types. c, Interaction plot between the epithelial and stromal (Fibroblasts, Perivascular and Vascular endothelial cells) cell types. d, Interaction plot within the stromal (Fibroblasts, Myeloid, Lymphatic, Vascular and Perivascular cells) cell types. e, Interaction plot between adipocytes and stromal cell types.Extended Data Fig. 3 Spatial Transcriptomic Analysis of Breast Cell Types.a, Integrated UMAP and unbiased clustering of ST data from 10 breast samples, showing 9 ST clusters. b, Histopathological images, and spatial distribution of ST clusters in the ST data from the breast tissues. c, Concordance of ST clusters and the scRNA-seq clusters of the major cell types using Fisher’s exact test. d, Pearson correlation analysis of marker gene expression levels between the ST clusters and the scRNA-seq data for different cell types. All p-values were calculated based on two-sided tests.Extended Data Fig. 4 Spatial Analysis of Breast Cell Types with CODEX and smFISH.a, Cell segmentation results of smFISH (Resolve) data across 12 tissue samples profiled from 5 different women. Cells were annotated based on combinations of markers for each cell type as described in Supplementary Table 6. b, Densities of cell types across three topographic areas using 12 tissues profiled by smFISH (Resolve). c, Heatmap of the top 5 targeted maker genes for each cell type in the smFISH (Resolve) data from 12 combined tissue samples. d, Cell segmentation results of CODEX data from 8 different women. Cells were annotated based on combinations or single protein markers to identify different cell types. e, Densities of cell types across three topographic areas from 8 different women by CODEX. f, Heatmap showing protein levels for markers that were used to identify different cell types in the CODEX data. (D: ducts, L: lobules and C: connective regions).Extended Data Fig. 5 Analysis of Single Cell and Spatial Epithelial Data.a, UMAPs of snRNA-seq data showing the expression of hormone receptor genes. b, Epithelial cell state frequencies across the 126 women in scRNA-seq data, where the top annotation bar represents the dissociation protocol. c, UMAP feature plots showing the expression of previously reported stem cell marker genes in the scRNA-seq epithelial dataset. d, Ligand-receptor interactions within the epithelial cell states predicted with CellPhoneDB. e, Cell cycle scoring of S-phase for different epithelial cell states detected in the scRNA-seq data. f, Cell cycle scoring for S-phase in the epithelial cell type clusters detected in the snRNA-seq data. g, smFISH (Resolve) data showing the expression of the MKI67 proliferation marker in the epithelial cells of the ducts and lobules from 4 different breast tissues. h, UMAP of different LumSec cell states and ELF5, LTF signature scores, respectively. i, Histopathological image of adjacent H&E section showing the anatomic annotation of ducts and lobules (left) and smFISH MERFISH (right panel) from P101 showing the spatial distribution of different LumSec cell states across different regions. j, Stacked barplot showing the distribution of different LumSec cell proportions in ducts and lobules across 3 MERFISH samples. k, Histopathological image (left panel) and smFISH MERFISH (right panel) from P101 showing the spatial distribution of the LumHR-SCGB population in a specific region of epithelium.Extended Data Fig. 6 Spatial analysis of epithelial cells in ductal and lobular structures.a, Spatial transcriptomic analysis showing clusters labelled as duct or lobule/TDLU from 3 breast tissues (P10, P35 and P47). b, smFISH (Resolve) data (P46-S1 and P46-S4) showing a subset of Keratin markers (left) and hormone receptor genes (right) and their localization to different breast tissue regions annotated as either duct or lobule/TDLU. c, CODEX data from P131 showing KRT5 in ducts and KRT19 in lobules/TDLU regions, with enlarged panels of the right. d, CODEX analysis from P130 of ductal and lobular/TDLU regions, showing differences for KRT14 levels in ducts and lobules. e, CODEX data from P131 showing protein levels of KRT8 and progesterone receptor (PR) in epithelial cells in the ducts and lobular/TDLU regions.Extended Data Fig. 7 Immune cell subtypes in the breast and their variation in women.a, H&E staining of plasma B-cells, T-cells, mast cell and macrophages (arrows) in human breast tissues. b, Stacked barplot showing the cell type frequencies of T, B and myeloid cells across 126 women in scRNA-seq data. Top annotation bar represents different tissue dissociation protocols that were utilized. c-e, Stacked barplots showing the cell state frequencies of T, B and myeloid cells across 126 women in scRNA-seq data respectively. f, Dot plot showing expression of checkpoint/exhaustion markers in NK and T cell states from the scRNA-seq data of 126 women. g, Ligand-receptor interaction analysis predicted with CellPhoneDB between the fibroblasts cell states and macrophage cell states.Extended Data Fig. 8 Spatial analysis of immune cells in human breast tissues.a, CODEX data from patient P130 and P131 showing localization of different immune cells with epithelial marker KRT19 and vascular marker CD31. Yellow and white arrows indicate CD4 Tregs and DCs, respectively. b, Frequency of T cells with the RUNX3 tissue residency marker in CODEX data. c, CODEX data (P130) showing immune cells in ductal, lobular and connective regions. d, Stacked barplots of CODEX data showing the density of immune cell types in each spatial region in 8 women. e, smFISH (Resolve) data (P46-S1) showing RNA localization of T, B and myeloid cells. f, Segmented smFISH (Resolve) data (P46-S1) showing cell localization of T, B and myeloid cells. g, smFISH (Resolve) data (P46-S1 and P47-S1) showing immune cell localization of B, T and myeloid cells across ducts, lobules and connective regions. h, Stacked barplots of smFISH (Resolve) data showing the density and proportion of immune cell types in different spatial regions. i, Adjacent histopathological tissue section (left) and segmented smFISH MERFISH data (right) from patient P91 showing the spatial distribution of m1, m2 macrophages and cDC2 populations in different regions of human breast tissue. j, Stacked barplot showing the density of m1, m2 macrophages and cDC2 populations in different regions across 3 smFISH MERFISH samples. k, Adjacent histopathological tissue section (left) and segmented smFISH MERFISH data (right) from patient P96 showing the spatial distribution of different B-cell states in different regions of human breast tissue. l, Stacked barplot showing the density of different B-cell states in different regions across three smFISH MERFISH samples.Extended Data Fig. 9 Fibroblast cell states in the human breast.a, Stacked barplot showing the fibroblasts cell state frequencies across 126 women in scRNA-seq data with top annotation bar representing the tissue dissociation protocol. b, Gene ontology enrichment analysis showing top enriched biological process gene sets associated with each cell state (Pos: positive; Neg: negative; Reg: regulation; RSTK: receptor protein serine/threonine kinase; TGF: transforming growth factor; IGF: insulin-like growth factor). c, CODEX data from P132 showing fibroblasts marked by VIM in the connective tissue (I) and interlobular (II) regions. d, smFISH (Resolve) data showing fibroblast markers in areas of connective tissue regions (I) and epithelial regions (II) from two women (P47-S1 and P69-S3). e, smFISH (Resolve) data (P35-S1) indicating spatial proximity regions with epithelial-proximal (Epi-prox), epithelial-middle (Epi-mid) and epithelial-distant (Epi-Dist) regions for 4 marker genes. f, Percentages of 4 markers that are proximal, middle or distant to the epithelial cells, quantified from the smFISH (Resolve) data. g, RNAscope in situ hybridization of breast tissues using an MMP3 probe in combination with anti-Vimentin and anti-PanCK immunofluorescent staining, with enlarged panel (right). h, Ligand-receptor interactions between fibroblasts, adipocytes and myeloid cell states predicted using CellPhoneDB.Extended Data Fig. 10 Endothelial cell diversity in the Human Breast.a, Stacked barplot showing the endothelial cell state frequencies across the 126 women in scRNA-seq data, with top annotation bar showing the tissue dissociation protocol. b, Dot plot of gene ontology enrichment results for 4 lymphatic cell states. c, Heatmap showing top gene expression for vascular and lymphatic endothelial clusters detected in the ST data. d, smFISH (Resolve) data showing veins (ACKR1) and capillaries (RBP7), as well as a canonical vascular marker (VWF) in two different HBCA samples (P46-S3 and P69-S3). e, Adjacent H&E tissue section with pathological annotations (left panel) and segmented smFISH MERFISH data (right panel) from P101 showing the spatial distribution of vascular endothelial cell states in different regions of human breast tissue. f, Stacked barplot showing the density of vascular endothelial states in different regions across 3 smFISH MERFISH samples.Extended Data Fig. 11 Perivascular cells in Human Breast Tissues.a, Stacked barplot showing the perivascular cell state frequencies across the 126 women in scRNA-seq data with top annotation bars indicating the tissue dissociation protocol. b, UMAPs of pericytes and vascular smooth muscle cells (VSMCs) and feature plots of the VSMCs marker genes (SYNM and ACTG2). c-e, smFISH (Resolve) data showing expression of pericyte marker RGS5, together with vascular marker VWF and fibroblast marker COL1A1 in lobular and ductal regions from 2 different breast tissue samples (P47-S1 and P46-S3). f, CODEX results from P131 showing vascular cells (anti-CD31) and pericytes (anti-LIF) in a TDLU region. g, smFISH MERFISH from P96 showing the spatial distribution of vascular endothelial cell states (left panel) and perivascular cell states (right panel) in different regions of human breast tissue. h, smFISH (MERFISH) data showing arteries (SOX17) and VSMCs (ATCG2 and SYNM) in breast tissue.Extended Data Fig. 12 Metadata correlations with breast cell types and states.a, Boxplots showing the major cell type frequencies across ethnicity status in the n = 69 women using Wilcoxon rank sum test (top). Significant associations of cell states with ethnicity status using Fisher’s exact test (bottom). b, Boxplots showing the major cell type frequencies across pre- and post-menopause status in the n = 71 women using Wilcoxon rank sum test (top). Significant associations of cell states with menopause status using Fisher’s exact test (bottom). c, Boxplots showing the major cell type frequencies across different age groups using Wilcoxon rank sum test, young (<50 years) and old (>50 years) for n = 76 women (top). Significant associations of cell states with age groups using Fisher’s exact test (bottom). d, Boxplots showing the major cell type frequencies across different breast density (high, low) groups in the n = 16 women using Wilcoxon rank sum test (top). Significant associations of cell states with breast density using Fisher’s exact test (bottom). e, Boxplots showing the major cell type frequencies across different BMI status in 73 women using Wilcoxon rank sum test, overweight (BMI >= 25 and < 30) and obese (BMI >= 30). f, Boxplots showing the major cell type frequencies across different parity status (nulliparous, parous) status in the n=64 women using Wilcoxon rank sum test. All p-values were calculated based on two-sided tests. Boxplots show the median with interquartile ranges (25–75%), while whiskers extend to 1.5× the interquartile range from the box.Extended Data Fig. 13 Summary of the Major Cell Types and States in Breast Tissues.This illustration summarizes all of the breast cell types and cell states that were identified in the HBCA study. a, Summary of cell lineages from cell types to cell states. b, Mapping of cell types and cell states to the four major spatial regions (Adipose, Connective, Ductal, Lobular) that were supported by the spatial technologies. Not all cell states were assigned to specific spatial regions, in cases where the data did not support their assignment. Individual figures were created with BioRender.com.Supplementary informationSupplementary InformationReporting SummaryRights and permissionsSpringer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.Reprints and permissionsAbout this articleCite this articleKumar, T., Nee, K., Wei, R. et al. A spatially resolved single-cell genomic atlas of the adult human breast.

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Breast cancer

Nadia Harbeck1, Frédérique Penault-Llorca2, Javier Cortes3,4, Michael Gnant5, Nehmat Houssami6, Philip Poortmans7,8, Kathryn Ruddy9, Janice Tsang10 & …Fatima Cardoso11 Show authors

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Breast cancerCancer therapyGenetic predisposition to diseaseRadiotherapyTumour biomarkers

AbstractBreast cancer is the most frequent malignancy in women worldwide and is curable in ~70–80% of patients with early-stage, non-metastatic disease. Advanced breast cancer with distant organ metastases is considered incurable with currently available therapies. On the molecular level, breast cancer is a heterogeneous disease; molecular features include activation of human epidermal growth factor receptor 2 (HER2, encoded by ERBB2), activation of hormone receptors (oestrogen receptor and progesterone receptor) and/or BRCA mutations. Treatment strategies differ according to molecular subtype. Management of breast cancer is multidisciplinary; it includes locoregional (surgery and radiation therapy) and systemic therapy approaches. Systemic therapies include endocrine therapy for hormone receptor-positive disease, chemotherapy, anti-HER2 therapy for HER2-positive disease, bone stabilizing agents, poly(ADP-ribose) polymerase inhibitors for BRCA mutation carriers and, quite recently, immunotherapy. Future therapeutic concepts in breast cancer aim at individualization of therapy as well as at treatment de-escalation and escalation based on tumour biology and early therapy response. Next to further treatment innovations, equal worldwide access to therapeutic advances remains the global challenge in breast cancer care for the future.

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Fig. 1: Breast cancer.Fig. 2: Molecular mutations in breast cancer.Fig. 3: Immune crosstalk in breast cancer.Fig. 4: Breast cancer imaging.Fig. 5: Breast cancer histological types and molecular alterations.Fig. 6: Algorithm for early breast cancer.Fig. 7: Breast-conserving surgery.Fig. 8: Radiation therapy for breast cancer.Fig. 9: Common metastatic sites in breast cancer.Fig. 10: Algorithm for advanced breast cancer.Fig. 11: Emerging targetable pathways in breast cancer.

ReferencesPerou, C. M. et al. Molecular portraits of human breast tumours. Nature 406, 747–752 (2000).Article

CAS

PubMed

Google Scholar

Cardoso, F. et al. European Breast Cancer Conference manifesto on breast centres/units. Eur. J. Cancer 72, 244–250 (2017).Article

PubMed

Google Scholar

Bray, F. et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 68, 394–424 (2018).Article

PubMed

Google Scholar

Bray, F. et al. Cancer Incidence in Five Continents: inclusion criteria, highlights from Volume X and the global status of cancer registration. Int. J. Cancer 137, 2060–2071 (2015).Article

CAS

PubMed

Google Scholar

Mariotto, A. B., Etzioni, R., Hurlbert, M., Penberthy, L. & Mayer, M. Estimation of the number of women living with metastatic breast cancer in the United States. Cancer Epidemiol. Biomark. Prev. 26, 809–815 (2017).Article

Google Scholar

Ren, J.-X., Gong, Y., Ling, H., Hu, X. & Shao, Z.-M. Racial/ethnic differences in the outcomes of patients with metastatic breast cancer: contributions of demographic, socioeconomic, tumor and metastatic characteristics. Breast Cancer Res. Treat. 173, 225–237 (2019).Article

PubMed

Google Scholar

Torre, L. A., Siegel, R. L., Ward, E. M. & Jemal, A. Global cancer incidence and mortality rates and trends — an update. Cancer Epidemiol. Biomark. Prev. 25, 16–27 (2016).Article

Google Scholar

Ginsburg, O. et al. The global burden of women’s cancers: a grand challenge in global health. Lancet 389, 847–860 (2017).Article

PubMed

Google Scholar

Allemani, C. et al. Global surveillance of cancer survival 1995–2009: analysis of individual data for 25 676 887 patients from 279 population-based registries in 67 countries (CONCORD-2). Lancet 385, 977–1010 (2015).Article

PubMed

Google Scholar

Winters, S., Martin, C., Murphy, D. & Shokar, N. K. Breast cancer epidemiology, prevention, and screening. Prog. Mol. Biol. Transl Sci. 151, 1–32 (2017).Article

PubMed

Google Scholar

Hossain, M. S., Ferdous, S. & Karim-Kos, H. E. Breast cancer in South. Asia: a Bangladeshi perspective. Cancer Epidemiol. 38, 465–470 (2014).PubMed

Google Scholar

Leong, S. P. L. et al. Is breast cancer the same disease in Asian and western countries? World J. Surg. 34, 2308–2324 (2010).Article

PubMed

PubMed Central

Google Scholar

Bhoo Pathy, N. et al. Breast cancer in a multi-ethnic Asian setting: results from the Singapore–Malaysia hospital-based breast cancer registry. Breast 20, S75–S80 (2011).Article

Google Scholar

Raina, V. et al. Clinical features and prognostic factors of early breast cancer at a major cancer center in North India. Indian J. Cancer 42, 40 (2005).Article

PubMed

Google Scholar

Agarwal, G., Pradeep, P. V., Aggarwal, V., Yip, C.-H. & Cheung, P. S. Y. Spectrum of breast cancer in Asian women. World J. Surg. 31, 1031–1040 (2007).Article

PubMed

Google Scholar

Li, C. I., Malone, K. E. & Daling, J. R. Differences in breast cancer hormone receptor status and histology by race and ethnicity among women 50 years of age and older. Cancer Epidemiol. Biomark. Prev. 11, 601–607 (2002).

Google Scholar

Wong, F. Y., Tham, W. Y., Nei, W. L., Lim, C. & Miao, H. Age exerts a continuous effect in the outcomes of Asian breast cancer patients treated with breast-conserving therapy. Cancer Commun. 38, 39 (2018).Article

Google Scholar

Kohler, B. A. et al. Annual report to the nation on the status of cancer, 1975–2011, featuring incidence of breast cancer subtypes by race/ethnicity, poverty, and state. J. Natl Cancer Inst. 107, https://doi.org/10.1093/jnci/djv048 (2015).DeSantis, C. E. et al. Breast cancer statistics, 2015: Convergence of incidence rates between black and white women: Breast Cancer Statistics, 2015. CA Cancer J. Clin. 66, 31–42 (2016).Article

PubMed

Google Scholar

DeSantis, C. E., Ma, J., Goding Sauer, A., Newman, L. A. & Jemal, A. Breast cancer statistics, 2017, racial disparity in mortality by state: Breast Cancer Statistics, 2017. CA Cancer J. Clin. 67, 439–448 (2017).Article

PubMed

Google Scholar

Shiovitz, S. & Korde, L. A. Genetics of breast cancer: a topic in evolution. Ann. Oncol. 26, 1291–1299 (2015).CAS

PubMed

PubMed Central

Google Scholar

Collaborative Group on Hormonal Factors in Breast Cancer. Familial breast cancer: collaborative reanalysis of individual data from 52 epidemiological studies including 58 209 women with breast cancer and 101 986 women without the disease. Lancet 358, 1389–1399 (2001).Article

Google Scholar

Brewer, H. R., Jones, M. E., Schoemaker, M. J., Ashworth, A. & Swerdlow, A. J. Family history and risk of breast cancer: an analysis accounting for family structure. Breast Cancer Res. Treat. 165, 193–200 (2017).Article

PubMed

PubMed Central

Google Scholar

Huen, M. S. Y., Sy, S. M. H. & Chen, J. BRCA1 and its toolbox for the maintenance of genome integrity. Nat. Rev. Mol. Cell Biol. 11, 138–148 (2010).Article

CAS

PubMed

Google Scholar

Kuchenbaecker, K. B. et al. Risks of breast, ovarian, and contralateral breast cancer for BRCA1 and BRCA2 mutation carriers. JAMA 317, 2402 (2017).Article

CAS

PubMed

Google Scholar

Balmana, J., Diez, O., Rubio, I. T. & Cardoso, F., On behalf of the ESMO Guidelines Working Group. BRCA in breast cancer: ESMO clinical practice guidelines. Ann. Oncol. 22, vi31–vi34 (2011).Article

PubMed

Google Scholar

Paluch-Shimon, S. et al. Prevention and screening in BRCA mutation carriers and other breast/ovarian hereditary cancer syndromes: ESMO Clinical Practice Guidelines for cancer prevention and screening. Ann. Oncol. 27, v103–v110 (2016).Article

CAS

PubMed

Google Scholar

Daly, M. B. et al. Genetic/familial high-risk assessment: breast and ovarian, version 2.2015. J. Natl Compr. Cancer Netw. 14, 153–162 (2016).Article

Google Scholar

Forbes, C., Fayter, D., de Kock, S. & Quek, R. G. W. A systematic review of international guidelines and recommendations for the genetic screening, diagnosis, GENETIC COUNSELING and treatment of BRCA-mutated breast cancer. Cancer Manag. Res. 2019, 2321–2337 (2019).Article

Google Scholar

Robson, M. et al. Olaparib for metastatic breast cancer in patients with a germline BRCA mutation. N. Engl. J. Med. 377, 523–533 (2017).Article

CAS

PubMed

Google Scholar

Litton, J. K. et al. Talazoparib in patients with advanced breast cancer and a germline BRCA mutation. N. Engl. J. Med. 379, 753–763 (2018).Article

CAS

PubMed

Google Scholar

FDA. FDA approves olaparib germline BRCA-mutated metastatic breast cancer. Fda.gov https://www.fda.gov/drugs/resources-information-approved-drugs/fda-approves-olaparib-germline-brca-mutated-metastatic-breast-cancer (2018).FDA. FDA approves talazoparib for gBRCAm HER2-negative locally advanced or metastatic breast cancer. Fda.gov https://www.fda.gov/drugs/drug-approvals-and-databases/fda-approves-talazoparib-gbrcam-her2-negative-locally-advanced-or-metastatic-breast-cancer (2018).Pasche, B. Recent advances in breast cancer genetics. Cancer Treat. Res. 141, 1–10 (2008).Article

PubMed

PubMed Central

Google Scholar

Cobain, E. F., Milliron, K. J. & Merajver, S. D. Updates on breast cancer genetics: clinical implications of detecting syndromes of inherited increased susceptibility to breast cancer. Semin. Oncol. 43, 528–535 (2016).Article

PubMed

Google Scholar

Crawford, B. et al. Multi-gene panel testing for hereditary cancer predisposition in unsolved high-risk breast and ovarian cancer patients. Breast Cancer Res. Treat. 163, 383–390 (2017).Article

CAS

PubMed

PubMed Central

Google Scholar

Taylor, A. et al. Consensus for genes to be included on cancer panel tests offered by UK genetics services: guidelines of the UK Cancer Genetics Group. J. Med. Genet. 55, 372–377 (2018).PubMed

Google Scholar

Althuis, M. D., Dozier, J. M., Anderson, W. F., Devesa, S. S. & Brinton, L. A. Global trends in breast cancer incidence and mortality 1973–1997. Int. J. Epidemiol. 34, 405–412 (2005).Article

PubMed

Google Scholar

Colditz, G. A., Sellers, T. A. & Trapido, E. Epidemiology — identifying the causes and preventability of cancer? Nat. Rev. Cancer 6, 75–83 (2006).Article

CAS

PubMed

Google Scholar

Britt, K., Ashworth, A. & Smalley, M. Pregnancy and the risk of breast cancer. Endocr. Relat. Cancer 14, 907–933 (2007).Article

CAS

PubMed

Google Scholar

Siwko, S. K. et al. Evidence that an early pregnancy causes a persistent decrease in the number of functional mammary epithelial stem cells — implications for pregnancy-induced protection against breast cancer. Stem Cells 26, 3205–3209 (2008).Article

PubMed

PubMed Central

Google Scholar

Hilakivi-Clarke, L., de Assis, S. & Warri, A. Exposures to synthetic estrogens at different times during the life, and their effect on breast cancer risk. J. Mammary Gland. Biol. Neoplasia 18, 25–42 (2013).Article

PubMed

PubMed Central

Google Scholar

Danaei, G., Vander Hoorn, S., Lopez, A. D., Murray, C. J. & Ezzati, M. Causes of cancer in the world: comparative risk assessment of nine behavioural and environmental risk factors. Lancet 366, 1784–1793 (2005).Article

PubMed

Google Scholar

Chen, W. Y., Rosner, B., Hankinson, S. E., Colditz, G. A. & Willett, W. C. Moderate alcohol consumption during adult life, drinking patterns, and breast cancer risk. JAMA 306, 1884 (2011).Article

CAS

PubMed

PubMed Central

Google Scholar

Singletary, K. W. & Gapstur, S. M. Alcohol and breast cancer: review of epidemiologic and experimental evidence and potential mechanisms. JAMA 286, 2143 (2001).Article

CAS

PubMed

Google Scholar

Smith-Warner, S. A. et al. Alcohol and breast cancer in women: a pooled analysis of cohort studies. JAMA 279, 535 (1998).Article

CAS

PubMed

Google Scholar

Bandera, E. V., Maskarinec, G., Romieu, I. & John, E. M. Racial and ethnic disparities in the impact of obesity on breast cancer risk and survival: a global perspective. Adv. Nutr. 6, 803–819 (2015).Article

CAS

PubMed

PubMed Central

Google Scholar

Picon-Ruiz, M., Morata-Tarifa, C., Valle-Goffin, J. J., Friedman, E. R. & Slingerland, J. M. Obesity and adverse breast cancer risk and outcome: mechanistic insights and strategies for intervention: breast cancer, inflammation, and obesity. CA Cancer J. Clin. 67, 378–397 (2017).Article

PubMed

PubMed Central

Google Scholar

Shieh, Y. et al. Body mass index, mammographic density, and breast cancer risk by estrogen receptor subtype. Breast Cancer Res. 21, 48 (2019).Article

PubMed

PubMed Central

Google Scholar

Suzuki, Y., Tsunoda, H., Kimura, T. & Yamauchi, H. BMI change and abdominal circumference are risk factors for breast cancer, even in Asian women. Breast Cancer Res. Treat. 166, 919–925 (2017).Article

PubMed

Google Scholar

Del Pup, L., Codacci-Pisanelli, G. & Peccatori, F. Breast cancer risk of hormonal contraception: counselling considering new evidence. Crit. Rev. Oncol. Hematol. 137, 123–130 (2019).Article

PubMed

Google Scholar

Busund, M. et al. Progestin-only and combined oral contraceptives and receptor-defined premenopausal breast cancer risk: the Norwegian Women and Cancer Study. Int. J. Cancer 142, 2293–2302 (2018).Article

CAS

PubMed

PubMed Central

Google Scholar

Mørch, L. S. et al. Contemporary hormonal contraception and the risk of breast cancer. N. Engl. J. Med. 377, 2228–2239 (2017).Article

PubMed

Google Scholar

Ganz, P. A. et al. Supportive care after curative treatment for breast cancer (survivorship care): resource allocations in low- and middle-income countries. A Breast Health Global Initiative 2013 consensus statement. Breast 22, 606–615 (2013).Article

PubMed

Google Scholar

Burris, J. L., Armeson, K. & Sterba, K. R. A closer look at unmet needs at the end of primary treatment for breast cancer: a longitudinal pilot study. Behav. Med. 41, 69–76 (2015).Article

PubMed

Google Scholar

Coughlin, S. S., Yoo, W., Whitehead, M. S. & Smith, S. A. Advancing breast cancer survivorship among African-American women. Breast Cancer Res. Treat. 153, 253–261 (2015).Article

PubMed

PubMed Central

Google Scholar

Bodai, B. Breast cancer survivorship: a comprehensive review of long-term medical issues and lifestyle recommendations. Perm. J. 19, 48–79 (2015).Article

PubMed

PubMed Central

Google Scholar

Ho, P. J., Gernaat, S. A. M., Hartman, M. & Verkooijen, H. M. Health-related quality of life in Asian patients with breast cancer: a systematic review. BMJ Open 8, e020512 (2018).Article

PubMed

PubMed Central

Google Scholar

Miyashita, M. et al. Unmet information needs and quality of life in young breast cancer survivors in japan. Cancer Nurs. 38, E1–E11 (2015).Article

PubMed

PubMed Central

Google Scholar

Bombonati, A. & Sgroi, D. C. The molecular pathology of breast cancer progression. J. Pathol. 223, 307–317 (2011).Article

CAS

PubMed

Google Scholar

Ellis, M. J. et al. Whole-genome analysis informs breast cancer response to aromatase inhibition. Nature 486, 353–360 (2012).Article

CAS

PubMed

PubMed Central

Google Scholar

Lopez-Garcia, M. A., Geyer, F. C., Lacroix-Triki, M., Marchió, C. & Reis-Filho, J. S. Breast cancer precursors revisited: molecular features and progression pathways: molecular evolution of breast cancer. Histopathology 57, 171–192 (2010).Article

PubMed

Google Scholar

Nik-Zainal, S. et al. Landscape of somatic mutations in 560 breast cancer whole-genome sequences. Nature 534, 47–54 (2016).Article

CAS

PubMed

PubMed Central

Google Scholar

Yates, L. R. & Desmedt, C. Translational genomics: practical applications of the genomic revolution in breast cancer. Clin. Cancer Res. 23, 2630–2639 (2017).Article

PubMed

Google Scholar

Heitzer, E., Haque, I. S., Roberts, C. E. S. & Speicher, M. R. Current and future perspectives of liquid biopsies in genomics-driven oncology. Nat. Rev. Genet. 20, 71–88 (2019).Article

CAS

PubMed

Google Scholar

Ediriweera, M. K., Tennekoon, K. H. & Samarakoon, S. R. Emerging role of histone deacetylase inhibitors as anti-breast-cancer agents. Drug Discov. Today 24, 685–702 (2019).Article

CAS

PubMed

Google Scholar

Munster, P. N. et al. A phase II study of the histone deacetylase inhibitor vorinostat combined with tamoxifen for the treatment of patients with hormone therapy-resistant breast cancer. Br. J. Cancer 104, 1828–1835 (2011).Article

CAS

PubMed

PubMed Central

Google Scholar

Zhou, Y., Wang, Y., Zhang, K., Zhu, J. & Ning, Z. Reverse effect of chidamide on endocrine resistance in estrogen receptor-positive breast cancer. J. Shenzhen Univ. Sci. Eng. 35, 339 (2018).Article

Google Scholar

Jiang, Z. et al. Phase III trial of chidamide, a subtype-selective histone deacetylase (HDAC) inhibitor, in combination with exemestane in patients with hormone receptor-positive advanced breast cancer [abstract]. Ann. Oncol. 29, 283O_PR (2018).Article

Google Scholar

Williams, C. & Lin, C.-Y. Oestrogen receptors in breast cancer: basic mechanisms and clinical implications. Ecancermedicalscience 7, 370 (2013).PubMed

PubMed Central

Google Scholar

Levin, E. R. & Pietras, R. J. Estrogen receptors outside the nucleus in breast cancer. Breast Cancer Res. Treat. 108, 351–361 (2008).Article

CAS

PubMed

Google Scholar

Santen, R. J. Clinical review: effect of endocrine therapies on bone in breast cancer patients. J. Clin. Endocrinol. Metab. 96, 308–319 (2011).Article

CAS

PubMed

Google Scholar

Ruffell, B. et al. Leukocyte composition of human breast cancer. Proc. Natl Acad. Sci. USA 109, 2796–2801 (2012).Article

CAS

PubMed

Google Scholar

Solinas, C., Carbognin, L., De Silva, P., Criscitiello, C. & Lambertini, M. Tumor-infiltrating lymphocytes in breast cancer according to tumor subtype: current state of the art. Breast 35, 142–150 (2017).Article

PubMed

Google Scholar

Nagarajan, D. & McArdle, S. Immune landscape of breast cancers. Biomedicines 6, 20 (2018).Article

PubMed Central

CAS

Google Scholar

Savas, P. et al. Clinical relevance of host immunity in breast cancer: from TILs to the clinic. Nat. Rev. Clin. Oncol. 13, 228–241 (2016).Article

CAS

PubMed

Google Scholar

Dieci, M. V. et al. Update on tumor-infiltrating lymphocytes (TILs) in breast cancer, including recommendations to assess TILs in residual disease after neoadjuvant therapy and in carcinoma in situ: a report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer. Semin. Cancer Biol. 52, 16–25 (2018).Article

PubMed

Google Scholar

Boudreau, A., van’t Veer, L. J. & Bissell, M. J. An ‘elite hacker’: breast tumors exploit the normal microenvironment program to instruct their progression and biological diversity. Cell Adhes. Migr. 6, 236–248 (2012).Article

Google Scholar

Smyth, M. J., Dunn, G. P. & Schreiber, R. D. Cancer immunosurveillance and immunoediting: the roles of immunity in suppressing tumor development and shaping tumor immunogenicity. Adv. Immunol. 90, 1–50 (2006).Article

CAS

PubMed

Google Scholar

Schreiber, R. D., Old, L. J. & Smyth, M. J. Cancer immunoediting: integrating immunity’s roles in cancer suppression and promotion. Science 331, 1565–1570 (2011).Article

CAS

PubMed

Google Scholar

Buonomo, O. C. et al. New insights into the metastatic behavior after breast cancer surgery, according to well-established clinicopathological variables and molecular subtypes. PLOS ONE 12, e0184680 (2017).Article

PubMed

PubMed Central

CAS

Google Scholar

Gobbini, E. et al. Time trends of overall survival among metastatic breast cancer patients in the real-life ESME cohort. Eur. J. Cancer 96, 17–24 (2018).Article

PubMed

Google Scholar

Santé Publique France. Breast cancer [French]. Santepubliquefrance.fr https://www.santepubliquefrance.fr/maladies-et-traumatismes/cancers/cancer-du-sein (2019).Zhang, K. et al. Clinical value of circulating ESR1 mutations for patients with metastatic breast cancer: a meta-analysis. Cancer Manag. Res. 10, 2573–2580 (2018).Article

CAS

PubMed

PubMed Central

Google Scholar

Yates, L. R. et al. Genomic evolution of breast cancer metastasis and relapse. Cancer Cell 32, 169–184.e7 (2017).Article

CAS

PubMed

PubMed Central

Google Scholar

Gingras, I., Salgado, R. & Ignatiadis, M. Liquid biopsy: will it be the ‘magic tool’ for monitoring response of solid tumors to anticancer therapies? Curr. Opin. Oncol. 27, 560–567 (2015).Article

CAS

PubMed

Google Scholar

Aurilio, G. et al. A meta-analysis of oestrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 discordance between primary breast cancer and metastases. Eur. J. Cancer 50, 277–289 (2014).Article

CAS

PubMed

Google Scholar

Independent, U. K. Panel on breast cancer screening. the benefits and harms of breast cancer screening: an independent review. Lancet 380, 1778–1786 (2012).Article

Google Scholar

Nelson, H. D. et al. Effectiveness of breast cancer screening: systematic review and meta-analysis to update the 2009 U.S. Preventive Services Task Force recommendation. Ann. Intern. Med. 164, 244–255 (2016).Article

PubMed

Google Scholar

Lauby-Secretan, B. et al. Breast-cancer screening — viewpoint of the IARC Working Group. N. Engl. J. Med. 372, 2353–2358 (2015).Article

CAS

PubMed

Google Scholar

Houssami, N. Overdiagnosis of breast cancer in population screening: does it make breast screening worthless? Cancer Biol. Med. 14, 1–8 (2017).Article

PubMed

PubMed Central

Google Scholar

Suhrke, P. et al. Effect of mammography screening on surgical treatment for breast cancer in Norway: comparative analysis of cancer registry data. BMJ 343, d4692–d4692 (2011).Article

PubMed

PubMed Central

Google Scholar

Stang, A., Kääb-Sanyal, V., Hense, H.-W., Becker, N. & Kuss, O. Effect of mammography screening on surgical treatment for breast cancer: a nationwide analysis of hospitalization rates in Germany 2005–2009. Eur. J. Epidemiol. 28, 689–696 (2013).Article

PubMed

Google Scholar

IARC Handbooks of Cancer Prevention. Breast Cancer Screening (Volume 15). Iarc.fr http://publications.iarc.fr/Book-And-Report-Series/Iarc-Handbooks-Of-Cancer-Prevention/Breast-Cancer-Screening-2016 (2016).Nelson, H. D. et al. Harms of breast cancer screening: systematic review to update the 2009 U.S. Preventive Services Task Force recommendation. Ann. Intern. Med. 164, 256–267 (2016).Article

PubMed

Google Scholar

Carter, J. L., Coletti, R. J. & Harris, R. P. Quantifying and monitoring overdiagnosis in cancer screening: a systematic review of methods. BMJ 350, g7773 (2015).Article

PubMed

PubMed Central

Google Scholar

Saslow, D. et al. American Cancer Society guidelines for breast screening with MRI as an adjunct to mammography. CA Cancer J. Clin. 57, 75–89 (2007).Article

PubMed

Google Scholar

Phi, X.-A. et al. Magnetic resonance imaging improves breast screening sensitivity in BRCA mutation carriers age ≥ 50 years: evidence from an individual patient data meta-analysis. J. Clin. Oncol. 33, 349–356 (2015).Article

PubMed

Google Scholar

Sardanelli, F. et al. Magnetic resonance imaging of the breast: recommendations from the EUSOMA working group. Eur. J. Cancer 46, 1296–1316 (2010).Article

PubMed

Google Scholar

Melnikow, J. et al. Supplemental screening for breast cancer in women with dense breasts: a systematic review for the U.S. preventive services task force. Ann. Intern. Med. 164, 268–278 (2016).Article

PubMed

PubMed Central

Google Scholar

Houssami, N. & Lee, C. I. The impact of legislation mandating breast density notification — review of the evidence. Breast 42, 102–112 (2018).Article

PubMed

Google Scholar

Marinovich, M. L., Hunter, K. E., Macaskill, P. & Houssami, N. Breast cancer screening using tomosynthesis or mammography: a meta-analysis of cancer detection and recall. J. Natl Cancer Inst. 110, 942–949 (2018).Article

PubMed

Google Scholar

Irwig, L., Macaskill, P. & Houssami, N. Evidence relevant to the investigation of breast symptoms: the triple test. Breast 11, 215–220 (2002).Article

CAS

PubMed

Google Scholar

Houssami, N., Ciatto, S., Turner, R. M., Cody, H. S. & Macaskill, P. Preoperative ultrasound-guided needle biopsy of axillary nodes in invasive breast cancer: meta-analysis of its accuracy and utility in staging the axilla. Ann. Surg. 254, 243–251 (2011).Article

PubMed

Google Scholar

Morrow, M., Waters, J. & Morris, E. MRI for breast cancer screening, diagnosis, and treatment. Lancet 378, 1804–1811 (2011).Article

PubMed

Google Scholar

Srigley, J. R. et al. Standardized synoptic cancer pathology reporting: a population-based approach. J. Surg. Oncol. 99, 517–524 (2009).Article

PubMed

Google Scholar

World Heath Organisation. WHO Classification of Tumours of the Breast, Fourth Edition. (World Health Organization, 2012).Elston, C. W. & Ellis, I. O. Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. Histopathology 19, 403–410 (1991).Article

CAS

PubMed

Google Scholar

National Comprehensive Cancer Network. NCCN Clinical Practice Guidelines in Oncology: Breast Cancer. Nccn.org https://www.nccn.org/professionals/physician_gls/pdf/breast.pdf (2018).Curigliano, G. et al. De-escalating and escalating treatments for early-stage breast cancer: the St. Gallen International Expert Consensus Conference on the Primary Therapy of Early Breast Cancer 2017. Ann. Oncol. 28, 1700–1712 (2017).Article

CAS

PubMed

PubMed Central

Google Scholar

Senkus, E. et al. Primary breast cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann. Oncol. 24 (Suppl. 6), vi7-vi23 (2013).PubMed

Google Scholar

Hammond, M. E. H. et al. American Society of Clinical Oncology/College of American Pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer. J. Clin. Oncol. 28, 2784–2795 (2010).Article

PubMed

PubMed Central

Google Scholar

Wolff, A. C. et al. Human epidermal growth factor receptor 2 testing in breast cancer: American Society of Clinical Oncology/College of American Pathologists clinical practice guideline focused update. J. Clin. Oncol. 36, 2105–2122 (2018).Article

CAS

PubMed

Google Scholar

Dowsett, M. et al. Assessment of Ki67 in breast cancer: recommendations from the International Ki67 in Breast Cancer working group. J. Natl Cancer Inst. 103, 1656–1664 (2011).Article

CAS

PubMed

PubMed Central

Google Scholar

Rakha, E. A. et al. The prognostic significance of lymphovascular invasion in invasive breast carcinoma. Cancer 118, 3670–3680 (2012).Article

PubMed

Google Scholar

Barrio, A. V. & Morrow, M. Appropriate margin for lumpectomy excision of invasive breast cancer. Chin. Clin. Oncol. 5, 35–35 (2016).Article

PubMed

PubMed Central

Google Scholar

Chung, A. et al. Impact of consensus guidelines by the Society of Surgical Oncology and the American Society for Radiation Oncology on margins for breast-conserving surgery in stages 1 and 2 invasive breast cancer. Ann. Surg. Oncol. 22, 422–427 (2015).Article

Google Scholar

Schulman, A. M. et al. Reexcision surgery for breast cancer: an analysis of the American Society of Breast Surgeons (ASBrS) MasterySM database following the SSO-ASTRO “no ink on tumor” guidelines. Ann. Surg. Oncol. 24, 52–58 (2017).Article

PubMed

Google Scholar

Morrow, M. et al. Society of Surgical Oncology–American Society for Radiation Oncology–American Society of Clinical Oncology consensus guideline on margins for breast-conserving surgery with whole-breast irradiation in ductal carcinoma in situ. Pract. Radiat. Oncol. 6, 287–295 (2016).Article

PubMed

PubMed Central

Google Scholar

PubMed

PubMed Central

Google Scholar

Moran, M. S. et al. Society of Surgical Oncology–American Society for Radiation Oncology consensus guideline on margins for breast-conserving surgery with whole-breast irradiation in stages I and II invasive breast cancer. Int. J. Radiat. Oncol. Biol. Phys. 88, 553–564 (2014).Article

PubMed

PubMed Central

Google Scholar

Amin, M. B. et al. The Eighth Edition AJCC Cancer Staging Manual: continuing to build a bridge from a population-based to a more ‘personalized’ approach to cancer staging. CA Cancer J. Clin. 67, 93–99 (2017).Article

PubMed

Google Scholar

Tao, L. et al. Breast cancer mortality in older and younger breast cancer patients in California. Cancer Epidemiol. Biomark. Prev. 28, 303–310 (2018).Article

Google Scholar

Salgado, R. et al. The evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer: recommendations by an International TILs Working Group 2014. Ann. Oncol. 26, 259–271 (2015).Article

CAS

PubMed

Google Scholar

Green, A. R. et al. Nottingham Prognostic Index Plus: validation of a clinical decision making tool in breast cancer in an independent series. J. Pathol. Clin. Res. 2, 32–40 (2016).Article

CAS

PubMed

PubMed Central

Google Scholar

Candido dos Reis, F. J. et al. An updated PREDICT breast cancer prognostication and treatment benefit prediction model with independent validation. Breast Cancer Res. 19, 58 (2017).Article

PubMed

PubMed Central

Google Scholar

Phung, M. T., Tin Tin, S. & Elwood, J. M. Prognostic models for breast cancer: a systematic review. BMC Cancer 19, 230 (2019).Article

PubMed

PubMed Central

Google Scholar

Senkus, E. et al. Primary breast cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann. Oncol. 26 (Suppl. 5), v8-v30 (2015).Article

PubMed

Google Scholar

Cortazar, P. et al. Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis. Lancet 384, 164–172 (2014).Article

PubMed

Google Scholar

Cardoso, F. et al. 70-Gene signature as an aid to treatment decisions in early-stage breast cancer. N. Engl. J. Med. 375, 717–729 (2016).Article

CAS

PubMed

Google Scholar

Sparano, J. A. et al. Prospective validation of a 21-gene expression assay in breast cancer. N. Engl. J. Med. 373, 2005–2014 (2015).Article

CAS

PubMed

PubMed Central

Google Scholar

Sparano, J. A. et al. Adjuvant chemotherapy guided by a 21-gene expression assay in breast cancer. N. Engl. J. Med. 379, 111–121 (2018).Article

CAS

PubMed

PubMed Central

Google Scholar

Harris, L. N. et al. Use of biomarkers to guide decisions on adjuvant systemic therapy for women with early-stage invasive breast cancer: American Society of Clinical Oncology clinical practice guideline. J. Clin. Oncol. 34, 1134–1150 (2016).Article

CAS

PubMed

PubMed Central

Google Scholar

Krop, I. et al. Use of biomarkers to guide decisions on adjuvant systemic therapy for women with early-stage invasive breast cancer: American Society of Clinical Oncology clinical practice guideline focused update. J. Clin. Oncol. 35, 2838–2847 (2017).Article

PubMed

Google Scholar

Nitz, U. et al. West German Study PlanB trial: adjuvant four cycles of epirubicin and cyclophosphamide plus docetaxel versus six cycles of docetaxel and cyclophosphamide in HER2-negative early breast cancer. J. Clin. Oncol. 37, 799–808 (2019).Article

CAS

PubMed

Google Scholar

Sestak, I. Risk stratification in early breast cancer in premenopausal and postmenopausal women: integrating genomic assays with clinicopathological features. Curr. Opin. Oncol. 1, 29–34 (2018).Article

Google Scholar

McLaughlin, S. A. Surgical management of the breast: breast conservation therapy and mastectomy. Surg. Clin. North Am. 93, 411–428 (2013).Article

PubMed

Google Scholar

Margenthaler, J. A. & Ollila, D. W. Breast conservation therapy versus mastectomy: shared decision-making strategies and overcoming decisional conflicts in your patients. Ann. Surg. Oncol. 23, 3133–3137 (2016).Article

PubMed

Google Scholar

Buchholz, T. A., Mittendorf, E. A. & Hunt, K. K. Surgical considerations after neoadjuvant chemotherapy: breast conservation therapy. J. Natl Cancer Inst. Monogr. 2015, 11–14 (2015).Article

PubMed

PubMed Central

CAS

Google Scholar

Houssami, N., Macaskill, P., Luke Marinovich, M. & Morrow, M. The association of surgical margins and local recurrence in women with early-stage invasive breast cancer treated with breast-conserving therapy: a meta-analysis. Ann. Surg. Oncol. 21, 717–730 (2014).Article

PubMed

PubMed Central

Google Scholar

Morrow, M., Harris, J. R. & Schnitt, S. J. Surgical margins in lumpectomy for breast cancer — bigger is not better. N. Engl. J. Med. 367, 79–82 (2012). This commentary and the meta-analysis by Houssami et al. (2014) settled the decade-long discussions about surgical resection margins and are, therefore, landmark contributions.

Article

PubMed

Google Scholar

Tan, M. P., Sitoh, N. Y. & Sim, A. S. The value of intraoperative frozen section analysis for margin status in breast conservation surgery in a nontertiary institution. Int. J. Breast Cancer https://doi.org/10.1155/2014/715404 (2014).Article

Google Scholar

Boughey, J. C. et al. Impact of analysis of frozen-section margin on reoperation rates in women undergoing lumpectomy for breast cancer: evaluation of the National Surgical Quality Improvement Program data. Surgery 156, 190–197 (2014).Article

PubMed

Google Scholar

Haloua, M. H. et al. A systematic review of oncoplastic breast-conserving surgery: current weaknesses and future prospects. Ann. Surg. 257, 609–620 (2013).Article

PubMed

Google Scholar

Benelli, L. A new periareolar mammaplasty: the ‘round block’ technique. Aesthetic Plast. Surg. 14, 93–100 (1990).Article

CAS

PubMed

Google Scholar

Clough, K. B., Kaufman, G. J., Nos, C., Buccimazza, I. & Sarfati, I. M. Improving breast cancer surgery: a classification and quadrant per quadrant atlas for oncoplastic surgery. Ann. Surg. Oncol. 17, 1375–1391 (2010).Article

PubMed

Google Scholar

Yao, K., Winchester, D. J., Czechura, T. & Huo, D. Contralateral prophylactic mastectomy and survival: report from the national cancer data base, 1998–2002. Breast Cancer Res. Treat. 142, 465–476 (2013).Article

PubMed

Google Scholar

Vila, J., Gandini, S. & Gentilini, O. Overall survival according to type of surgery in young (≤40 years) early breast cancer patients: a systematic meta-analysis comparing breast-conserving surgery versus mastectomy. Breast 24, 175–181 (2015).Article

PubMed

Google Scholar

Lucci, A. et al. Surgical complications associated with sentinel lymph node dissection (SLND) plus axillary lymph node dissection compared with SLND alone in the American College of Surgeons Oncology Group trial Z0011. J. Clin. Oncol. 25, 3657–3663 (2007).Article

PubMed

Google Scholar

Krag, D. N. et al. Sentinel-lymph-node resection compared with conventional axillary-lymph-node dissection in clinically node-negative patients with breast cancer: overall survival findings from the NSABP B-32 randomised phase 3 trial. Lancet Oncol. 11, 927–933 (2010). This large clinical trial confirms that there is no overall survival difference between sentinel lymph node biopsy and axillary lymph node dissection.

Article

PubMed

PubMed Central

Google Scholar

Veronesi, U. et al. A randomized comparison of sentinel-node biopsy with routine axillary dissection in breast cancer. N. Engl. J. Med. 349, 546–553 (2003).Article

PubMed

Google Scholar

Giuliano, A. E. et al. Locoregional recurrence after sentinel lymph node dissection with or without axillary dissection in patients with sentinel lymph node metastases: long-term follow-up from the American College of Surgeons Oncology Group (Alliance) ACOSOG Z0011 randomized trial. Ann. Surg. 264, 413–420 (2016).Article

PubMed

Google Scholar

Balic, M., Thomssen, C., Würstlein, R., Gnant, M. & Harbeck, N. St. Gallen/Vienna 2019: a brief summary of the consensus discussion on the optimal primary breast cancer treatment. Breast Care 14, 1–8 (2019).Kaidar-Person, O., Meattini, I. & Poortmans, P. M. P. Between uncertainties and overtreatment. Int. J. Radiat. Oncol. 104, 15–16 (2019).Article

Google Scholar

Kuehn, T. et al. Sentinel-lymph-node biopsy in patients with breast cancer before and after neoadjuvant chemotherapy (SENTINA): a prospective, multicentre cohort study. Lancet Oncol. 14, 609–618 (2013).Article

PubMed

Google Scholar

King, T. A. & Morrow, M. Surgical issues in patients with breast cancer receiving neoadjuvant chemotherapy. Nat. Rev. Clin. Oncol. 12, 335–343 (2015).Article

PubMed

Google Scholar

Giuliano, A. E. et al. Axillary dissection vs no axillary dissection in women with invasive breast cancer and sentinel node metastasis: a randomized clinical trial. JAMA 305, 569–575 (2011).Article

CAS

PubMed

PubMed Central

Google Scholar

Early Breast Cancer Trialists’ Collaborative Group (EBCTCG). et al. Effect of radiotherapy after breast-conserving surgery on 10-year recurrence and 15-year breast cancer death: meta-analysis of individual patient data for 10,801 women in 17 randomised trials. Lancet 378, 1707–1716 (2011). This meta-analysis underlines that the contribution of radiation therapy should always be the standard approach for breast-conserving therapy.Article

CAS

Google Scholar

EBCTCG (Early Breast Cancer Trialists’ Collaborative Group). Effect of radiotherapy after mastectomy and axillary surgery on 10-year recurrence and 20-year breast cancer mortality: meta-analysis of individual patient data for 8135 women in 22 randomised trials. Lancet 383, 2127–2135 (2014). This meta-analysis helps us to better identify those patients who would benefit most from radiation therapy after mastectomy.Article

Google Scholar

Jatoi, I., Benson, J. R. & Kunkler, I. Hypothesis: can the abscopal effect explain the impact of adjuvant radiotherapy on breast cancer mortality? NPJ Breast Cancer 4, 8 (2018).Article

PubMed

PubMed Central

CAS

Google Scholar

Bartelink, H. et al. Whole-breast irradiation with or without a boost for patients treated with breast-conserving surgery for early breast cancer: 20-year follow-up of a randomised phase 3 trial. Lancet Oncol. 16, 47–56 (2015).Article

PubMed

Google Scholar

Poortmans, P. Postmastectomy radiation in breast cancer with one to three involved lymph nodes: ending the debate. Lancet 383, 2104–2106 (2014).Article

PubMed

Google Scholar

Poortmans, P. M. et al. Internal mammary and medial supraclavicular irradiation in breast cancer. N. Engl. J. Med. 373, 317–327 (2015).Article

CAS

PubMed

Google Scholar

Whelan, T. J. et al. Regional nodal irradiation in early-stage breast cancer. N. Engl. J. Med. 373, 307–316 (2015).Article

CAS

PubMed

PubMed Central

Google Scholar

Thorsen, L. B. J. et al. DBCG-IMN: a population-based cohort study on the effect of internal mammary node irradiation in early node-positive breast cancer. J. Clin. Oncol. 34, 314–320 (2016).Article

PubMed

Google Scholar

Curigliano, G. et al. De-escalating and escalating treatments for early-stage breast cancer: the St. Gallen International Expert Consensus Conference on the Primary Therapy of Early Breast Cancer 2017. Ann. Oncol. 29, 2153–2153 (2018).Article

CAS

PubMed

PubMed Central

Google Scholar

Oliai, C. & Hurvitz, S. A. The debate over post-mastectomy radiotherapy should continue: breast cancer. Nat. Rev. Clin. Oncol. 12, 567–568 (2015).Article

PubMed

Google Scholar

Recht, A. et al. Postmastectomy radiotherapy: an American Society of Clinical Oncology, American Society for Radiation Oncology, and Society of Surgical Oncology focused guideline update. Ann. Surg. Oncol. 24, 38–51 (2017).Article

PubMed

Google Scholar

Dodwell, D. et al. Abstract GS4-02: regional lymph node irradiation in early stage breast cancer: an EBCTCG meta-analysis of 13,000 women in 14 trials. in General Session Abstracts GS4-02-GS4-02 https://doi.org/10.1158/1538-7445.SABCS18-GS4-02 (American Association for Cancer Research, 2019).Kunkler, I. H., Canney, P., van Tienhoven, G. & Russell, N. S. MRC/EORTC (BIG 2-04) SUPREMO Trial Management Group. Elucidating the role of chest wall irradiation in ‘intermediate-risk’. breast cancer: The MRC/EORTC SUPREMO trial. Clin. Oncol. R. Coll. Radiol. 20, 31–34 (2008).CAS

PubMed

Google Scholar

Poortmans, P., Aznar, M. & Bartelink, H. Quality indicators for breast cancer: revisiting historical evidence in the context of technology changes. Semin. Radiat. Oncol. 22, 29–39 (2012).Article

PubMed

Google Scholar

Osman, S. O. S., Hol, S., Poortmans, P. M. & Essers, M. Volumetric modulated arc therapy and breath-hold in image-guided locoregional left-sided breast irradiation. Radiother. Oncol. 112, 17–22 (2014).Article

PubMed

Google Scholar

Essers, M., Poortmans, P. M., Verschueren, K., Hol, S. & Cobben, D. C. P. Should breathing adapted radiotherapy also be applied for right-sided breast irradiation? Acta Oncol. 55, 460–465 (2016).Article

PubMed

Google Scholar

Poortmans, P. M. P., Arenas, M. & Livi, L. Over-irradiation. Breast 31, 295–302 (2017).Article

PubMed

Google Scholar

Blamey, R. W. et al. Radiotherapy or tamoxifen after conserving surgery for breast cancers of excellent prognosis: British Association of Surgical Oncology (BASO) II trial. Eur. J. Cancer 49, 2294–2302 (2013).Article

CAS

PubMed

Google Scholar

McGuire, S. E. et al. Postmastectomy radiation improves the outcome of patients with locally advanced breast cancer who achieve a pathologic complete response to neoadjuvant chemotherapy. Int. J. Radiat. Oncol. Biol. Phys. 68, 1004–1009 (2007).Article

PubMed

PubMed Central

Google Scholar

Mamounas, E. P. et al. Predictors of locoregional recurrence after neoadjuvant chemotherapy: results from combined analysis of national surgical adjuvant breast and bowel project B-18 and B-27. J. Clin. Oncol. 30, 3960–3966 (2012).Article

PubMed

PubMed Central

Google Scholar

Krug, D. et al. Individualization of post-mastectomy radiotherapy and regional nodal irradiation based on treatment response after neoadjuvant chemotherapy for breast cancer: a systematic review. Strahlenther. Onkol. 194, 607–618 (2018).Article

PubMed

Google Scholar

Amoroso, V. et al. International Expert Consensus on Primary Systemic Therapy in the Management of Early Breast Cancer: Highlights of the Fifth Symposium on Primary Systemic Therapy in the Management of Operable Breast Cancer, Cremona, Italy (2013). J. Natl Cancer Inst. Monogr. 2015, 90–96 (2015).Article

PubMed

PubMed Central

Google Scholar

Offersen, B. V. et al. ESTRO consensus guideline on target volume delineation for elective radiation therapy of early stage breast cancer, version 1.1. Radiother. Oncol. 118, 205–208 (2016).Article

PubMed

Google Scholar

Haviland, J. S. et al. The UK Standardisation of Breast Radiotherapy (START) trials of radiotherapy hypofractionation for treatment of early breast cancer: 10-year follow-up results of two randomised controlled trials. Lancet Oncol. 14, 1086–1094 (2013).Article

PubMed

Google Scholar

Whelan, T. J. et al. Long-term results of hypofractionated radiation therapy for breast cancer. N. Engl. J. Med. 362, 513–520 (2010).Article

CAS

PubMed

Google Scholar

Wang, S.-L. et al. Hypofractionated versus conventional fractionated postmastectomy radiotherapy for patients with high-risk breast cancer: a randomised, non-inferiority, open-label, phase 3 trial. Lancet Oncol. 20, 352–360 (2019).Article

PubMed

Google Scholar

Brouwers, P. J. A. M. et al. Predictors for poor cosmetic outcome in patients with early stage breast cancer treated with breast conserving therapy: results of the Young Boost trial. Radiother. Oncol. 128, 434–441 (2018).Article

PubMed

Google Scholar

Polgár, C. et al. Patient selection for accelerated partial-breast irradiation (APBI) after breast-conserving surgery: recommendations of the groupe européen de curiethérapie-european society for therapeutic radiology and oncology (GEC-ESTRO) breast cancer working group based on clinical evidence (2009). Radiother. Oncol. 94, 264–273 (2010).Article

PubMed

Google Scholar

Correa, C. et al. Accelerated partial breast irradiation: executive summary for the update of an ASTRO Evidence-Based. Consensus Statement. Pract. Radiat. Oncol. 7, 73–79 (2017).Article

PubMed

Google Scholar

Miranda, F. A. et al. Accelerated partial breast irradiation: current status with a focus on clinical practice. Breast J. https://doi.org/10.1111/tbj.13164 (2018).Article

PubMed

Google Scholar

Marta, G. N. et al. Effectiveness of different accelerated partial breast irradiation techniques for the treatment of breast cancer patients: systematic review using indirect comparisons of randomized clinical trials. Rep. Pract. Oncol. Radiother. 24, 165–174 (2019).Article

PubMed

PubMed Central

Google Scholar

Veronesi, U. et al. Intraoperative radiotherapy versus external radiotherapy for early breast cancer (ELIOT): a randomised controlled equivalence trial. Lancet Oncol. 14, 1269–1277 (2013).Article

PubMed

Google Scholar

Vaidya, J. S. et al. Risk-adapted targeted intraoperative radiotherapy versus whole-breast radiotherapy for breast cancer: 5-year results for local control and overall survival from the TARGIT-A randomised trial. Lancet 383, 603–613 (2014).Article

PubMed

Google Scholar

Early Breast Cancer Trialists’ Collaborative Group (EBCTCG). et al. Relevance of breast cancer hormone receptors and other factors to the efficacy of adjuvant tamoxifen: patient-level meta-analysis of randomised trials. Lancet 378, 771–784 (2011).Article

CAS

Google Scholar

Early Breast Cancer Trialists’ Collaborative Group (EBCTCG) et al. Comparisons between different polychemotherapy regimens for early breast cancer: meta-analyses of long-term outcome among 100,000 women in 123 randomized trials. Lancet 379, 432–444 (2012). This meta-analysis demonstrates the benefits of adjuvant chemotherapy in early breast cancer.Rastogi, P. et al. Preoperative chemotherapy: updates of national surgical adjuvant breast and bowel project protocols B-18 and B-27. J. Clin. Oncol. 26, 778–785 (2008).Article

PubMed

Google Scholar

Francis, P. A. et al. Tailoring adjuvant endocrine therapy for premenopausal breast cancer. N. Engl. J. Med. 379, 122–137 (2018).Article

CAS

PubMed

PubMed Central

Google Scholar

Gnant, M. et al. Zoledronic acid combined with adjuvant endocrine therapy of tamoxifen versus anastrozol plus ovarian function suppression in premenopausal early breast cancer: final analysis of the Austrian Breast and Colorectal Cancer Study Group Trial 12. Ann. Oncol. 26, 313–320 (2015).Article

CAS

PubMed

Google Scholar

Early Breast Cancer Trialists’ Collaborative Group (EBCTCG). Aromatase inhibitors versus tamoxifen in early breast cancer: patient-level meta-analysis of the randomised trials. Lancet 386, 1341–1352 (2015). This meta-analysis demonstrates the benefit of the two individual options for adjuvant endocrine therapy in postmenopausal patients with early breast cancer.Article

CAS

Google Scholar

Pan, H. et al. 20-Year risks of breast-cancer recurrence after stopping endocrine therapy at 5 years. N. Engl. J. Med. 377, 1836–1846 (2017).Article

PubMed

PubMed Central

Google Scholar

Gray, R. et al. Increasing the dose density of adjuvant chemotherapy by shortening intervals between courses or by sequential drug administration significantly reduces both disease recurrence and breast cancer mortality: an EBCTCG meta-analysis of 21,000 women in 16 randomised trials [abstract]. SABCS GS1-GS01 (2018).Finn, R. S. et al. Palbociclib and letrozole in advanced breast cancer. N. Engl. J. Med. 375, 1925–1936 (2016).Article

CAS

PubMed

Google Scholar

Hortobagyi, G. N. et al. Ribociclib as first-line therapy for HR-positive, advanced breast cancer. N. Engl. J. Med. 375, 1738–1748 (2016).Article

CAS

PubMed

Google Scholar

Goetz, M. P. et al. MONARCH 3: abemaciclib as initial therapy for advanced breast cancer. J. Clin. Oncol. 35, 3638–3646 (2017).Article

CAS

PubMed

Google Scholar

Mackey, J. R. et al. Long-term outcomes after adjuvant treatment of sequential versus combination docetaxel with doxorubicin and cyclophosphamide in node-positive breast cancer: BCIRG-005 randomized trial. Ann. Oncol. 27, 1041–1047 (2016).Article

CAS

PubMed

Google Scholar

Del Mastro, L. et al. Fluorouracil and dose-dense chemotherapy in adjuvant treatment of patients with early-stage breast cancer: an open-label, 2×2 factorial, randomised phase 3 trial. Lancet 385, 1863–1872 (2015).Article

PubMed

CAS

Google Scholar

Blum, J. L. et al. Anthracyclines in early breast cancer: the ABC Trials-USOR 06-090, NSABP B-46-I/USOR 07132, and NSABP B-49 (NRG Oncology). J. Clin. Oncol. 35, 2647–2655 (2017).Article

CAS

PubMed

PubMed Central

Google Scholar

Gray, R. et al. Increasing the dose intensity of chemotherapy by more frequent administration or sequential scheduling: a patient-level meta-analysis of 37 298 women with early breast cancer in 26 randomised trials. Lancet 393, 1440–1452 (2019).Article

Google Scholar

Gianni, L. et al. 5-Year analysis of neoadjuvant pertuzumab and trastuzumab in patients with locally advanced, inflammatory, or early-stage HER2-positive breast cancer (NeoSphere): a multicentre, open-label, phase 2 randomised trial. Lancet Oncol. 17, 791–800 (2016).Article

CAS

PubMed

Google Scholar

von Minckwitz, G. et al. Trastuzumab emtansine for residual invasive HER2-positive breast cancer. N. Engl. J. Med. 380, 617–628 (2018).Article

Google Scholar

von Minckwitz, G. et al. Adjuvant pertuzumab and trastuzumab in early HER2-positive breast cancer. N. Engl. J. Med. 377, 122–131 (2017).Article

Google Scholar

Martin, M. et al. Neratinib after trastuzumab-based adjuvant therapy in HER2-positive breast cancer (ExteNET): 5-year analysis of a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Oncol. 18, 1688–1700 (2017).Article

CAS

PubMed

Google Scholar

Tolaney, S. M. et al. Adjuvant paclitaxel and trastuzumab for node-negative, HER2-positive breast cancer. N. Engl. J. Med. 372, 134–141 (2015).Article

PubMed

PubMed Central

CAS

Google Scholar

Tolaney, S. M. et al. Seven-year (yr) follow-up of adjuvant paclitaxel (T) and trastuzumab (H) (APT trial) for node-negative, HER2-positive breast cancer (BC). J. Clin. Oncol. 35, 511–511 (2017).Article

Google Scholar

Earl, H. M. et al. 6 versus 12 months of adjuvant trastuzumab for HER2-positive early breast cancer (PERSEPHONE): 4-year disease-free survival results of a randomised phase 3 non-inferiority trial. Lancet 393, 2599–2612 (2019).Article

CAS

PubMed

PubMed Central

Google Scholar

Pivot, X. et al. Either 6 months versus 12 months of adjuvant trastuzumab for patients with HER2-positive early breast cancer (PHARE): a randomised phase 3 trial. Lancet Oncol. 14, 741–748 (2013).Article

CAS

PubMed

Google Scholar

Joensuu, H. et al. Effect of adjuvant trastuzumab for a duration of 9 weeks vs 1 year with concomitant chemotherapy for early human epidermal growth factor receptor 2–positive breast cancer: the SOLD randomized clinical trial. JAMA Oncol. 4, 1199 (2018).Article

PubMed

PubMed Central

Google Scholar

Piccart-Gebhart, M. J. et al. Trastuzumab after adjuvant chemotherapy in HER2-positive breast cancer. N. Engl. J. Med. 353, 1659–1672 (2005).Article

CAS

PubMed

Google Scholar

Goldhirsch, A. et al. 2 years versus 1 year of adjuvant trastuzumab for HER2-positive breast cancer (HERA): an open-label, randomised controlled trial. Lancet 382, 1021–1028 (2013).Article

CAS

PubMed

Google Scholar

Hahnen, E. et al. Germline mutation status, pathological complete response, and disease-free survival in triple-negative breast cancer: secondary analysis of the GeparSixto randomized clinical trial. JAMA Oncol. 3, 1378–1385 (2017).Article

PubMed

PubMed Central

Google Scholar

Sikov, W. M. et al. Impact of the addition of carboplatin and/or bevacizumab to neoadjuvant once-per-week paclitaxel followed by dose-dense doxorubicin and cyclophosphamide on pathologic complete response rates in stage II to III triple-negative breast cancer: CALGB 40603 (Alliance). J. Clin. Oncol. 33, 13–21 (2015).Article

CAS

PubMed

Google Scholar

Masuda, N. et al. Adjuvant capecitabine for breast cancer after preoperative chemotherapy. N. Engl. J. Med. 376, 2147–2159 (2017).Article

CAS

PubMed

Google Scholar

Gnant, M. et al. Adjuvant denosumab in breast cancer (ABCSG-18): a multicentre, randomised, double-blind, placebo-controlled trial. Lancet 386, 433–443 (2015).Article

CAS

PubMed

Google Scholar

Gnant, M. et al. Adjuvant denosumab in postmenopausal patients with hormone receptor-positive breast cancer (ABCSG-18): disease-free survival results from a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Oncol. 20, 339–351 (2019).Article

CAS

PubMed

Google Scholar

Coleman, R. E. et al. Adjuvant denosumab in early breast cancer: first results from the international multicenter randomized phase III placebo controlled D-CARE study [abstract]. J. Clin. Oncol. 36 (Suppl.), a501 (2018).Article

Google Scholar

Early Breast Cancer Trialists’ Collaborative Group (EBCTCG). Adjuvant bisphosphonate treatment in early breast cancer: meta-analyses of individual patient data from randomised trials. Lancet 386, 1353–1361 (2015).Article

CAS

Google Scholar

Coleman, R. E. et al. Benefits and risks of adjuvant treatment with zoledronic acid in stage II/III breast cancer. 10 years follow-up of the AZURE randomized clinical trial (BIG 01/04). J. Bone Oncol. 13, 123–135 (2018).Article

CAS

PubMed

PubMed Central

Google Scholar

Cardoso, F. et al. 4th ESO–ESMO international consensus guidelines for advanced breast cancer (ABC 4)†. Ann. Oncol. 29, 1634–1657 (2018).Article

CAS

PubMed

Google Scholar

Golse, N. & Adam, R. Liver metastases from breast cancer: what role for surgery? Indications and results. Clin. Breast Cancer 17, 256–265 (2017).Article

PubMed

Google Scholar

Xie, Y. et al. Surgery of the primary tumor improves survival in women with stage IV breast cancer in southwest China: a retrospective analysis. Medicine 96, e7048 (2017).Article

PubMed

PubMed Central

Google Scholar

Shien, T. & Doihara, H. Resection of the primary tumor in stage IV breast cancer. World J. Clin. Oncol. 5, 82–85 (2014).Article

PubMed

PubMed Central

Google Scholar

Badwe, R. et al. Locoregional treatment versus no treatment of the primary tumour in metastatic breast cancer: an open-label randomised controlled trial. Lancet Oncol. 16, 1380–1388 (2015).Article

PubMed

Google Scholar

Soran, A., Ozbas, S., Kelsey, S. F. & Gulluoglu, B. M. Randomized trial comparing locoregional resection of primary tumor with no surgery in stage IV breast cancer at the presentation (Protocol MF07-01): a study of Turkish Federation of the National Societies for Breast Diseases. Breast J. 15, 399–403 (2009).Article

PubMed

Google Scholar

Fitzal, F. et al. Impact of breast surgery in primary metastasized breast cancer: outcomes of the prospective randomized phase III ABCSG-28 POSYTIVE Trial. Ann. Surg. https://doi.org/10.1097/SLA.0000000000002771 (2018).Article

PubMed

Google Scholar

Barinoff, J. et al. Primary metastatic breast cancer in the era of targeted therapy — prognostic impact and the role of breast tumour surgery. Eur. J. Cancer 83, 116–124 (2017).Article

PubMed

Google Scholar

Shien, T. et al. A randomized controlled trial comparing primary tumor resection plus systemic therapy with systemic therapy alone in metastatic breast cancer (JCOG1017 PRIM-BC). J. Clin. Oncol. 35, TPS588–TPS588 (2017).Article

Google Scholar

Cameron, D. Removing the primary tumour in metastatic breast cancer. Lancet Oncol. 16, 1284–1285 (2015).Article

PubMed

Google Scholar

Dare, A. J. et al. Surgical Services for Cancer Care. in Cancer: Disease Control Priorities, Third Edition (Volume 3) (eds. Gelband, H., Jha, P., Sankaranarayanan, R. & Horton, S.) (The International Bank for Reconstruction and Development/The World Bank, 2015).Phillips, C., Jeffree, R. & Khasraw, M. Management of breast cancer brain metastases: a practical review. Breast 31, 90–98 (2017).Article

PubMed

Google Scholar

Thavarajah, N. et al. Continued success in providing timely palliative radiation therapy at the rapid response radiotherapy program: a review of 2008–2012. Curr. Oncol. 20, e206–e211 (2013).Article

CAS

PubMed

PubMed Central

Google Scholar

Chow, E. et al. Single versus multiple fractions of repeat radiation for painful bone metastases: a randomised, controlled, non-inferiority trial. Lancet Oncol. 15, 164–171 (2014).Article

PubMed

Google Scholar

Sologuren, I., Rodríguez-Gallego, C. & Lara, P. C. Immune effects of high dose radiation treatment: implications of ionizing radiation on the development of bystander and abscopal effects. Transl Cancer Res. 3, 18-31–31 (2014).

Google Scholar

Morgan, S. C. & Parker, C. C. Local treatment of metastatic cancer — killing the seed or disturbing the soil? Nat. Rev. Clin. Oncol. 8, 504–506 (2011).Article

PubMed

Google Scholar

Morgan, S., Caudrelier, J.-M. & Clemons, M. Radiotherapy to the primary tumor is associated with improved survival in stage IV breast cancer [abstract]. SABCS P4, 16–06 (2012).

Google Scholar

Bernier, J. Immuno-oncology: allying forces of radio- and immuno-therapy to enhance cancer cell killing. Crit. Rev. Oncol. Hematol. 108, 97–108 (2016).Article

PubMed

Google Scholar

Fietz, T. et al. Palliative systemic therapy and overall survival of 1,395 patients with advanced breast cancer — rResults from the prospective German TMK cohort study. Breast. 34, 122–130 (2017).Article

PubMed

Google Scholar

Rugo, H. S. et al. Endocrine therapy for hormone receptor-positive metastatic breast cancer: American Society of Clinical Oncology guideline. J. Clin. Oncol. 34, 3069–3103 (2016).Article

CAS

PubMed

Google Scholar

Turner, N. C. et al. Overall survival with palbociclib and fulvestrant in advanced breast cancer. N. Engl. J. Med. 379, 1926–1936 (2018).Article

CAS

PubMed

Google Scholar

Miles, D. W. et al. First-line bevacizumab in combination with chemotherapy for HER2-negative metastatic breast cancer: pooled and subgroup analyses of data from 2447 patients. Ann. Oncol. 24, 2773–2780 (2013).Article

CAS

PubMed

Google Scholar

Giordano, S. H. et al. Systemic therapy for patients with advanced human epidermal growth factor receptor 2-positive breast cancer: American Society of Clinical Oncology clinical practice guideline. J. Clin. Oncol. 32, 2078–2099 (2014).Article

CAS

PubMed

PubMed Central

Google Scholar

Partridge, A. H. et al. Chemotherapy and targeted therapy for women with human epidermal growth factor receptor 2-negative (or unknown) advanced breast cancer: American Society of Clinical Oncology clinical practice guideline. J. Clin. Oncol. 32, 3307–3329 (2014).Article

PubMed

PubMed Central

Google Scholar

Schmid, P. et al. Atezolizumab and nab-paclitaxel in advanced triple-negative breast cancer. N. Engl. J. Med. 379, 2108–2121 (2018).Article

CAS

PubMed

Google Scholar

Marinovich, M. L. et al. Early prediction of pathologic response to neoadjuvant therapy in breast cancer: systematic review of the accuracy of MRI. Breast 21, 669–677 (2012).Article

CAS

PubMed

Google Scholar

Avril, S. et al. 18F-FDG PET/CT for monitoring of treatment response in breast cancer. J. Nucl. Med. 57, 34S–39SS (2016).Article

CAS

PubMed

Google Scholar

Marinovich, M. L. et al. Meta-analysis of magnetic resonance imaging in detecting residual breast cancer after neoadjuvant therapy. J. Natl Cancer Inst. 105, 321–333 (2013).Article

CAS

PubMed

Google Scholar

Marinovich, M. L. et al. Agreement between MRI and pathologic breast tumor size after neoadjuvant chemotherapy, and comparison with alternative tests: individual patient data meta-analysis. BMC Cancer 15, 662 (2015).Article

PubMed

PubMed Central

CAS

Google Scholar

Humbert, O. et al. Role of positron emission tomography for the monitoring of response to therapy in breast cancer. Oncologist 20, 94–104 (2015).Article

PubMed

PubMed Central

Google Scholar

Pennant, M. et al. A systematic review of positron emission tomography (PET) and positron emission tomography/computed tomography (PET/CT) for the diagnosis of breast cancer recurrence. Health Technol. Assess. 14, 1–103 (2010).Article

CAS

PubMed

Google Scholar

Shachar, S. S. Assessing treatment response in metastatic breast cancer. Am. J. Hematol. Oncol. 12, (2016).Lee, C. I. et al. Comparative effectiveness of imaging modalities to determine metastatic breast cancer treatment response. Breast 24, 3–11 (2015).Article

PubMed

Google Scholar

Pagani, O. et al. Adjuvant exemestane with ovarian suppression in premenopausal breast cancer. N. Engl. J. Med. 371, 107–118 (2014).Article

PubMed

PubMed Central

CAS

Google Scholar

Francis, P., Regan, M. & Fleming, G. Adjuvant ovarian suppression in premenopausal breast cancer. N. Engl. J. Med. 372, 1672–1673 (2015).Article

CAS

Google Scholar

Mao, J. J. et al. Electroacupuncture versus gabapentin for hot flashes among breast cancer survivors: a randomized placebo-controlled trial. J. Clin. Oncol. 33, 3615–3620 (2015).Article

CAS

PubMed

PubMed Central

Google Scholar

Elkins, G. et al. Randomized trial of a hypnosis intervention for treatment of hot flashes among breast cancer survivors. J. Clin. Oncol. 26, 5022–5026 (2008).Article

PubMed

PubMed Central

Google Scholar

Loprinzi, C. L. et al. Venlafaxine in management of hot flashes in survivors of breast cancer: a randomised controlled trial. Lancet 356, 2059–2063 (2000).Article

CAS

PubMed

Google Scholar

Niravath, P. Aromatase inhibitor-induced arthralgia: a review. Ann. Oncol. 24, 1443–1449 (2013).Article

CAS

PubMed

Google Scholar

Barton, D. L. et al. Impact of vaginal dehydroepiandosterone (DHEA) on vaginal symptoms in female cancer survivors: Trial N10C1 (Alliance). J. Clin. Oncol. 32, 9507–9507 (2014).Article

Google Scholar

Razvi, Y. et al. ASCO, NCCN, MASCC/ESMO: a comparison of antiemetic guidelines for the treatment of chemotherapy-induced nausea and vomiting in adult patients. Support. Care Cancer 27, 87–95 (2019).Article

PubMed

Google Scholar

Gulati, G. et al. Prevention of Cardiac Dysfunction During Adjuvant Breast Cancer Therapy (PRADA): a 2×2 factorial, randomized, placebo-controlled, double-blind clinical trial of candesartan and metoprolol. Eur. Heart J. 37, 1671–1680 (2016).Article

CAS

PubMed

PubMed Central

Google Scholar

Smith, E. M. L. et al. Effect of duloxetine on pain, function, and quality of life among patients with chemotherapy-induced painful peripheral neuropathy: a randomized clinical trial. JAMA 309, 1359–1367 (2013).Article

CAS

PubMed

PubMed Central

Google Scholar

Hershman, D. L. et al. Prevention and management of chemotherapy-induced peripheral neuropathy in survivors of adult cancers: American Society of Clinical Oncology clinical practice guideline. J. Clin. Oncol. 32, 1941–1967 (2014).Article

CAS

PubMed

Google Scholar

Hanai, A. et al. Effects of cryotherapy on objective and subjective symptoms of paclitaxel-induced neuropathy: prospective self-controlled trial. J. Natl Cancer Inst. 110, 141–148 (2018).Article

CAS

PubMed

Google Scholar

Kadakia, K. C., Rozell, S. A., Butala, A. A. & Loprinzi, C. L. Supportive cryotherapy: a review from head to toe. J. Pain Symptom Manage. 47, 1100–1115 (2014).Article

PubMed

Google Scholar

Hou, S., Huh, B., Kim, H. K., Kim, K.-H. & Abdi, S. Treatment of chemotherapy-induced peripheral neuropathy: systematic review and recommendations. Pain Physician 21, 571–592 (2018).PubMed

Google Scholar

Ahmed, R. L., Schmitz, K. H., Prizment, A. E. & Folsom, A. R. Risk factors for lymphedema in breast cancer survivors, the Iowa Women’s Health Study. Breast Cancer Res. Treat. 130, 981–991 (2011).Article

PubMed

PubMed Central

Google Scholar

Gillespie, T. C., Sayegh, H. E., Brunelle, C. L., Daniell, K. M. & Taghian, A. G. Breast cancer-related lymphedema: risk factors, precautionary measures, and treatments. Gland. Surg. 7, 379–403 (2018).Article

PubMed

PubMed Central

Google Scholar

Runowicz, C. D. et al. American Cancer Society/American Society of Clinical Oncology breast cancer survivorship care guideline. J. Clin. Oncol. 34, 611–635 (2016).Article

CAS

PubMed

Google Scholar

Velikova, G. et al. Quality of life after postmastectomy radiotherapy in patients with intermediate-risk breast cancer (SUPREMO): 2-year follow-up results of a randomised controlled trial. Lancet Oncol. 19, 1516–1529 (2018).Article

PubMed

Google Scholar

Hofmann, D. et al. WSG ADAPT — adjuvant dynamic marker-adjusted personalized therapy trial optimizing risk assessment and therapy response prediction in early breast cancer: study protocol for a prospective, multi-center, controlled, non-blinded, randomized, investigator initiated phase II/III trial. Trials 14, 261 (2013).Article

PubMed

PubMed Central

Google Scholar

Robertson, J. F. R., Dowsett, M. & Bliss, J. M. Peri-operative aromatase inhibitor treatment in determining or predicting long-term outcome in early breast cancer — the POETIC Trial (CRUK/07/015) [abstract]. SABCS GS1-03 (2017).Ellis, M. J. et al. Ki67 Proliferation index as a tool for chemotherapy decisions during and after neoadjuvant aromatase inhibitor treatment of breast cancer: results from the American College of Surgeons Oncology Group Z1031 trial (Alliance). J. Clin. Oncol. 35, 1061–1069 (2017).Article

CAS

PubMed

PubMed Central

Google Scholar

Hölzel, D. et al. Improved systemic treatment for early breast cancer improves cure rates, modifies metastatic pattern and shortens post-metastatic survival: 35-year results from the munich cancer registry. J. Cancer Res. Clin. Oncol. 143, 1701–1712 (2017).Article

PubMed

Google Scholar

Hölzel, D. et al. Survival of de novo stage IV breast cancer patients over three decades. J. Cancer Res. Clin. Oncol. 143, 509–519 (2017).Article

PubMed

Google Scholar

Angus, L. et al. The genomic landscape of 501 metastatic breast cancer patients [abstract]. SABCS GS1-07 (2018).Desmedt, C. et al. Unraveling lobular breast cancer progression and endocrine resistance mechanisms through genomic and immune characterization of matched primary and metastatic samples [abstract]. SABCS GS1–06 (2018).

Google Scholar

Baselga, J. et al. Buparlisib plus fulvestrant versus placebo plus fulvestrant in postmenopausal, hormone receptor-positive, HER2-negative, advanced breast cancer (BELLE-2): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Oncol. 18, 904–916 (2017).Article

CAS

PubMed

PubMed Central

Google Scholar

André, F. et al. Alpelisib for PIK3CA-mutated, hormone receptor-positive advanced breast cancer. N. Engl. J. Med. 380, 1929–1940 (2019).Article

PubMed

Google Scholar

Baselga, J. et al. Phase III study of taselisib (GDC-0032) + fulvestrant (FULV) v FULV in patients (pts) with estrogen receptor (ER)-positive, PIK3CA-mutant (MUT), locally advanced or metastatic breast cancer (MBC): primary analysis from SANDPIPER. J. Clin. Oncol. 36, LBA1006–LBA1006 (2018).Article

Google Scholar

Kim, S.-B. et al. Ipatasertib plus paclitaxel versus placebo plus paclitaxel as first-line therapy for metastatic triple-negative breast cancer (LOTUS): a multicentre, randomised, double-blind, placebo-controlled, phase 2 trial. Lancet Oncol. 18, 1360–1372 (2017).Article

CAS

PubMed

PubMed Central

Google Scholar

Schmid, P. et al. AZD5363 plus paclitaxel versus placebo plus paclitaxel as first-line therapy for metastatic triple-negative breast cancer (PAKT): a randomised, double-blind, placebo-controlled, phase II trial. J. Clin. Oncol. 36 (15 Suppl.), 1007 (2018).Article

Google Scholar

Jones, R. H. et al. Capivasertib (AZD5363) plus fulvestrant versus placebo plus fulvestrant after relapse or progression on an aromatase inhibitor in metastatic ER-positive breast cancer (FAKTION): a randomized, double-blind, placebo-controlled, phase II trial [abstract]. J. Clin. Oncol. 37 (no. 15_suppl), 1005–1005 (2019).Article

Google Scholar

Yardley, D. A. et al. Randomized phase II, double-blind, placebo-controlled study of exemestane with or without entinostat in postmenopausal women with locally recurrent or metastatic estrogen receptor-positive breast cancer progressing on treatment with a nonsteroidal aromatase inhibitor. J. Clin. Oncol. 31, 2128–2135 (2013).Article

CAS

PubMed

PubMed Central

Google Scholar

Ogitani, Y. et al. DS-8201a, a novel HER2-targeting ADC with a novel DNA Topoisomerase I inhibitor, demonstrates a promising antitumor efficacy with differentiation from T-DM1. Clin. Cancer Res. 22, 5097–5108 (2016).Article

CAS

PubMed

Google Scholar

Tamura, K. et al. Trastuzumab deruxtecan (DS-8201a) in patients with advanced HER2-positive breast cancer previously treated with trastuzumab emtansine: a dose-expansion, phase 1 study. Lancet Oncol. 20, 816–826 (2019).Article

CAS

PubMed

Google Scholar

Burris III, H. A., Giaccone, G. & Im, S. A. Updated findings of a first-in-human phase 1 study of margetuximab, an Fc-optimized chimeric monoclonal antibody, in patients with HER2-positive advanced solid tumors [abstract]. Am. Soc. Clin. Oncol. Meet. 33 (no. 15_suppl), A523 (2015).Article

Google Scholar

Rugo, H. S. et al. SOPHIA primary analysis: a phase 3 (P3) study of margetuximab (M) + chemotherapy (C) versus trastuzumab (T) + C in patients (pts) with HER2+ metastatic (met) breast cancer (MBC) after prior anti-HER2 therapies (Tx) [abstract]. J. Clin. Oncol. 37 (Suppl.), Abstr 1000 (2019).Article

Google Scholar

Hyman, D. M., Piha-Paul, S. & Rodon, J. Neratinib in HER2- or HER3-mutant solid tumors: SUMMIT, a global, multi-histology, open-label, phase 2 ‘basket’ study [abstract]. Am. Assoc. Cancer Res. Meet. CT001 (2017).Saura, C. et al. Neratinib + capecitabine versus lapatinib + capecitabine in patients with HER2+ metastatic breast cancer previously treated with ≥2 HER2-directed regimens: findings from the multinational, randomized, phase III NALA trial [abstract]. J. Clin. Oncol. 37 (Suppl.), Abstract 1002 (2019).Article

Google Scholar

Gucalp, A. et al. Phase II trial of bicalutamide in patients with androgen receptor-positive, estrogen receptor-negative metastatic breast cancer. Clin. Cancer Res. 19, 5505–5512 (2013).Article

CAS

PubMed

PubMed Central

Google Scholar

Cortes, J., Crown, J. & Awada, A. Overall survival (OS) from the phase 2 study of enzalutamide (ENZA), an androgen receptor (AR) signaling inhibitor, in AR+ advanced triple-negative breast cancer (aTNBC) [abstract]. Eur. Cancer Congr. 51 (Suppl. 3), 1802 (2015).

Google Scholar

Gelmon, K. A. et al. Olaparib in patients with recurrent high-grade serous or poorly differentiated ovarian carcinoma or triple-negative breast cancer: a phase 2, multicentre, open-label, non-randomised study. Lancet Oncol. 12, 852–861 (2011).Article

CAS

PubMed

Google Scholar

Nanda, R. et al. Pembrolizumab in patients with advanced triple-negative breast cancer: phase Ib KEYNOTE-012 Study. J. Clin. Oncol. 34, 2460–2467 (2016).Article

CAS

PubMed

PubMed Central

Google Scholar

Schmid, P., Cruz, C. & Braiteh, F. S. Atezolizumab in metastatic triple-negative breast cancer: long-term clinical outcomes and biomarker analyses [abstract]. Am. Assoc. Cancer Res. 77, A2986 (2017).

Google Scholar

André, F. et al. Alpelisib (ALP) + fulvestrant (FUL) for advanced breast cancer (ABC): results of the phase 3 SOLAR-1 trial [abstract]. ESMO LBA3 PR (2018).Hyman, D. M. et al. HER kinase inhibition in patients with HER2- and HER3-mutant cancers. Nature 554, 189–194 (2018).Article

CAS

PubMed

PubMed Central

Google Scholar

Hartley, R. L., Stone, J. P. & Temple-Oberle, C. Breast cancer in transgender patients: a systematic review. Part 1: male to female. Eur. J. Surg. Oncol. 44, 1455–1462 (2018).Article

PubMed

Google Scholar

Cardoso, F. et al. Characterization of male breast cancer: results of the EORTC 10085/TBCRC/BIG/NABCG International Male Breast Cancer Program. Ann. Oncol. 29, 405–417 (2017).PubMed Central

Google Scholar

Di Oto, E. et al. X chromosome gain is related to increased androgen receptor expression in male breast cancer. Virchows Arch. 473, 155–163 (2018).Article

PubMed

CAS

Google Scholar

Severson, T. M. & Zwart, W. A review of estrogen receptor/androgen receptor genomics in male breast cancer. Endocr. Relat. Cancer 24, R27–R34 (2017).Article

CAS

PubMed

Google Scholar

Deb, S. et al. PIK3CA mutations are frequently observed in BRCAX but not BRCA2-associated male breast cancer. Breast Cancer Res. 15, R69 (2013).Article

PubMed

PubMed Central

Google Scholar

Gucalp, A. et al. Male breast cancer: a disease distinct from female breast cancer. Breast Cancer Res. Treat. 173, 37–48 (2019).Article

PubMed

Google Scholar

Korde, L. A. et al. Multidisciplinary meeting on male breast cancer: summary and research recommendations. J. Clin. Oncol. 28, 2114–2122 (2010).Article

PubMed

PubMed Central

Google Scholar

Cardoso, F. et al. Early breast cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann. Oncol. 30, 1194–1220 (2019).Article

PubMed

Google Scholar

Bareche, Y. et al. Unravelling triple-negative breast cancer molecular heterogeneity using an integrative multiomic analysis. Ann. Oncol. 29, 895–902 (2018).Article

CAS

PubMed

PubMed Central

Google Scholar

Lehmann, B. D. & Pietenpol, J. A. Clinical implications of molecular heterogeneity in triple negative breast cancer. Breast 24, S36–S40 (2015).Article

PubMed

Google Scholar

Lehmann, B. D. et al. Refinement of triple-negative breast cancer molecular subtypes: implications for neoadjuvant chemotherapy selection. PLOS ONE 11, e0157368 (2016).Article

PubMed

PubMed Central

CAS

Google Scholar

Burstein, M. D. et al. Comprehensive genomic analysis identifies novel subtypes and targets of triple-negative breast cancer. Clin. Cancer Res. 21, 1688–1698 (2015).Article

CAS

PubMed

Google Scholar

Siu, A. L. & on behalf of the U.S. Preventive Services Task Force. Screening for breast cancer: U.S. Preventive Services Task Force recommendation statement. Ann. Intern. Med. 164, 279 (2016).Article

PubMed

Google Scholar

Klarenbach, S. et al. Recommendations on screening for breast cancer in women aged 40–74 years who are not at increased risk for breast cancer. Can. Med. Assoc. J. 190, E1441–E1451 (2018).Article

Google Scholar

Oeffinger, K. C. et al. Breast cancer screening for women at average risk: 2015 guideline update from the American Cancer Society. JAMA 314, 1599 (2015).Article

CAS

PubMed

PubMed Central

Google Scholar

European Commission Initiative on Breast Cancer. Recommendations from European Breast Guidelines Europa.eu https://ecibc.jrc.ec.europa.eu/recommendations/list/Professional (2019).Dawood, S. et al. International expert panel on inflammatory breast cancer: consensus statement for standardized diagnosis and treatment. Ann. Oncol. 22, 515–523 (2011).Article

CAS

PubMed

Google Scholar

Cserni, G., Charafe-Jauffret, E. & van Diest, P. J. Inflammatory breast cancer: the pathologists’ perspective. Eur. J. Surg. Oncol. 44, 1128–1134 (2018).Article

CAS

PubMed

Google Scholar

Cheang, M. C. U. et al. Defining breast cancer intrinsic subtypes by quantitative receptor expression. Oncologist 20, 474–482 (2015).Article

CAS

PubMed

PubMed Central

Google Scholar

Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature 490, 61–70 (2012). This research establishes the contemporary method of classifying breast cancer into clinically relevant molecular subtypes.

Article

CAS

Google Scholar

Hoadley, K. A., Andre, F., Ellis, M. J. & Perou, C. M. Breast cancer intrinsic subtypes (Poster). Nat. Rev. Clin. Oncol. https://www.nature.com/documents/nrclinonc_posters_breastcancer.pdf (2014).Desmedt, C. et al. Genomic characterization of primary invasive lobular breast cancer. J. Clin. Oncol. 34, 1872–1881 (2016).Article

CAS

PubMed

Google Scholar

Ciriello, G. et al. Comprehensive molecular portraits of invasive lobular breast cancer. Cell 163, 506–519 (2015).Article

CAS

PubMed

PubMed Central

Google Scholar

Vasudev, P. & Onuma, K. Secretory breast carcinoma: unique, triple-negative carcinoma with a favorable prognosis and characteristic molecular expression. Arch. Pathol. Lab. Med. 135, 1606–1610 (2011).Article

PubMed

Google Scholar

Martelotto, L. G. et al. Genomic landscape of adenoid cystic carcinoma of the breast. J. Pathol. 237, 179–189 (2015).Article

CAS

PubMed

PubMed Central

Google Scholar

Goss, P. E. et al. Extending aromatase-inhibitor adjuvant therapy to 10 years. N. Engl. J. Med. 375, 209–219 (2016).Article

CAS

PubMed

PubMed Central

Google Scholar

Liang, M. et al. Association between CHEK2*1100delC and breast cancer: a systematic review and meta-analysis. Mol. Diagn. Ther. 22, 397–407 (2018).Article

CAS

PubMed

Google Scholar

Wang, X. et al. Breast cancer risk and germline genomic profiling of women with neurofibromatosis type 1 who developed breast cancer. Genes. Chromosomes Cancer 57, 19–27 (2018).Article

CAS

PubMed

Google Scholar

McCart Reed, A. E. et al. Phenotypic and molecular dissection of metaplastic breast cancer and the prognostic implications: prognostic features of metaplastic breast cancer. J. Pathol. 247, 214–227 (2019).Article

CAS

PubMed

Google Scholar

Wendt, C. & Margolin, S. Identifying breast cancer susceptibility genes — a review of the genetic background in familial breast cancer. Acta Oncol. 58, 135–146 (2019).Article

CAS

PubMed

Google Scholar

Couch, F. J. et al. Associations between cancer predisposition testing panel genes and breast cancer. JAMA Oncol. 3, 1190 (2017).Article

PubMed

PubMed Central

Google Scholar

Nguyen, J. et al. EORTC QLQ-BR23 and FACT-B for the assessment of quality of life in patients with breast cancer: a literature review. J. Comp. Eff. Res. 4, 157–166 (2015).Article

PubMed

Google Scholar

McLachlan, S. A., Devins, G. M. & Goodwin, P. J. Factor analysis of the psychosocial items of the EORTC QLQ-C30 in metastatic breast cancer patients participating in a psychosocial intervention study. Qual. Life Res. 8, 311–317 (1999).Article

CAS

PubMed

Google Scholar

Bjelic-Radisic, V. et al. An international update of the EORTC questionnaire for assessing quality of life in breast cancer patients (EORTC QLQ-BC23) — EORTC QLQ-BR45. Ann. Oncol. 29, viii58–viii86 (2018).Article

Google Scholar

Ganz, P. A., Kwan, L., Stanton, A. L., Bower, J. E. & Belin, T. R. Physical and psychosocial recovery in the year after primary treatment of breast cancer. J. Clin. Oncol. 29, 1101–1109 (2011).Article

PubMed

PubMed Central

Google Scholar

Revicki, D. A. et al. Predicting EuroQol (EQ-5D) scores from the patient-reported outcomes measurement information system (PROMIS) global items and domain item banks in a United States sample. Qual. Life Res. 18, 783–791 (2009).Article

PubMed

PubMed Central

Google Scholar

Hays, R. D., Bjorner, J. B., Revicki, D. A., Spritzer, K. L. & Cella, D. Development of physical and mental health summary scores from the patient-reported outcomes measurement information system (PROMIS) global items. Qual. Life Res. 18, 873–880 (2009).Article

PubMed

PubMed Central

Google Scholar

Bevans, M., Ross, A. & Cella, D. Patient-reported outcomes measurement information system (PROMIS): efficient, standardized tools to measure self-reported health and quality of life. Nurs. Outlook 62, 339–345 (2014).Article

PubMed

PubMed Central

Google Scholar

Download referencesAcknowledgementsThe authors thank N. Radosevic-Robin (Jean Perrin Comprehensive Cancer Centre, France) for her assistance in preparing Fig. 1. N. Houssami receives research support through a National Breast Cancer Foundation (NBCF, Australia) Breast Cancer Research Leadership Fellowship. K.R. acknowledges research funding from the Clinical and Translational Sciences Award (CTSA) grant number KL2 TR002379 from the National Centre for Advancing Translational Sciences, a component of the US National Institutes of Health.Author informationAuthors and AffiliationsLMU Munich, University Hospital, Department of Obstetrics and Gynecology, Breast Center and Comprehensive Cancer Center (CCLMU), Munich, GermanyNadia HarbeckDepartment of Pathology and Biopathology, Jean Perrin Comprehensive Cancer Centre, UMR INSERM 1240, University Clermont Auvergne, Clermont-Ferrand, FranceFrédérique Penault-LlorcaIOB Institute of Oncology, Quironsalud Group, Madrid and Barcelona, SpainJavier CortesVall d´Hebron Institute of Oncology, Barcelona, SpainJavier CortesComprehensive Cancer Center, Medical University of Vienna, Vienna, AustriaMichael GnantSydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, AustraliaNehmat HoussamiDepartment of Radiation Oncology, Institut Curie, Paris, FrancePhilip PoortmansUniversité PSL, Paris, FrancePhilip PoortmansDepartment of Oncology, Mayo Clinic, Rochester, MN, USAKathryn RuddyHong Kong Breast Oncology Group, The University of Hong Kong, Hong Kong, ChinaJanice TsangBreast Unit, Champalimaud Clinical Center/Champalimaud Foundation, Lisbon, PortugalFatima CardosoAuthorsNadia HarbeckView author publicationsYou can also search for this author in

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PubMed Google ScholarContributionsIntroduction (all authors); Epidemiology (J.T.); Mechanisms/pathophysiology (F.P.-L.); Diagnosis, screening and prevention (N. Houssami); Management (N. Harbeck, F.C., M.G., P.P., J.C. and N. Houssami); Quality of life (K.R.); Outlook (all authors); Overview of the Primer (N. Harbeck and F.C.).Corresponding authorCorrespondence to

Nadia Harbeck.Ethics declarations

Competing interests

N. Harbeck reports honoraria for lectures and/or consulting from Agendia, Amgen, Astra Zeneca, Celgene, Daiichi-Sankyo, Genomic Health, Lilly, MSD, Novartis, Odonate, Pfizer, Roche, Sandoz/Hexal and Seattle Genetics. F.P.-L. declares personal financial interests in Abbvie, Agendia, Astrazeneca, BMS, Genomic Health, Janssen, Lilly, Merck Lifa, MSD, Myriad, Nanostring, Novartis, Pfizer and Roche; institutional financial interests in Astrazeneca, BMS, Genomic Health, MSD, Myriad, Nanostring and Roche; and congress invitations from Abbvie, Astrazeneca, BMS, MSD and Roche. J.C. has received honoraria from Celgene, Chugai, Eisai, Novartis, Pfizer, Roche and Samsung; has served as a consultant for Astrazeneca, Biothera, Celgene, Daichii Sankyo, Erytech Pharma, Merus, Polyphor, Roche and Seattle Genetics; has received research funding from Ariad, Astrazeneca, Baxalta GMBH, Bayer, Eisai, Guardant Health, Merch Sharp & Dohme, Pfizer, Puma and Roche; and has stocks in MedSIR. M.G. reports honoraria from Amgen, AstraZeneca, Celgene, Eli Lilly, Medison, Nanostring Technologies, Novartis and Roche; advisory fees from Accelsoir; research funding from AstraZeneca, Novartis, Pfizer and Roche; and travel expenses from Amgen, AstraZeneca, Celgene, Eli Lilly, Ipsen, Medison, Novartis and Pfizer. K.R. declares previous ownership of Merck and Pfizer stock (October 2016–February 2018). J.T. reports honoraria and consultancy or advisory roles for AstraZeneca, Astellas, De Novo, Eisai, Foundation Medicine, Nanostring, Novartis, Pfizer and Roche. F.C. declares consultancy roles for Amgen, Astellas/Medivation, AstraZeneca, Celgene, Daiichi-Sankyo, Eisai, Genentech, GE Oncology, GlaxoSmithKline, Macrogenics, Medscape, Merck-Sharp, Merus BV, Mylan, Mundipharma, Novartis, Pfizer, Pierre-Fabre, prIME Oncology, Roche, Sanofi, Seattle Genetics and Teva. The remaining authors declare no competing interests.

Additional informationPeer review informationNature Reviews Disease Primers thanks T. Howell, P. Neven, M. Toi and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.Publisher’s noteSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Related links

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European Organization for Research and Treatment of Cancer:

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EuroQol 5-Dimensions:

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Functional Assessment of Cancer Therapy:

http://www.facit.org/FACITOrg

Patient-Reported Outcomes Measurement Information System:

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Short Form Health Survey-36:

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Nat Rev Dis Primers 5, 66 (2019). https://doi.org/10.1038/s41572-019-0111-2Download citationAccepted: 22 July 2019Published: 23 September 2019DOI: https://doi.org/10.1038/s41572-019-0111-2Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard

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Breast cancer - Symptoms and causes - Mayo Clinic

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Overview

Breast anatomy

Enlarge image

Breast anatomy

Each breast contains 15 to 20 lobes of glandular tissue, arranged like the petals of a daisy. The lobes are further divided into smaller lobules that produce milk for breastfeeding. Small tubes, called ducts, conduct the milk to a reservoir that lies just beneath your nipple.

Breast cancer is a kind of cancer that begins as a growth of cells in the breast tissue.

After skin cancer, breast cancer is the most common cancer diagnosed in women in the United States. But breast cancer doesn't just happen in women. Everyone is born with some breast tissue, so anyone can get breast cancer.

Breast cancer survival rates have been increasing. And the number of people dying of breast cancer is steadily going down. Much of this is due to the widespread support for breast cancer awareness and funding for research.

Advances in breast cancer screening allow healthcare professionals to diagnose breast cancer earlier. Finding the cancer earlier makes it much more likely that the cancer can be cured. Even when breast cancer can't be cured, many treatments exist to extend life. New discoveries in breast cancer research are helping healthcare professionals choose the most effective treatment plans.

Breast cancer care at Mayo ClinicProducts & ServicesA Book: Beyond Breast CancerA Book: Taking Care of YouShow more products from Mayo Clinic

Types

Angiosarcoma

Ductal carcinoma in situ (DCIS)

Inflammatory breast cancer

Invasive lobular carcinoma

Lobular carcinoma in situ (LCIS)

Male breast cancer

Paget's disease of the breast

Recurrent breast cancer

Symptoms

Nipple changes

Enlarge image

Nipple changes

Breast and nipple changes can be a sign of breast cancer. Make an appointment with a healthcare professional if you notice any changes.

Signs and symptoms of breast cancer may include:

A breast lump or thickened area of skin that feels different from the surrounding tissue.

A nipple that looks flattened or turns inward.

Changes in the color of the breast skin. In people with white skin, the breast skin may look pink or red. In people with brown and Black skin, the breast skin may look darker than the other skin on the chest or it may look red or purple.

Change in the size, shape or appearance of a breast.

Changes to the skin over the breast, such as skin that looks dimpled or looks like an orange peel.

Peeling, scaling, crusting or flaking of the skin on the breast.

When to see a doctorIf you find a lump or other change in your breast, make an appointment with a doctor or other healthcare professional. Don't wait for your next mammogram to see if the change you found is breast cancer. Report any changes in your breasts even if a recent mammogram showed there was no breast cancer.

Request an appointment

CausesThe exact cause of most breast cancers isn't known. Researchers have found things that increase the risk of breast cancer. These include hormones, lifestyle choices and things in the environment. But it's not clear why some people who don't have any factors get cancer, yet others with risk factors never do. It's likely that breast cancer happens through a complex interaction of your genetic makeup and the world around you.

Healthcare professionals know that breast cancer starts when something changes the DNA inside cells in the breast tissue. A cell's DNA holds the instructions that tell a cell what to do. In healthy cells, the DNA gives instructions to grow and multiply at a set rate. The instructions tell the cells to die at a set time. In cancer cells, the DNA changes give different instructions. The changes tell the cancer cells to make many more cells quickly. Cancer cells can keep living when healthy cells would die. This causes too many cells.

The cancer cells might form a mass called a tumor. The tumor can grow to invade and destroy healthy body tissue. In time, cancer cells can break away and spread to other parts of the body. When cancer spreads, it's called metastatic cancer.

The DNA changes that lead to breast cancer most often happen in the cells that line the milk ducts. These ducts are tubes designed to carry milk to the nipple. Breast cancer that starts in the ducts is called invasive ductal carcinoma. Breast cancer also can start in cells in the milk glands. These glands, called lobules, are designed to make breast milk. Cancer that happens in the lobules is called invasive lobular carcinoma. Other cells in the breast can become cancer cells, though this isn't common.

Risk factorsFactors that may increase the risk of breast cancer include:

A family history of breast cancer. If a parent, sibling or child had breast cancer, your risk of breast cancer is increased. The risk is higher if your family has a history of getting breast cancer at a young age. The risk also is higher if you have multiple family members with breast cancer. Still, most people diagnosed with breast cancer don't have a family history of the disease.

A personal history of breast cancer. If you've had cancer in one breast, you have an increased risk of getting cancer in the other breast.

A personal history of breast conditions. Certain breast conditions are markers for a higher risk of breast cancer. These conditions include lobular carcinoma in situ, also called LCIS, and atypical hyperplasia of the breast. If you've had a breast biopsy that found one of these conditions, you have an increased risk of breast cancer.

Beginning your period at a younger age. Beginning your period before age 12 increases your risk of breast cancer.

Beginning menopause at an older age. Beginning menopause after age 55 increases the risk of breast cancer.

Being female. Women are much more likely than men are to get breast cancer. Everyone is born with some breast tissue, so anyone can get breast cancer.

Dense breast tissue. Breast tissue is made up of fatty tissue and dense tissue. Dense tissue is made of milk glands, milk ducts and fibrous tissue. If you have dense breasts, you have more dense tissue than fatty tissue in your breasts. Having dense breasts can make it harder to detect breast cancer on a mammogram. If a mammogram showed that you have dense breasts, your risk of breast cancer is increased. Talk with your healthcare team about other tests you might have in addition to mammograms to look for breast cancer.

Drinking alcohol. Drinking alcohol increases the risk of breast cancer.

Having your first child at an older age. Giving birth to your first child after age 30 may increase the risk of breast cancer.

Having never been pregnant. Having been pregnant one or more times lowers the risk of breast cancer. Never having been pregnant increases the risk.

Increasing age. The risk of breast cancer goes up as you get older.

Inherited DNA changes that increase cancer risk. Certain DNA changes that increase the risk of breast cancer can be passed from parents to children. The most well-known changes are called BRCA1 and BRCA2. These changes can greatly increase your risk of breast cancer and other cancers, but not everyone with these DNA changes gets cancer.

Menopausal hormone therapy. Taking certain hormone therapy medicines to control the symptoms of menopause may increase the risk of breast cancer. The risk is linked to hormone therapy medicines that combine estrogen and progesterone. The risk goes down when you stop taking these medicines.

Obesity. People with obesity have an increased risk of breast cancer.

Radiation exposure. If you received radiation treatments to your chest as a child or young adult, your risk of breast cancer is higher.

PreventionThings you can do to lower your risk of breast cancer

Breast self-exam

Enlarge image

Breast self-exam

To perform a breast self-exam for breast awareness, use a methodical approach that ensures you cover your entire breast. For instance, imagine that your breasts are divided into equal wedges, like pieces of a pie, and sweep your fingers along each piece in toward your nipple.

Making changes in your daily life may help lower your risk of breast cancer. Try to:

Ask about breast cancer screening. Talk with your doctor or other healthcare professional about when to begin breast cancer screening. Ask about the benefits and risks of screening. Together, you can decide what breast cancer screening tests are right for you.

Become familiar with your breasts through breast self-exam for breast awareness. You may choose to become familiar with your breasts by occasionally inspecting them during a breast self-exam for breast awareness. If there is a new change, a lump or something not typical in your breasts, report it to a healthcare professional right away.

Breast awareness can't prevent breast cancer. But it may help you to better understand the look and feel of your breasts. This might make it more likely that you'll notice if something changes.

Drink alcohol in moderation, if at all. Limit the amount of alcohol you drink to no more than one drink a day, if you choose to drink. For breast cancer prevention, there is no safe amount of alcohol. So if you're very concerned about your breast cancer risk, you may choose to not drink alcohol.

Exercise most days of the week. Aim for at least 30 minutes of exercise on most days of the week. If you haven't been active lately, ask a healthcare professional whether it's OK and start slowly.

Limit menopausal hormone therapy. Combination hormone therapy may increase the risk of breast cancer. Talk with a healthcare professional about the benefits and risks of hormone therapy.

Some people have symptoms during menopause that cause discomfort. These people may decide that the risks of hormone therapy are acceptable in order to get relief. To reduce the risk of breast cancer, use the lowest dose of hormone therapy possible for the shortest amount of time.

Maintain a healthy weight. If your weight is healthy, work to maintain that weight. If you need to lose weight, ask a healthcare professional about healthy ways to lower your weight. Eat fewer calories and slowly increase the amount of exercise.

Medicines and operations for those a high risk of breast cancerIf you have a high risk of breast cancer, you might consider other options to lower the risk. You might have a high risk if you have a family history of breast cancer. Your risk also might be higher if you have a history of precancerous cells in the breast tissue. Talk about your risk with your healthcare team. Your team might have options for lowering your risk, such as:

Preventive medicines. Using estrogen-blocking medicines can lower the risk of breast cancer in those who have a high risk. Options include medicines called selective estrogen receptor modulators and aromatase inhibitors. These medicines also are used as hormone therapy treatment for breast cancer.

These medicines carry a risk of side effects. For this reason, they're only used in those who have a very high risk of breast cancer. Discuss the benefits and risks with your healthcare team.

Preventive surgery. If you have a very high risk of breast cancer, you may consider having surgery to lower the risk of breast cancer. One option might be surgery to remove the breasts, called prophylactic mastectomy. Another option is surgery to remove the ovaries, called prophylactic oophorectomy. This operation lowers the risk of breast cancer and ovarian cancer.

More InformationBreast cancer care at Mayo ClinicBreast cancer chemopreventionGenetic testing for breast cancer: Psychological and social impact

By Mayo Clinic Staff

Breast cancer care at Mayo Clinic

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Diagnosis & treatment

Feb. 10, 2024

Show references

Cancer facts and figures 2023. American Cancer Society. https://www.cancer.org/research/cancer-facts-statistics/all-cancer-facts-figures/2023-cancer-facts-figures.html. Accessed Aug. 9, 2023.

Abraham J, et al., eds. Breast cancer. In: The Bethesda Handbook of Clinical Oncology. 6th ed. Kindle edition. Wolters Kluwer; 2023. Accessed March 30, 2023.

Breast cancer. Cancer.Net. https://www.cancer.net/cancer-types/breast-cancer/view-all. Accessed Aug. 2, 2023.

Mukwende M, et al. Erythema. In: Mind the Gap: A Handbook of Clinical Signs in Black and Brown Skin. St. George's University of London; 2020. https://www.blackandbrownskin.co.uk/mindthegap. Accessed Aug. 10, 2023.

Townsend CM Jr, et al. Diseases of the breast. In: Sabiston Textbook of Surgery: The Biological Basis of Modern Surgical Practice. 21st ed. Elsevier; 2022. https://www.clinicalkey.com. Accessed Aug. 2, 2023.

Breast cancer risk reduction. National Comprehensive Cancer Network. https://www.nccn.org/guidelines/guidelines-detail?category=2&id=1420. Accessed Aug. 2, 2023.

Breast cancer prevention (PDQ) – Patient version. National Cancer Institute. https://www.cancer.gov/types/breast/patient/breast-prevention-pdq. Accessed Aug. 2, 2023.

Breast cancer. National Comprehensive Cancer Network. https://www.nccn.org/guidelines/guidelines-detail?category=1&id=1419. Accessed Aug. 2, 2023.

Klimberg VS, et al., eds. Breast cancer diagnosis and techniques for biopsy. In: Bland and Copeland's The Breast: Comprehensive Management of Benign and Malignant Diseases. 6th ed. Elsevier; 2024. https://www.clinicalkey.com. Accessed Aug. 2, 2023.

Palliative care. National Comprehensive Cancer Network. https://www.nccn.org/guidelines/guidelines-detail?category=3&id=1454. Accessed Aug. 2, 2023.

Cancer-related fatigue. National Comprehensive Cancer Network. https://www.nccn.org/guidelines/guidelines-detail?category=3&id=1424. Accessed Aug. 2, 2023.

Breast SPOREs. National Cancer Institute. https://trp.cancer.gov/spores/breast.htm. Accessed Aug. 9, 2023.

Ami TR. Allscripts EPSi. Mayo Clinic. Jan. 31, 2023.

Ami TR. Allscripts EPSi. Mayo Clinic. April 5, 2023.

Member institutions. Alliance for Clinical Trials in Oncology. https://www.allianceforclinicaltrialsinoncology.org/main/public/standard.xhtml?path=%2FPublic%2FInstitutions. Accessed Aug. 9, 2023.

Giridhar KV (expert opinion). Mayo Clinic. Oct. 18, 2023.

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Infographic: Breast Cancer Risk

Lumpectomy

Modified radical mastectomy

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Associated Procedures

3D mammogram

Bone scan

Brachytherapy

BRCA gene test

Breast cancer risk assessment

Breast cancer supportive therapy and survivorship

Breast cancer surgery

Breast MRI

Breast self-exam for breast awareness

Chemotherapy

Chemotherapy for breast cancer

Chest X-rays

Complete blood count (CBC)

CT scan

Hormone therapy for breast cancer

Lumpectomy

Mammogram

Mastectomy

Molecular breast imaging

MRI

Positron emission tomography scan

Precision medicine for breast cancer

Radiation therapy

Radiation therapy for breast cancer

Sentinel node biopsy

Ultrasound

X-ray

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breast noun

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B1 [ C ] either of the two soft, rounded parts of a woman's chest that produce milk after she has a baby

乳房

When a woman becomes pregnant her breasts tend to grow larger.

女性懷孕後，乳房會增大。

breast cancer

乳癌

Do you think she's had breast implants?

你覺得她做過隆胸手術嗎？

更多範例减少例句Antibodies found in breast milk protect newborn babies against infection.The study showed that one in twelve women is likely to develop breast cancer.A lot of mothers find early weaning from breast milk more convenient.a silicone breast implantThey found a malignant tumour in her breast.

breast noun

(BIRD/ANIMAL)

[ C ] the front part of a bird's body

（鳥的）前胸，胸部

A robin is easy to identify because of its red breast.

知更鳥因其胸脯是紅色的很容易辨認。

[ U or C ] the meat from the front part of the body of a bird or other animal

雞胸肉;（動物的）胸肉

I had a cold chicken breast and a salad for lunch.

我午飯吃的是冷雞胸肉和沙拉。

breast of turkey

火雞的前胸肉

pigeon breasts

鴿子的前胸肉

breast noun

(CLOTHING)

[ C ] the part of a piece of clothing that covers a person's chest

上衣前部

He put a silk hanky in his breast pocket (= a pocket on the top front part of a shirt or coat).

他將一條絲綢手帕放入上衣口袋。

breast noun

(CHEST)

[ C ] literary a person's chest

（人的）胸部，胸膛

The dagger entered his breast.

匕首插入了他的胸膛。

[ C ] literary the centre of a person's feelings

心窩，胸懷

A feeling of love surged in his breast.

他心中湧起一陣愛意。

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Anatomy of the Breast

What does the inside of the breast look like? This illustration shows the makeup of breast anatomy both inside and outside.

What’s inside your breasts? Most people aren’t really sure, but if you want to understand breast cancer prevention, risk, or diagnosis, it’s important to know the kinds of tissue and structures breasts are made of. This information will help you visualize what parts of the breast your doctor is referring to. If you have been diagnosed with breast cancer, knowing this will help you talk to your doctor about surgery and other treatment options.

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What is a breast made of?

If you were assigned female at birth, your breasts contain different types of tissue:

glandular tissue, which includes the breast lobes and breast ducts

fibrous, or supportive or connective tissue, which is the same tissue that ligaments and scar tissue are made of

fatty tissue fills in the spaces between glandular and fibrous tissue and largely determines your breast size

Doctors refer to all non-fatty tissue as fibroglandular tissue. There are also bands of supportive, flexible connective tissue called ligaments, which stretch from the skin to the chest wall to hold the breast tissue in place. Muscle plays an important role too. The pectoral muscle lies against the chest wall underneath both breasts, giving them support. Blood vessels provide oxygen to the breast tissue and carry away waste.

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Embedded in the breast’s fatty and fibrous tissue are 15 to 20 glands called lobes, each of which has many smaller lobules, or sacs, that produce milk. Lobules are arranged in clusters, like bunches of grapes.

Ducts are thin tubes that carry milk to the nipple. The nipple is located in the middle of the areola, which is the darker area surrounding the nipple. Breast cancers can form in the ducts and the lobes.

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Lymph vessels filter and carry lymph fluid from the breast to the lymph nodes. Clusters of lymph nodes near the breast are located in the armpit (known as axillary lymph nodes), above the collarbone, in the neck, and in the chest.

What does a mammogram show?

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A doctor will tell you that your breasts are dense if most of the tissue seen on your mammogram is fibrous or glandular breast tissue. These tissue types appear thicker and denser than fatty tissue and will show up white on a mammogram. Because cancer cells also appear white on the image, it may be harder for radiologists to see disease in people with dense breasts. So that’s why some people with dense breasts may be asked to have extra imaging tests, such as ultrasound or MRI, which can pick up some cancers that may be missed on a mammogram.

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A single-cell and spatially resolved atlas of human breast cancers | Nature Genetics

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Published: 06 September 2021

A single-cell and spatially resolved atlas of human breast cancers

Sunny Z. Wu

ORCID: orcid.org/0000-0002-6153-04491,2 na1, Ghamdan Al-Eryani1,2 na1, Daniel Lee Roden

ORCID: orcid.org/0000-0003-2393-58051,2 na1, Simon Junankar

ORCID: orcid.org/0000-0002-3965-82781,2, Kate Harvey

ORCID: orcid.org/0000-0002-2155-52031, Alma Andersson3, Aatish Thennavan4, Chenfei Wang5, James R. Torpy

ORCID: orcid.org/0000-0002-5392-16421,2, Nenad Bartonicek

ORCID: orcid.org/0000-0003-2144-18871,2, Taopeng Wang1,2, Ludvig Larsson

ORCID: orcid.org/0000-0003-4209-29113, Dominik Kaczorowski

ORCID: orcid.org/0000-0002-9205-19346, Neil I. Weisenfeld7, Cedric R. Uytingco7, Jennifer G. Chew7, Zachary W. Bent7, Chia-Ling Chan6, Vikkitharan Gnanasambandapillai6, Charles-Antoine Dutertre8,9, Laurence Gluch10, Mun N. Hui1,11, Jane Beith11, Andrew Parker2,12, Elizabeth Robbins13, Davendra Segara12, Caroline Cooper

ORCID: orcid.org/0000-0002-3630-001914,15, Cindy Mak16,17, Belinda Chan16, Sanjay Warrier16,17, Florent Ginhoux

ORCID: orcid.org/0000-0002-2857-775518,19,20, Ewan Millar21,22,23, Joseph E. Powell6,24, Stephen R. Williams7, X. Shirley Liu

ORCID: orcid.org/0000-0003-4736-73395, Sandra O’Toole1,13,23,25, Elgene Lim

ORCID: orcid.org/0000-0001-8065-88381,2,12, Joakim Lundeberg

ORCID: orcid.org/0000-0003-4313-16013, Charles M. Perou

ORCID: orcid.org/0000-0001-9827-22474 & …Alexander Swarbrick

ORCID: orcid.org/0000-0002-3051-56761,2 Show authors

Nature Genetics

volume 53, pages 1334–1347 (2021)Cite this article

81k Accesses

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Breast cancerCancer microenvironment

AbstractBreast cancers are complex cellular ecosystems where heterotypic interactions play central roles in disease progression and response to therapy. However, our knowledge of their cellular composition and organization is limited. Here we present a single-cell and spatially resolved transcriptomics analysis of human breast cancers. We developed a single-cell method of intrinsic subtype classification (SCSubtype) to reveal recurrent neoplastic cell heterogeneity. Immunophenotyping using cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) provides high-resolution immune profiles, including new PD-L1/PD-L2+ macrophage populations associated with clinical outcome. Mesenchymal cells displayed diverse functions and cell-surface protein expression through differentiation within three major lineages. Stromal-immune niches were spatially organized in tumors, offering insights into antitumor immune regulation. Using single-cell signatures, we deconvoluted large breast cancer cohorts to stratify them into nine clusters, termed ‘ecotypes’, with unique cellular compositions and clinical outcomes. This study provides a comprehensive transcriptional atlas of the cellular architecture of breast cancer.

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Fig. 1: Cellular composition of primary breast cancers and identification of malignant epithelial cells.Fig. 2: Identifying drivers of neoplastic breast cancer cell heterogeneity.Fig. 3: T cell and innate lymphoid cell landscape of breast cancers.Fig. 4: Myeloid landscape of breast cancers.Fig. 5: Transcriptional profiling and phenotyping of diverse mesenchymal differentiation states across breast cancers.Fig. 6: Mapping breast cancer heterogeneity using spatially resolved transcriptomics.Fig. 7: Spatially mapping new heterotypic cellular interactions.Fig. 8: Deconvolution of breast cancer cohorts using single-cell signatures reveals robust ecotypes associated with patient survival and intrinsic subtypes.

Data availability

All processed scRNA-seq data are available for in-browser exploration and download through the Broad Institute Single Cell portal at https://singlecell.broadinstitute.org/single_cell/study/SCP1039. Processed scRNA-seq data from this study are also available through the Gene Expression Omnibus under accession number GSE176078. Raw scRNA-seq data from this study have been deposited with the European Genome-phenome Archive, which is hosted by the European Bioinformatics Institute and Centre for Genomic Regulation under accession no. EGAS00001005173. All spatially resolved transcriptomics data from this study are available from the Zenodo data repository (https://doi.org/10.5281/zenodo.4739739). Spatially resolved transcriptomics data from Andersson et al.56 can be downloaded from the Zenodo data repository (https://doi.org/10.5281/zenodo.3957257).

Code availability

Code related to the analyses in this study can be found on GitHub at https://github.com/Swarbricklab-code/BrCa_cell_atlas (ref. 72).

ReferencesKim, H. K. et al. Discordance of the PAM50 intrinsic subtypes compared with immunohistochemistry-based surrogate in breast cancer patients: potential implication of genomic alterations of discordance. Cancer Res. Treat. 51, 737–747 (2019).Article

CAS

PubMed

Google Scholar

Picornell, A. C. et al. Breast cancer PAM50 signature: correlation and concordance between RNA-Seq and digital multiplexed gene expression technologies in a triple negative breast cancer series. BMC Genomics 20, 452 (2019).Article

CAS

PubMed

PubMed Central

Google Scholar

Parker, J. S. et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J. Clin. Oncol. 27, 1160–1167 (2009).Article

PubMed

PubMed Central

Google Scholar

Perou, C. M. et al. Molecular portraits of human breast tumours. Nature 406, 747–752 (2000).Article

CAS

PubMed

Google Scholar

Sørlie T. et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc. Natl Acad. Sci. USA 98, 10869–10874 (2001).Article

PubMed

PubMed Central

Google Scholar

Sørlie, T. et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc. Natl Acad. Sci. USA 100, 8418–8423 (2003).Article

PubMed

PubMed Central

CAS

Google Scholar

Su, S. et al. CD10+ GPR77+ cancer-associated fibroblasts promote cancer formation and chemoresistance by sustaining cancer stemness. Cell 172, 841–856.e16 (2018).Article

CAS

PubMed

Google Scholar

Cazet, A. S. et al. Targeting stromal remodeling and cancer stem cell plasticity overcomes chemoresistance in triple negative breast cancer. Nat. Commun. 9, 2897 (2018).Article

PubMed

PubMed Central

CAS

Google Scholar

Dushyanthen, S. et al. Relevance of tumor-infiltrating lymphocytes in breast cancer. BMC Med. 13, 202 (2015).Article

PubMed

PubMed Central

CAS

Google Scholar

Cassetta, L. et al. Human tumor-associated macrophage and monocyte transcriptional landscapes reveal cancer-specific reprogramming, biomarkers, and therapeutic targets. Cancer Cell 35, 588–602.e10 (2019).Article

CAS

PubMed

PubMed Central

Google Scholar

Katzenelenbogen, Y. et al. Coupled scRNA-seq and intracellular protein activity reveal an immunosuppressive role of TREM2 in cancer. Cell 182, 872–885.e19 (2020).Article

CAS

PubMed

Google Scholar

Medler, T. R. et al. Complement C5a fosters squamous carcinogenesis and limits T cell response to chemotherapy. Cancer Cell 34, 561–578.e6 (2018).Article

CAS

PubMed

PubMed Central

Google Scholar

Nakamura, K. & Smyth, M. J. TREM2 marks tumor-associated macrophages. Signal Transduct. Target. Ther. 5, 233 (2020).Article

CAS

PubMed

PubMed Central

Google Scholar

Costa, A. et al. Fibroblast heterogeneity and immunosuppressive environment in human breast cancer. Cancer Cell 33, 463–479.e10 (2018).Article

CAS

PubMed

Google Scholar

Wu, S. Z. et al. Stromal cell diversity associated with immune evasion in human triple-negative breast cancer. EMBO J. 39, e104063 (2020).CAS

PubMed

PubMed Central

Google Scholar

Sahai, E. et al. A framework for advancing our understanding of cancer-associated fibroblasts. Nat. Rev. Cancer 20, 174–186 (2020).Article

CAS

PubMed

PubMed Central

Google Scholar

Öhlund, D. et al. Distinct populations of inflammatory fibroblasts and myofibroblasts in pancreatic cancer. J. Exp. Med. 214, 579–596 (2017).Article

PubMed

PubMed Central

CAS

Google Scholar

Biffi, G. et al. IL1-induced JAK/STAT signaling is antagonized by TGFβ to shape CAF heterogeneity in pancreatic ductal adenocarcinoma. Cancer Discov. 9, 282–301 (2019).Article

PubMed

Google Scholar

Elyada, E. et al. Cross-species single-cell analysis of pancreatic ductal adenocarcinoma reveals antigen-presenting cancer-associated fibroblasts. Cancer Discov. 9, 1102–1123 (2019).Article

CAS

PubMed

PubMed Central

Google Scholar

Puram, S. V. et al. Single-cell transcriptomic analysis of primary and metastatic tumor ecosystems in head and neck cancer. Cell 171, 1611–1624.e24 (2017).Article

CAS

PubMed

PubMed Central

Google Scholar

Lambrechts, D. et al. Phenotype molding of stromal cells in the lung tumor microenvironment. Nat. Med. 24, 1277–1289 (2018).Article

CAS

PubMed

Google Scholar

Azizi, E. et al. Single-cell map of diverse immune phenotypes in the breast tumor microenvironment. Cell 174, 1293–1308.e36 (2018).Article

CAS

PubMed

PubMed Central

Google Scholar

Savas, P. et al. Single-cell profiling of breast cancer T cells reveals a tissue-resident memory subset associated with improved prognosis. Nat. Med. 24, 986–993 (2018).Article

CAS

PubMed

Google Scholar

Kim, C. et al. Chemoresistance evolution in triple-negative breast cancer delineated by single-cell sequencing. Cell 173, 879–893.e13 (2018).Article

CAS

PubMed

PubMed Central

Google Scholar

Ali, H. R. et al. Imaging mass cytometry and multiplatform genomics define the phenogenomic landscape of breast cancer. Nat. Cancer 1, 163–175 (2020).Article

PubMed

Google Scholar

Wagner, J. et al. A single-cell atlas of the tumor and immune ecosystem of human breast cancer. Cell 177, 1330–1345.e18 (2019).CAS

PubMed

PubMed Central

Google Scholar

Aran, D., Hu, Z. & Butte, A. J. xCell: digitally portraying the tissue cellular heterogeneity landscape. Genome Biol. 18, 220 (2017).Article

PubMed

PubMed Central

CAS

Google Scholar

Lim, E. et al. Aberrant luminal progenitors as the candidate target population for basal tumor development in BRCA1 mutation carriers. Nat. Med. 15, 907–913 (2009).Article

CAS

PubMed

Google Scholar

Pliner, H. A., Shendure, J. & Trapnell, C. Supervised classification enables rapid annotation of cell atlases. Nat. Methods 16, 983–986 (2019).Article

CAS

PubMed

PubMed Central

Google Scholar

Neftel, C. et al. An integrative model of cellular states, plasticity, and genetics for glioblastoma. Cell 178, 835–849.e21 (2019).Article

CAS

PubMed

PubMed Central

Google Scholar

Tirosh, I. et al. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science 352, 189–196 (2016).Article

CAS

PubMed

PubMed Central

Google Scholar

Koboldt, D. C. et al. Comprehensive molecular portraits of human breast tumours. Nature 490, 61–70 (2012).Article

CAS

Google Scholar

Prat, A. et al. Phenotypic and molecular characterization of the claudin-low intrinsic subtype of breast cancer. Breast Cancer Res. 12, R68 (2010).Article

PubMed

PubMed Central

CAS

Google Scholar

Nielsen, T. O. et al. A comparison of PAM50 intrinsic subtyping with immunohistochemistry and clinical prognostic factors in tamoxifen-treated estrogen receptor-positive breast cancer. Clin. Cancer Res. 16, 5222–5232 (2010).Article

CAS

PubMed

PubMed Central

Google Scholar

Stoeckius, M. et al. Simultaneous epitope and transcriptome measurement in single cells. Nat. Methods 14, 865–868 (2017).Article

CAS

PubMed

PubMed Central

Google Scholar

Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888–1902.e21 (2019).Article

CAS

PubMed

PubMed Central

Google Scholar

Glajcar, A., Szpor, J., Hodorowicz-Zaniewska, D., Tyrak, K. E. & Okoń, K. The composition of T cell infiltrates varies in primary invasive breast cancer of different molecular subtypes as well as according to tumor size and nodal status. Virchows Arch. 475, 13–23 (2019).Article

CAS

PubMed

PubMed Central

Google Scholar

Li, H. et al. Dysfunctional CD8 T cells form a proliferative, dynamically regulated compartment within human melanoma. Cell 176, 775–789.e18 (2019).Article

CAS

PubMed

Google Scholar

Yamada, S., Shinozaki, K. & Agematsu, K. Involvement of CD27/CD70 interactions in antigen-specific cytotoxic T-lymphocyte (CTL) activity by perforin-mediated cytotoxicity. Clin. Exp. Immunol. 130, 424–430 (2002).Article

CAS

PubMed

PubMed Central

Google Scholar

Curtis, C. et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 486, 346–352 (2012).Article

CAS

PubMed

PubMed Central

Google Scholar

Slyper, M. et al. A single-cell and single-nucleus RNA-Seq toolbox for fresh and frozen human tumors. Nat. Med. 26, 792–802 (2020).Article

CAS

PubMed

PubMed Central

Google Scholar

Ruffell, B. et al. Leukocyte composition of human breast cancer. Proc. Natl Acad. Sci. USA 109, 2796–2801 (2012).Article

CAS

PubMed

Google Scholar

Zhang, Q. et al. Landscape and dynamics of single immune cells in hepatocellular carcinoma. Cell 179, 829–845.e20 (2019).Article

CAS

PubMed

Google Scholar

Jaitin, D. A. et al. Lipid-associated macrophages control metabolic homeostasis in a Trem2-dependent manner. Cell 178, 686–698.e14 (2019).Article

CAS

PubMed

PubMed Central

Google Scholar

Chen, J. et al. CCL18 from tumor-associated macrophages promotes breast cancer metastasis via PITPNM3. Cancer Cell 19, 541–555 (2011).Article

CAS

PubMed

PubMed Central

Google Scholar

Qiu, X. et al. Reversed graph embedding resolves complex single-cell trajectories. Nat. Methods 14, 979–982 (2017).Article

CAS

PubMed

PubMed Central

Google Scholar

Kumar, A. et al. Specification and diversification of pericytes and smooth muscle cells from mesenchymoangioblasts. Cell Rep. 19, 1902–1916 (2017).Article

CAS

PubMed

PubMed Central

Google Scholar

Thiriot, A. et al. Differential DARC/ACKR1 expression distinguishes venular from non-venular endothelial cells in murine tissues. BMC Biol. 15, 45 (2017).Article

PubMed

PubMed Central

CAS

Google Scholar

Mailhos, C. et al. Delta4, an endothelial specific notch ligand expressed at sites of physiological and tumor angiogenesis. Differentiation 69, 135–144 (2001).Article

CAS

PubMed

Google Scholar

Ubezio, B. et al. Synchronization of endothelial Dll4-Notch dynamics switch blood vessels from branching to expansion. eLife 5, e12167 (2016).Article

PubMed

PubMed Central

CAS

Google Scholar

Kryczek, I. et al. CXCL12 and vascular endothelial growth factor synergistically induce neoangiogenesis in human ovarian cancers. Cancer Res. 65, 465–472 (2005).CAS

PubMed

Google Scholar

Blanco, R. & Gerhardt, H. VEGF and Notch in tip and stalk cell selection. Cold Spring Harb. Perspect. Med. 3, a006569 (2013).Article

PubMed

PubMed Central

CAS

Google Scholar

Jakobsson, L. et al. Endothelial cells dynamically compete for the tip cell position during angiogenic sprouting. Nat. Cell Biol. 12, 943–953 (2010).Article

CAS

PubMed

Google Scholar

Andersson, A. et al. Single-cell and spatial transcriptomics enables probabilistic inference of cell type topography. Commun. Biol. 3, 565 (2020).Article

PubMed

PubMed Central

Google Scholar

Lakins, M. A., Ghorani, E., Munir, H., Martins, C. P. & Shields, J. D. Cancer-associated fibroblasts induce antigen-specific deletion of CD8+ T cells to protect tumour cells. Nat. Commun. 9, 948 (2018).Article

PubMed

PubMed Central

CAS

Google Scholar

Andersson, A. et al. Spatial deconvolution of HER2-positive breast tumors reveals novel intercellular relationships. Preprint at bioRxiv https://doi.org/10.1101/2020.07.14.200600 (2020).Newman, A. M. et al. Determining cell type abundance and expression from bulk tissues with digital cytometry. Nat. Biotechnol. 37, 773–782 (2019).Article

CAS

PubMed

PubMed Central

Google Scholar

Tsoucas, D. et al. Accurate estimation of cell-type composition from gene expression data. Nat. Commun. 10, 2975 (2019).Article

PubMed

PubMed Central

CAS

Google Scholar

Tsai, J. H., Donaher, J. L., Murphy, D. A., Chau, S. & Yang, J. Spatiotemporal regulation of epithelial-mesenchymal transition is essential for squamous cell carcinoma metastasis. Cancer Cell 22, 725–736 (2012).Article

CAS

PubMed

PubMed Central

Google Scholar

Molgora, M. et al. TREM2 modulation remodels the tumor myeloid landscape enhancing anti-PD-1 immunotherapy. Cell 182, 886–900.e17 (2020).Article

CAS

PubMed

PubMed Central

Google Scholar

Leruste, A. et al. Clonally expanded T cells reveal immunogenicity of rhabdoid tumors. Cancer Cell 36, 597–612.e8 (2019).Article

CAS

PubMed

Google Scholar

Dutertre, C. A. et al. Single-cell analysis of human mononuclear phagocytes reveals subset-defining markers and identifies circulating inflammatory dendritic cells. Immunity 51, 573–589.e8 (2019).Article

CAS

PubMed

Google Scholar

Wu, S. Z. et al. Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis. Genome Med. 13, 81 (2021).Article

CAS

PubMed

PubMed Central

Google Scholar

Lun, A. T. L. et al. EmptyDrops: distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data. Genome Biol. 20, 63 (2019).Article

PubMed

PubMed Central

Google Scholar

Zhao, X., Rødland, E. A., Tibshirani, R. & Plevritis, S. Molecular subtyping for clinically defined breast cancer subgroups. Breast Cancer Res. 17, 29 (2015).Article

CAS

PubMed

PubMed Central

Google Scholar

Patro, R., Duggal, G., Love, M. I., Irizarry, R. A. & Kingsford, C. Salmon provides fast and bias-aware quantification of transcript expression. Nat. Methods 14, 417–419 (2017).Article

CAS

PubMed

PubMed Central

Google Scholar

Finak, G. et al. MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data. Genome Biol. 16, 278 (2015).Article

PubMed

PubMed Central

CAS

Google Scholar

Aibar, S. et al. SCENIC: single-cell regulatory network inference and clustering. Nat. Methods 14, 1083–1086 (2017).Article

CAS

PubMed

PubMed Central

Google Scholar

Yu, G., Wang, L.-G., Han, Y. & He, Q.-Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 16, 284–287 (2012).Article

CAS

PubMed

PubMed Central

Google Scholar

CAS

PubMed

Google Scholar

Ramilowski, J. A. et al. A draft network of ligand–receptor-mediated multicellular signalling in human. Nat. Commun. 6, 7866 (2015).Article

CAS

PubMed

Google Scholar

Swarbrick, A., Wu, S., Al-Eryani, G., Roden, D. & Bartonicek, N. BrCa_cell_atlas. Version 1.0.0 (analysis code) https://doi.org/10.5281/zenodo.5031502 (2021).Download referencesAcknowledgementsThis work is supported by a research grant from the National Breast Cancer Foundation (NBCF) of Australia (no. IIRS-19-106) and supported by the generosity of J. McMurtrie, AM and D. McMurtrie, the Petre Foundation, White Butterfly Foundation, Sydney Breast Cancer Foundation, Skipper Jacobs Charitable Trust, G. P. Harris Foundation and The National Health and Medical Research Council (NHMRC). A.S. is the recipient of a Senior Research Fellowship from the NHMRC (no. APP1161216). S.Z.W., G.A.-E. and J.T. are supported by the Australian Government Research Training Program Scholarship. S.O.T. is supported by the NBCF (PRAC 16-006; no. IIRS-19-084), Sydney Breast Cancer Foundation and the Family and Friends of M. O’Sullivan. S.J. is supported by a research fellowship from the NBCF. X.S.L. is supported by the Breast Cancer Research Foundation (no. BCRF-19-100) and National Institutes of Health (no. R01CA234018). C.M.P. and A.T. were supported by the National Cancer Institute Breast SPORE program (no. P50-CA58223), grant no. RO1-CA148761, and Breast Cancer Research Foundation. This work was supported by the Australian Centre for Translational Breast Cancer Research, Walter and Eliza Hall Institute, with funding support from the NHMRC Centre for Research Excellence grant no. APP1153049. E.L. is supported as a National Breast Cancer Foundation Endowed Chair and by the Love Your Sister foundation. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We thank the following people for their assistance in the experimental part of this manuscript: J. Yang; G. Lehrbach from the Garvan Institute of Medical Research Tissue Culture Facility; A. Zaratzian from the Garvan Histopathology Facility for tissue processing and IHC staining and guidance on the Visium experiments; the Garvan–Weizmann Centre for Cellular Genomics, including E. Lam, H. Saeed and M. Armstrong for the expertise in flow sorting. We thank H. Holliday for the incredible illustration in Fig. 8g. We thank H. H. Milioli for providing guidance for analyzing the METABRIC cohort dataset. We thank I. Shapiro and C. Grant as consumer advocates. This manuscript was edited at Life Science Editors.Author informationAuthor notesThese authors contributed equally: Sunny Z. Wu, Ghamdan Al-Eryani, Daniel Lee Roden.Authors and AffiliationsThe Kinghorn Cancer Centre and Cancer Research Theme, Garvan Institute of Medical Research, Darlinghurst, New South Wales, AustraliaSunny Z. Wu, Ghamdan Al-Eryani, Daniel Lee Roden, Simon Junankar, Kate Harvey, James R. Torpy, Nenad Bartonicek, Taopeng Wang, Mun N. Hui, Sandra O’Toole, Elgene Lim & Alexander SwarbrickSt Vincent’s Clinical School, Faculty of Medicine, University of New South Wales, Sydney, New South Wales, AustraliaSunny Z. Wu, Ghamdan Al-Eryani, Daniel Lee Roden, Simon Junankar, James R. Torpy, Nenad Bartonicek, Taopeng Wang, Andrew Parker, Elgene Lim & Alexander SwarbrickScience for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Solna, SwedenAlma Andersson, Ludvig Larsson & Joakim LundebergLineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USAAatish Thennavan & Charles M. PerouDepartment of Data Science, Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Harvard T.H. Chan School of Public Health, Boston, MA, USAChenfei Wang & X. Shirley LiuGarvan-Weizmann Centre for Cellular Genomics, Garvan Institute of Medical Research, Sydney, New South Wales, AustraliaDominik Kaczorowski, Chia-Ling Chan, Vikkitharan Gnanasambandapillai & Joseph E. Powell10x Genomics, Pleasanton, CA, USANeil I. Weisenfeld, Cedric R. Uytingco, Jennifer G. Chew, Zachary W. Bent & Stephen R. WilliamsGustave Roussy Cancer Campus, Villejuif, FranceCharles-Antoine DutertreInstitut National de la Santé Et de la Recherche Médicale (INSERM) U1015, Equipe Labellisée—Ligue Nationale contre le Cancer, Villejuif, FranceCharles-Antoine DutertreThe Strathfield Breast Centre, Strathfield, New South Wales, AustraliaLaurence GluchChris O’Brien Lifehouse, Camperdown, New South Wales, AustraliaMun N. Hui & Jane BeithSt Vincent’s Hospital, Darlinghurst, New South Wales, AustraliaAndrew Parker, Davendra Segara & Elgene Lim Department of Tissue Pathology and Diagnostic Pathology, New South Wales Health Pathology, Royal Prince Alfred Hospital, Camperdown, New South Wales, AustraliaElizabeth Robbins & Sandra O’ToolePathology Queensland, Princess Alexandra Hospital, Brisbane, Queensland, AustraliaCaroline CooperSouthside Clinical Unit, Faculty of Medicine, University of Queensland, Brisbane, Queensland, AustraliaCaroline CooperDepartment of Breast Surgery, Chris O’Brien Lifehouse, Camperdown, New South Wales, AustraliaCindy Mak, Belinda Chan & Sanjay WarrierRoyal Prince Alfred Institute of Academic Surgery, University of Sydney, Sydney, New South Wales, AustraliaCindy Mak & Sanjay WarrierSingapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore, SingaporeFlorent GinhouxShanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaFlorent GinhouxTranslational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, SingaporeFlorent GinhouxNew South Wales Health Pathology, Department of Anatomical Pathology, St George Hospital, Kogarah, New South Wales, AustraliaEwan MillarSchool of Medical Sciences, University of New South Wales, Sydney, New South Wales, AustraliaEwan MillarFaculty of Medicine & Health Sciences, Western Sydney University, Campbelltown, New South Wales, AustraliaEwan Millar & Sandra O’TooleUniversity of New South Wales Cellular Genomics Futures Institute, University of New South Wales, Sydney, New South Wales, AustraliaJoseph E. PowellSydney Medical School, Sydney University, Sydney, New South Wales, AustraliaSandra O’TooleAuthorsSunny Z. WuView author publicationsYou can also search for this author in

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PubMed Google ScholarContributionsA.S. conceived the project and directed the study with input from all authors. E.L., S.W., M.N.H., B.C., C.C., C.M., D.S., E.R., A.P., J.B., S.O.T., E.M. and L.G. contributed to the experimental design, procured the patient tumor tissue and assisted with interpreting the data. S.Z.W., G.A.-E. and K.H. performed the single-cell captures. K.H. analyzed all the clinical information. S.Z.W., K.H. and G.A.-E. optimized and performed the tumor dissociation experiments. G.A.-E. optimized and performed the antibody staining for the CITE-seq experiments. N.B. and G.A.-E. performed the CITE-seq data processing. C.-L.C. and S.Z.W. performed the scRNA-seq experiments on the Chromium Controller. C.-L.C. helped perform the next-generation sequencing of the scRNA-seq libraries. S.Z.W. performed the preprocessing, data integration and reclustering steps for the scRNA-seq data. J.T. performed the analysis and benchmarking of inferCNV. A.T. and C.M.P. led the development of SCSubtype. D.R. interpreted and led the analyses for the breast cancer GM analyses. K.H. and T.W. performed the H&E and IHC experiments. S.O.T. independently assessed and scored all histology in this study. G.A.-E. interpreted and performed the analyses of the immune cells with intellectual input from S.J. C.-A.D. and F.G. provided intellectual input related to myeloid cluster annotation. S.Z.W. interpreted and performed all the analyses of stromal cells. D.K. and C.-L.C. performed the Visium experiments with input from J.E.P. V.G. helped perform preprocessing of the Visium datasets. S.R.W., N.I.W., C.R.U., J.G.C. and Z.W.B. performed the Visium experiments and data processing from an independent laboratory. A.A. performed the Stereoscope deconvolution with input from J.L. S.Z.W. performed the downstream analysis of the Visium data with guidance from A.A., L.L., G.A.-E. and J.L. D.R. interpreted and performed the CIBERSORTx analysis. S.Z.W. and D.R. performed the survival analyses. C.W. and X.S.L. provided intellectual input and guidance on bulk deconvolution and survival analyses. S.Z.W., A.S., D.R., G.A.-E. and S.J. wrote the manuscript with input from all authors.Corresponding authorCorrespondence to

Alexander Swarbrick.Ethics declarations

Competing interests

C.M.P. is an equity stockholder and consultant for BioClassifier; he is also listed as an inventor on patent applications for the Breast PAM50 Subtyping assay. J.L. is an author on patents owned by Spatial Transcriptomics AB covering technology presented in this paper. The other authors declare no competing interests.

Additional informationPeer review information Nature Genetics thanks Itai Yanai and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Extended dataExtended Data Fig. 1 Identification of malignant cells, single-cell RNA sequencing metrics and non-integrated data of stromal and immune cells.a-b, Number of unique molecular identifiers (a) and genes (b) per tumor analyzed by scRNA-Seq in this study. Tumors are stratified by the clinical subtypes TNBC (red), HER2 (pink) and ER (blue). Diamond points represent the mean. c-d, Number of unique molecular identifiers (UMIs;c) and genes (d) per major lineage cell types identified in this study. These major lineage tiers are grouped by T-cells, B-cells, Plasmablasts, Myeloid, Epithelial, Cycling, Mesenchymal (cancer-associated fibroblasts and perivascular-like cells) and Endothelial. Diamond points represent the mean. e-f, UMAP visualization of all 71,220 stromal and immune cells without batch correction and data integration. UMAP dimensional reduction was performed using 100 principal components in the Seurat v3 package. Cells are grouped by tumor (e) and major lineage tiers (f) as identified using the Garnett cell classification method. g, InferCNV heatmaps of all malignant cells grouped by clinical subtypes. Common subtype-specific CNVs and a chr6 artefact reported by Tirosh et. al. are marked (Tirosh et al., 2016b).Extended Data Fig. 2 Supplementary data for SCSubtype classifier.a-b, Hierarchical Clustering of Allcells-Pseudobulk (indicated by yellow stars) and Ribozero mRNA-Seq (indicated by blue stars) profiles of the patient samples with TCGA patient mRNA-Seq data. a, View of the basal cluster showing pairing of Allcells-Pseudobulk and Ribozero mRNA-Seq profiles of 2 representative tumors (CID4495 and CID4515) in the present study. b, View of the luminal cluster showing pairing of Allcells-Pseudobulk and Ribozero mRNA-Seq profiles of 4 representative tumors (CID4067, CID4463, CID4290 and CID3948) in the present study. c, Heatmap of SCSubtype gene sets across the training and test samples in each individual group. Colored outlined boxes highlighting the top expressed genes per group. d, Barplot representing proportions of SCSubtype calls in individual samples. Test dataset samples are highlighted within the golden colored outline. e, Scatterplot of individual cancer cells plotted according to the Proliferation score (x-axis) and Differentiation – DScore (y-axis). Individual cells are colored based on the SCSubtype calls. f, Scatterplot of individual TCGA breast tumors plotted according to the Proliferation score (x-axis) and Differentiation – DScore (y-axis). Individual patients are colored based on the PAM50 subtype calls.Extended Data Fig. 3 Supplementary data for breast cancer gene modules.a, Spherical k-means (skmeans) based consensus clustering of the Jaccard similarities between 574 signatures of neoplastic cell ITTH. This showed the probability (p1-p7) of each signature of ITTH being assigned to one of seven clusters/classes. Silhouette scores are shown for each signature. b, Heatmap of pair-wise Pearson correlations of the scaled AUCell signature scores, across all individual neoplastic cells, for each of the seven ITTH gene-modules (bolded) and a curated set of breast cancer related gene-signatures. Hierarchical clustering was performed using Pearson correlations and average linkage c, Heatmap showing the scaled AUCell signature scores of each of the seven ITTH gene-modules (rows) across all individual neoplastic cells (columns). Hierarchical clustering was done using Pearson correlations and average linkage. (HER2_AMP = Clinical HER2 amplification status). d, Distributions of signature scores (z-score scaled) for each of the gene-module signatures (24,489 cells from 21 tumors). Cells are grouped according to the gene-module (GM1-7) cell-state. e, Barchart showing the proportion of cells assigned to each of the gene-module cell-states (GM1-7) with cells grouped according to the SCSubtypes. f, Distributions of SCSubtype scores for each of the gene-module signatures (24,489 cells from 21 tumors). Cells are grouped according to the gene-module (GM1-7) cell-state. Kruskal-Wallis tests were performed to calculate the significance between the four SCSubtype score groups in each of the gene-module groups, p-value shown. Wilcox tests were used to identify which SCSubtype had significantly increased SCSubtype scores in the cells assigned to each gene-module, the scores of each SCSubtype were compared to the rest of the SCSubtype scores (****: Holm adjusted p-value < 0.0001, ns: Holm adjusted p-value > 0.05). Box plots in d and f depict the first and third quartiles as the lower and upper bounds, respectively. The whiskers represent 1.5x the interquartile range and the centre depicts the median.Extended Data Fig. 4 CITE-seq vignette.a, UMAP Visualization of a TNBC sample with 157 DNA barcoded antibodies (Supplementary Table 11). Cluster annotations were extracted from our final breast cancer atlas cell annotations. b, Heatmap visualization of the cluster averaged antibody derived tag (ADT) values for the 157 CITE-seq antibody panel. Only immune cells are shown. c-d, Expression featureplots of measured experimental ADT values (shown in top rows) against the CITE-seq imputation ADT levels (shown in bottom rows), as determined using the seurat v3 method. Selected markers for immunophenotyping T-cells (c; CD4, CD8A, PD-1 and CD103) and myeloid cells (d; PD-L1, CD86, CD49f and CD14) are shown.Extended Data Fig. 5 Supplementary data for T-cells and innate lymphoid cells.a, Dotplot visualizing averaged expression of canonical markers across T-cell and innate lymphoid clusters. b, Cytotoxic and dysfunctional gene signature scores across T-cell and innate lymphoid clusters. A Kruskal-Wallis test was performed to compare significance between (pairwise two-sided t-test for each cluster compared to the mean, p-values denoted by asterisks: *p < 0.05, **p < 0.01, ***p < 0.001 and ****p < 0.0001). Red line indicates the median expression. c, Dysfunctional gene signature scores of CD8 : LAG3 and CD8+ T : IFNG clusters across clinical subtypes (n = 26; 11 TNBC, 10 ER+ and 5 HER2+). A pairwise two-sided t-test for each cluster was performed to determine significance. P-values denoted by asterisks: *p < 0.05, **p < 0.01, ***p < 0.001 and ****p < 0.0001. d, Differentially expressed immune modulator genes, stratified by T-cell and Myeloid clusters, compared across breast cancer subtypes. A pairwise MAST comparison was performed to obtain bonferroni corrected p-values. All genes displayed are statistically significant (p-value < 0.05). e, Pairwise two-sided t-test comparison of LAG3, CD27, PD-1 (PDCD1) and CD70 log-normalised expression values in LAG3/c8 T-cells across breast cancer subtypes (n = 26; 11 TNBC, 10 ER+ and 5 HER2+). f, Enrichment of PDCD1, CD27, LAG3 and CD70 expression in the METABRIC cohort between clinical subtypes (n = 1,608; 209 Basal, 224 Her2, 700 LumA and 475 LumB). A pair-wise Wilcox test was performed to identify statistical significance. P‐values denoted by asterisks: *p < 0.05, **p < 0.01, ***p < 0.001 and ****p < 0.0001. Box plots in b and f depict the first and third quartiles as the lower and upper bounds, respectively. The whiskers represent 1.5x the interquartile range and the centre depicts the median.Extended Data Fig. 6 Gene expression of immune cell surface receptors across malignant, immune and mesenchymal clusters and breast cancer clinical subtypes.a, Averaged expression and clustering of 133 clinically targetable receptor or ligand immune modulator markers across all cell types grouped by clinical breast cancer subtypes (TNBC, HER2+ and ER+). Gene lists were manually curated through systematic literature search of known immune modulating proteins expressed on the surface of cells. Default parameters for hierarchical clustering were used via the ‘pheatmap’ package for the visualization of gene expression values.Extended Data Fig. 7 Supplementary data for B-cells, Plasmablasts and Myeloid cells.a, UMAP visualization of all reclustered B-cells (n = 3,202 cells) and Plasmablasts (n = 3,525 cells) as annotated using canonical gene expression markers. b, Featureplots of CD27, IGHD, IGKC and IGLC2 across naïve B cells, memory B cells, and Plasmablasts. c, Tumour associated macrophage (TAM) signature score obtained from Cassetta et al. 2019 and the expression of log-normalised levels of CCL8 across all myeloid clusters (9,675 cells from 26 tumors). A pairwise two-sided t-test was performed to determine statistical significance for clusters of interest. P-values denoted by asterisks: *p < 0.05, **p < 0.01, ***p < 0.001 and ****p < 0.0001. Dashed red line marks median TAM module score or gene expression. A Kruskal-Wallis test was performed to compare significance between groups’. d, LAM and DC : LAMP3 gene expression signatures acquired from Jaitin et al. 2019 and Zhang et al. 2019 respectively, visualized on the myeloid UMAP clusters. e, Heatmap visualizing GO enrichment pathways across myeloid clusters. f, Proportion of myeloid clusters across clinical subtypes. Statistical significance was determined using a two-sided t-test in a pairwise comparison of means between groups (n = 26; 11 TNBC, 10 ER+ and 5 HER2+). P‐values denoted by asterisks: *p < 0.05, **p < 0.01, ***p < 0.001 and ****p < 0.0001. g, Violin plots of imputed CITE-seq PD-L1 and PD-L2 expression values found on myeloid cells. Box plots in c and f depict the first and third quartiles as the lower and upper bounds, respectively. The whiskers represent 1.5x the interquartile range and the centre depicts the median.Extended Data Fig. 8 Supplementary data for mesenchymal cell states and subclusters.a, t-SNEvisualization CAFs, PVL cells and endothelial cells using Seurat reclustered with default resolution parameters (0.8). b, Pseudotime plot for CAFs, PVL cells and endothelial cells, as determined using monocle. Coordinates are as in main Figs. 5c, 5e and 5g. c, t-SNE visualizations for CAFs, PVL cells and endothelial cells with monocle derived cell states overlaid. d, Heatmaps for CAFs, PVL cells and endothelial cells show cell state averaged log normalised expression values for all differentially expressed genes determined using the MAST method, with select stromal markers highlighted. e, Top 10 gene ontologies (GO) of each mesenchymal cell state, as determined using pathway enrichment with ClusterProfiler with all differentially expressed genes as input. f, Stromal cell state averaged signature scores for pancreatic ductal adenocarcinoma myofibroblast-like, inflammatory-like and antigen-presenting CAF sub-populations, as determined using AUCell. g, Enrichment of antigen-presenting CAF markers CLU, CD74 and CAV1 in various stromal cell states. h, Subclusters of CAFs, PVL cells and endothelial cells determined using Seurat show a strong integration with three normal breast tissue datasets, highlighting similarities in subclusters across disease status and clinical subtypes of breast cancer. i, Cell states of CAFs, PVL cells and endothelial cells determined using monocle show a strong integration with three normal breast tissue datasets and breast cancer clinical subtypes.Extended Data Fig. 9 Supplementary data for spatial transcriptomics.a, H&E images for the remaining five breast tumors analysed using Visium (TNBC: CID4465, 1142243F and 1160920F; ER+: CID4535 and CID4290). Scale bars represent 500 μm. b, Histograms of cancer deconvolution values, as estimated using Stereoscope. Red line indicates the 10% cutoff used to select spots for scoring breast cancer gene-modules. Spots are colored by the pathology annotation. c, Box plots of gene module scores for all cancer filtered spots, as determined using AUCell, grouped by sample (TNBC=red; ER=blue). Statistical significance was determined using a two-sided t-test, with p-values adjusted using the Benjamini–Hochberg procedure. Box plots depict the first and third quartiles as the lower and upper bounds, respectively. The whiskers represent 1.5x the interquartile range and the centre depicts the median. P‐values denoted by asterisks: *p < 0.05, **p < 0.01, ***p < 0.001 and ****p < 0.0001. d, Clustered gene module correlations across all cancer filtered spots. Color scales represent Pearson correlation values and are scaled per GM (‘n.s’ denotes not significant; two-sided correlation coefficient, Benjamini–Hochberg adjusted p-value < 0.05). e, Heatmap of the deconvolution values for inflammatory-like CAFs, myofibroblast-like CAFs, Macrophage CXCL10/c9, LAM1 and LAM2 clusters. Spots (columns) are grouped by sample and pathology. Deconvolution abundances (rows) are scaled by cell type. f, Predicted signaling in tissue spots enriched for iCAFs and CD4/CD8+ T-cells. Spots filtered for CAF-ligands and T-cell receptors detected by scRNA-Seq. The mean interaction scores of cell-signaling pairs are defined as the product of the ligand and receptor expression. g, Plots of PD-1 (PDCD1; y axis) expression with PD-L1 (CD274; x axis) or PD-L2 (PDCD1LG2; x axis) expression in spots enriched for CD4/CD8+ T-cells and LAM2 cells, as determined by Stereoscope. Abundance of CD4/CD8 T-cells (combined as T_cell here) and LAM2 are overlaid on the expression plots.Extended Data Fig. 10 Supplementary figure for CIBERSORTx cell-type deconvolution.a, Bar and boxplot (inset) of the Pearson correlation for 45 cell-types between the actual cell-fractions captured by scRNA-Seq and the CIBERSORTx predicted fractions from pseudo-bulk expression profiles (*denotes significance p < 0.05, two-sided correlation coefficient). Inset box plot depicts the first and third quartiles as the lower and upper bounds, respectively. The whiskers represent 1.5x the interquartile range and the centre depicts the median. b, Barplot comparing the Pearson correlation for cell-types between the actual cell-fractions captured by scRNA-Seq and the CIBERSORTx (red) and DWLS (blue) predicted fractions from pseudo-bulk expression profiles (*denotes significance p < 0.05, two-sided correlation coefficient). c, Boxplot comparing the CIBERSORTx predicted SCSubtype and Cycling cell-fractions in each METABRIC tumor, stratified by PAM50 subtypes (n = 1,608; 209 Basal, 224 Her2, 700 LumA and 475 LumB). Box plots depicted as described in b. d, Heatmap of ecotypes formed from the common METABRIC tumors (columns) identified from combining ecotypes generated using CIBERSORTx with all 32 significantly correlated cell-types (rows), when using CIBERSORTx on pseudo-bulk samples. e-f, Relative proportion of the PAM50 subtypes (e) and major cell-types (f) in each ecotype, when combining CIBERSORTx consensus clustering results. g-h, Kaplan-Meier (KM) plot of all patients with common tumors in each of the ecotypes (g) and patients with tumors in ecotypes E4 and E7 (h), when combining CIBERSORTx consensus clustering results. p-values calculated using the log-rank test. i-j, Relative proportion of the PAM50 molecular subtypes (i) and major cell-types (j) of the common tumors from combining CIBERSORT and DWLS generated ecotypes. k, KM plot of the patients with tumors in ecotypes E4 and E7, formed from combining CIBERSORT and DWLS generated ecotypes. p-value calculated using the log-rank test. l, Relative proportion of the METABRIC integrative cluster annotations of the tumors in each ecotype, as determined using CIBERSORTx across all cell-types.Supplementary informationSupplementary InformationSupplementary Note, containing Methods and one figure.Reporting SummaryPeer Review InformationSupplementary TablesSupplementary TablesRights and permissionsReprints and permissionsAbout this articleCite this articleWu, S.Z., Al-Eryani, G., Roden, D.L. et al. A single-cell and spatially resolved atlas of human breast cancers.

Nat Genet 53, 1334–1347 (2021). https://doi.org/10.1038/s41588-021-00911-1Download citationReceived: 11 September 2020Accepted: 08 July 2021Published: 06 September 2021Issue Date: September 2021DOI: https://doi.org/10.1038/s41588-021-00911-1Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard

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tokenpocket钱包下载app苹果|breast

BREAST中文(简体)翻译：剑桥词典

A spatially resolved single-cell genomic atlas of the adult human breast | Nature

Breast cancer | Nature Reviews Disease Primers

Development of the Human Breast - PMC

Breast cancer - Symptoms and causes - Mayo Clinic

BREAST中文(繁體)翻譯：劍橋詞典

Anatomy of the Breast | Memorial Sloan Kettering Cancer Center

A single-cell and spatially resolved atlas of human breast cancers | Nature Genetics

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