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The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups
Open accessAbstract
The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (copy number variants and single nucleotide polymorphisms) and acquired somatic copy number aberrations (CNAs) were associated with expression in ~40% of genes, with the landscape dominated by cis- and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP and MAP2K4. Unsupervised analysis of paired DNA–RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, oestrogen-receptor-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the ‘CNA-devoid’ subgroup and a basal-specific chromosome 5 deletion-associated mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic CNAs on the transcriptome.
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“Currently, numerous research efforts are focused on utilizing genetic data and artificial intelligence algorithms to develop diagnostic models to enhance the clinical efficiency and accuracy of breast cancer diagnosis [109,110,111].”
From A Comprehensive Review on Synergy of Multi-Modal Data and AI Technologies in Medical Diagnosis (2024) · cites this paper as [111]
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“This framework was also employed for a landmark study which used genomic and transcriptomic data from 2,000 breast tumours and discovered novel subgroups amongst them (Curtis et al., 2012).”
From Using machine learning approaches for multi-omics data analysis: A review (2021) · cites this paper as Curtis et al., 2012
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Molecular portraits of human breast tumours
Perou, C., Sørlie, T., Eisen, M., van de Rijn, M., Jeffrey, S., Rees, C. A., Pollack, J., Ross, D., Johnsen, H., Akslen, L., et al. (2000) · Nature · doi:10.1038/35021093 · Cited by 16,551
Self-citationNishimura, R., Osako, T., Nishiyama, Y., Tashima, R., Nakano, M., Fujisue, M., Toyozumi, Y., & Arima, N. (2013) · Oncology · doi:10.1159/000353099 · Cited by 13,239
Sørlie, T., Perou, C. M., Tibshirani, R. J., Aas, T., Geisler, S. B., Johnsen, H., Hastie, T. J., Eisen, M. B., van de Rijn, M., Jeffrey, S. S., et al. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.191367098 · Cited by 11,506
Self-citationSupervised Risk Predictor of Breast Cancer Based on Intrinsic Subtypes
Parker, J. S., Mullins, M., Cheang, M. C. U., Leung, S. C. Y., Voduc, D. K., Vickery, T. L., Davies, S. R., Fauron, C. M. ‐., He, X., Hu, Z., et al. (2009) · Journal of Clinical Oncology · doi:10.1200/jco.2008.18.1370 · Cited by 4,818
Li, J., Yen, C., Liaw, D., Podsypanina, K., Bose, S., Wang, S. I., Puc, J., Miliaresis, C., Rodgers, L., McCombie, R., et al. (1997) · Science · doi:10.1126/science.275.5308.1943 · Cited by 4,785
Ki67 expression in breast cancer
Elkablawy, M. A., Albasri, A. M., Mohammed, R. A., Hussainy, A. S., Nouh, M. M., & Alhujaily, A. S. (2016) · Saudi Medical Journal · doi:10.15537/smj.2016.2.12285 · Cited by 4,382
Diagnosis of multiple cancer types by shrunken centroids of gene expression
Tibshirani, R. J., Hastie, T. J., Narasimhan, B., & Chu, G. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.082099299 · Cited by 2,931
Tumor-Infiltrating CD8+Lymphocytes Predict Clinical Outcome in Breast Cancer
Mahmoud, S., Paish, E. C., Powe, D. G., Macmillan, R. D., Grainge, M. J., Lee, A. H. S., Ellis, I. O., & Green, A. R. (2011) · Journal of Clinical Oncology · doi:10.1200/jco.2010.30.5037 · Cited by 1,411
Self-citationGenomic and transcriptional aberrations linked to breast cancer pathophysiologies
Chin, K., DeVries, S., Fridlyand, J., Spellman, P. T., Roydasgupta, R., Kuo, W.-L., Lapuk, A. V., Neve, R. M., Qian, Z., Ryder, T., et al. (2006) · Cancer Cell · doi:10.1016/j.ccr.2006.10.009 · Cited by 1,309
Frequent Mutations of Chromatin Remodeling Gene ARID1A in Ovarian Clear Cell Carcinoma
Jones, S., Wang, T., Shih, I., Mao, T., Nakayama, K., Roden, R. B. S., Glas, R., Slamon, D. J., Diaz, L. A., Vogelstein, B., et al. (2010) · Science · doi:10.1126/science.1196333 · Cited by 1,218
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Luminal B Breast Cancer: Molecular Characterization, Clinical Management, and Future Perspectives
Ades, F., Zardavas, D., Božović‐Spasojević, I., Pugliano, L., Fumagalli, D., de Azambuja, E., Viale, G., Sotiriou, C. P., & Piccart, M. J. (2014) · Journal of Clinical Oncology · doi:10.1200/jco.2013.54.1870 · Cited by 465
Functional Genomic Landscape of Human Breast Cancer Drivers, Vulnerabilities, and Resistance
Marcotte, R., Sayad, A., Brown, K. R., Sanchez-Garcia, F., Reimand, J., Haider, M., Virtanen, C., Bradner, J. E., Bader, G. D., Mills, G. B., et al. (2016) · Cell · doi:10.1016/j.cell.2015.11.062 · Cited by 446
Stromal cell diversity associated with immune evasion in human triple‐negative breast cancer
Wu, S. Z., Roden, D. L., Wang, C., Holliday, H., Harvey, K., Cazet, A., Murphy, K. J., Pereira, B., Al‐Eryani, G., Bartoniček, N., et al. (2020) · The EMBO Journal · doi:10.15252/embj.2019104063 · Cited by 454
Copy number signatures and mutational processes in ovarian carcinoma
Macintyre, G., Goranova, T., Silva, D. D., Ennis, D. P., Piskorz, A., Eldridge, M., Sie, D., Lewsley, L.-A., Hanif, A., Wilson, C. A., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0179-8 · Cited by 434
Self-citationBruna, A., Rueda, O. M., Greenwood, W., Batra, A. S., Callari, M., Batra, R. N., McNamara, K. L., Sandoval, J. L., Cassidy, J. W., Vidaković, A. T., et al. (2016) · Cell · doi:10.1016/j.cell.2016.08.041 · Cited by 442
Self-citationA metastasis map of human cancer cell lines
Jin, X., Demere, Z., Nair, K., Ali, A., Ferraro, G. B., Natoli, T. E., Deik, A., Petronio, L., Tang, A. A., Zhu, C., et al. (2020) · Nature · doi:10.1038/s41586-020-2969-2 · Cited by 436
Quantitative Image Analysis of Cellular Heterogeneity in Breast Tumors Complements Genomic Profiling
Yuan, Y., Failmezger, H., Rueda, O. M., Ali, H. R., Gräf, S., Chin, S.-F., Schwarz, R. F., Curtis, C., Dunning, M. J., Bardwell, H., et al. (2012) · Science Translational Medicine · doi:10.1126/scitranslmed.3004330 · Cited by 426
Self-citationThe evolving concept of cancer and metastasis stem cells
Baccelli, I., & Trumpp, A. (2012) · The Journal of Cell Biology · doi:10.1083/jcb.201202014 · Cited by 428
TP53 Mutations in Human Cancer: Database Reassessment and Prospects for the Next Decade
Leroy, B., Anderson, M., & Soussi, T. (2014) · Human Mutation · doi:10.1002/humu.22552 · Cited by 422
Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer
ABCTB Investigators, Milne, R. L., EMBRACE, Collaborators, G. S., HEBON, kConFab/AOCS Investigators, Collaborators, N., Kuchenbaecker, K. B., Michailidou, K., Beesley, J., et al. (2017) · Nature Genetics · doi:10.1038/ng.3785 · Cited by 415
Self-citationDynamics of breast-cancer relapse reveal late-recurring ER-positive genomic subgroups
Rueda, O. M., Sammut, S., Seoane, J. A., Chin, S., Caswell-Jin, J. L., Callari, M., Batra, R. N., Pereira, B., Bruna, A., Ali, H. R., et al. (2019) · Nature · doi:10.1038/s41586-019-1007-8 · Cited by 423
Self-citationHartman, Z. C., Poage, G. M., den Hollander, P., Tsimelzon, A. I., Hill, J. L., Panupinthu, N., Zhang, Y., Mazumdar, A., Hilsenbeck, S. G., Mills, G. B., et al. (2013) · Cancer Research · doi:10.1158/0008-5472.can-12-4524-t · Cited by 416
André, F., Bachelot, T., Commo, F., Campone, M., Arnedos, M., Dieras, V. C., Lacroix‐Triki, M., Lacroix, L., Cohen, P. A., Gentien, D., et al. (2014) · The Lancet Oncology · doi:10.1016/s1470-2045(13)70611-9 · Cited by 417
Cancer genetics and genomics of human FOX family genes
Katoh, M., Igarashi, M., Fukuda, H., Nakagama, H., & Katoh, M. (2012) · Cancer Letters · doi:10.1016/j.canlet.2012.09.017 · Cited by 401
Protein phosphatase 2A: a target for anticancer therapy
Perrotti, D., & Neviani, P. (2013) · The Lancet Oncology · doi:10.1016/s1470-2045(12)70558-2 · Cited by 400
Endogenous Purification Reveals GREB1 as a Key Estrogen Receptor Regulatory Factor
Mohammed, H., D’Santos, C., Serandour, A. A., Ali, H. R., Brown, G. D., Atkins, A., Rueda, O. M., Holmes, K. A., Theodorou, V., Robinson, J. L. L., et al. (2013) · Cell Reports · doi:10.1016/j.celrep.2013.01.010 · Cited by 400
Self-citationBreast Cancer: Multiple Subtypes within a Tumor?
Yeo, S. K., & Guan, J. (2017) · Trends in cancer · doi:10.1016/j.trecan.2017.09.001 · Cited by 413
Predicting outcomes in radiation oncology—multifactorial decision support systems
Lambin, P., van Stiphout, R. G. P. M., Starmans, M. H. W., Velazquez, E. R., Nalbantov, G. I., Aerts, H. J. W. L., Roelofs, E., van Elmpt, W., Boutros, P. C., Granone, P. M., et al. (2012) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2012.196 · Cited by 396
Triple-negative breast cancer: is there a treatment on the horizon?
Yao, H., He, G., Yan, S., Chen, C., Song, L., Rosol, T. J., & Deng, X. (2016) · Oncotarget · doi:10.18632/oncotarget.12284 · Cited by 394
The shaping and functional consequences of the microRNA landscape in breast cancer
Dvinge, H., Git, A., Gräf, S., Salmon‐Divon, M., Curtis, C. N., Sottoriva, A., Zhao, Y., Hirst, M., Armisen, J., Miska, E. A., et al. (2013) · Nature · doi:10.1038/nature12108 · Cited by 393
Self-citationSchmid, P., Abraham, J., Chan, S. Y. T., Wheatley, D. A., Brunt, A. M., Nemsadze, G., Baird, R. D., Park, Y. H., Hall, P. S., Perren, T. J., et al. (2019) · Journal of Clinical Oncology · doi:10.1200/jco.19.00368 · Cited by 391
Gendoo, D. M. A., Ratanasirigulchai, N., Schröder, M., Paré, L., Parker, J. S., Prat, A., & Haibe‐Kains, B. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv693 · Cited by 389
Artificial intelligence in oncology
Shimizu, H., & Nakayama, K. I. (2020) · Cancer Science · doi:10.1111/cas.14377 · Cited by 388
Menyhárt, O., & Győrffy, B. (2021) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2021.01.009 · Cited by 412
Barèche, Y., Venet, D., Ignatiadis, M., Aftimos, P. G., Piccart, M. J., Rothé, F., & Sotiriou, C. P. (2018) · Annals of Oncology · doi:10.1093/annonc/mdy024 · Cited by 386
The Osteogenic Niche Promotes Early-Stage Bone Colonization of Disseminated Breast Cancer Cells
Wang, H., Yu, C. R., Gao, X., Welte, T., Muscarella, A. M., Tian, L. H., Zhao, H., Zhao, Z., Du, S., Tao, J., et al. (2015) · Cancer Cell · doi:10.1016/j.ccell.2014.11.017 · Cited by 394
Effective breast cancer combination therapy targeting BACH1 and mitochondrial metabolism
Lee, J., Yesilkanal, A. E., Wynne, J. P., Frankenberger, C. A., Liu, J., Yan, J., Elbaz, M., Rabe, D. C., Rustandy, F. D., Tiwari, P., et al. (2019) · Nature · doi:10.1038/s41586-019-1005-x · Cited by 381
Invasive lobular carcinoma of the breast: morphology, biomarkers and ’omics
Reed, A. E. M., Kutasovic, J. R., Lakhani, S. R., & Simpson, P. T. (2015) · Breast Cancer Research · doi:10.1186/s13058-015-0519-x · Cited by 379
Cancer progression and the invisible phase of metastatic colonization
Klein, C. A. (2020) · Nature reviews. Cancer · doi:10.1038/s41568-020-00300-6 · Cited by 387
Profiling human breast epithelial cells using single cell RNA sequencing identifies cell diversity
Nguyen, Q., Pervolarakis, N., Blake, K., Ma, D., Davis, R. T., James, N., Phung, A. T., Willey, E., Kumar, R., Jabart, E., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-04334-1 · Cited by 388
Couch, F. J., Wang, X., McGuffog, L., Lee, A., Olswold, C., Kuchenbaecker, K. B., Soucy, P., Fredericksen, Z., Barrowdale, D., Dennis, J., et al. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003212 · Cited by 378
Targeting lysyl oxidase (LOX) overcomes chemotherapy resistance in triple negative breast cancer
Saatci, Ö., Kaymak, A., Raza, U., Ersan, P. G., Akbulut, Ö., Banister, C. E., Sikirzhytski, V., Tokat, Ü. M., Aykut, G., Ansari, S. A., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-16199-4 · Cited by 390
Polyamines in cancer: integrating organismal metabolism and antitumour immunity
Holbert, C. E., Cullen, M., Casero, R. A., & Stewart, T. M. (2022) · Nature reviews. Cancer · doi:10.1038/s41568-022-00473-2 · Cited by 378
Principles and methods of integrative genomic analyses in cancer
Kristensen, V. N., Lingjærde, O. C., Russnes, H. G., Vollan, H. K. M., Frigessi, A., & Børresen‐Dale, A. (2014) · Nature reviews. Cancer · doi:10.1038/nrc3721 · Cited by 376
Self-citationHereditary breast and ovarian cancer: new genes in confined pathways
Nielsen, F. C., van Overeem Hansen, T., & Sørensen, C. S. (2016) · Nature Reviews Cancer · doi:10.1038/nrc.2016.72 · Cited by 367
Risom, T., Glass, D. R., Averbukh, I., Liu, C. C., Baranski, A., Kagel, A., McCaffrey, E., Greenwald, N. F., Rivero‐Gutiérrez, B., Strand, S. H., et al. (2022) · Cell · doi:10.1016/j.cell.2021.12.023 · Cited by 373
Basal-like breast cancer: molecular profiles, clinical features and survival outcomes
Milioli, H. H., Tishchenko, I., Riveros, C., Berretta, R. E., & Moscato, P. (2017) · BMC Medical Genomics · doi:10.1186/s12920-017-0250-9 · Cited by 371
Hu, Z., Li, Z., Ma, Z., & Curtis, C. N. (2020) · Nature Genetics · doi:10.1038/s41588-020-0628-z · Cited by 364
Self-citationMitochondrial DNA drives abscopal responses to radiation that are inhibited by autophagy
Yamazaki, T., Kirchmair, A., Sato, A., Buqué, A., Rybstein, M., Petroni, G., Bloy, N., Finotello, F., Stafford, L., Navarro Manzano, E., et al. (2020) · Nature Immunology · doi:10.1038/s41590-020-0751-0 · Cited by 359
NR2F1 controls tumour cell dormancy via SOX9- and RARβ-driven quiescence programmes
Sosa, M. S., Parikh, F., Gaspar‐Maia, A., Estrada, Y. D., Bosch, A., Bragado, P., Ekpin, E., George, A. D., Zheng, Y., Lam, H., et al. (2015) · Nature Communications · doi:10.1038/ncomms7170 · Cited by 357
Breast cancer heterogeneity and its implication in personalized precision therapy
Guo, L., Kong, D., Liu, J., Zhan, L., Luo, L., Zheng, W., Zheng, Q., Chen, C., & Sun, S. (2023) · Experimental Hematology and Oncology · doi:10.1186/s40164-022-00363-1 · Cited by 370
Bao, Y., Wang, L., Shi, L., Yun, F., Liu, X., Chen, Y., Chen, C., Ren, Y., & Jia, Y. (2019) · Cellular & Molecular Biology Letters · doi:10.1186/s11658-019-0162-0 · Cited by 355
Reactivation of multipotency by oncogenic PIK3CA induces breast tumour heterogeneity
Keymeulen, A. V., Lee, M. Y., Ousset, M., Brohée, S., Rorive, S., Giraddi, R. R., Wuidart, A., Bouvencourt, G., Dubois, C., Salmon, I. J., et al. (2015) · Nature · doi:10.1038/nature14665 · Cited by 362
The Implications of Clonal Genome Evolution for Cancer Medicine
Aparicio, S. A. J. R., & Caldas, C. (2013) · New England Journal of Medicine · doi:10.1056/nejmra1204892 · Cited by 361
Self-citationHuman breast cancer metastases to the brain display GABAergic properties in the neural niche
Neman, J., Termini, J. S., Wilczynski, S. P., Vaidehi, N., Choy, C., Kowolik, C. M., Li, H., Hambrecht, A. C., Roberts, E., & Jandial, R. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1322098111 · Cited by 348
Maintaining Tumor Heterogeneity in Patient-Derived Tumor Xenografts
Cassidy, J. W., Caldas, C., & Bruna, A. (2015) · Cancer Research · doi:10.1158/0008-5472.can-15-0727 · Cited by 352
Self-citationFriedman, G., Levi-Galibov, O., David, E., Bornstein, C., Giladi, A., Dadiani, M., Mayo, A., Halperin, C., Pevsner‐Fischer, M., Lavon, H., et al. (2020) · Nature Cancer · doi:10.1038/s43018-020-0082-y · Cited by 355
Self-citationSpatial Heterogeneity in the Tumor Microenvironment
Yuan, Y. (2016) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a026583 · Cited by 342
Self-citationSun, D., Wang, M., & Li, A. (2019) · IEEE/ACM Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2018.2806438 · Cited by 338
Cancer Evolution: Mathematical Models and Computational Inference
Beerenwinkel, N., Schwarz, R. F., Gerstung, M., & Markowetz, F. M. (2014) · Systematic Biology · doi:10.1093/sysbio/syu081 · Cited by 352
Self-citationFrom mice to humans: developments in cancer immunoediting
Teng, M. W. L., Galon, J., Fridman, W.-H., & Smyth, M. J. (2015) · Journal of Clinical Investigation · doi:10.1172/jci80004 · Cited by 337
Kim, I. S., Gao, Y., Welte, T., Wang, H., Liu, J., Janghorban, M., Sheng, K., Niu, Y., Goldstein, A., Zhao, N., et al. (2019) · Nature Cell Biology · doi:10.1038/s41556-019-0373-7 · Cited by 340
PAM50 Breast Cancer Subtyping by RT-qPCR and Concordance with Standard Clinical Molecular Markers
Bastien, R. R. L., Rodríguez-Lescure, Á., Ebbert, M., Prat, A., Munárriz, B., Rowe, L. R., Miller, P. A., Ruíz‐Borrego, M., Anderson, D., Lyons, B. W., et al. (2012) · BMC Medical Genomics · doi:10.1186/1755-8794-5-44 · Cited by 338
Bierie, B., Pierce, S. E., Kröger, C., Stover, D. G., Pattabiraman, D. R., Thiru, P., Donaher, J. L., Reinhardt, F., Chaffer, C. L., Keckesova, Z., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1618298114 · Cited by 341
Proteomic maps of breast cancer subtypes
Tyanova, S., Albrechtsen, R., Kronqvist, P., Cox, J., Mann, M., & Geiger, T. (2016) · Nature Communications · doi:10.1038/ncomms10259 · Cited by 330
Gluz, O., Nitz, U. A., Christgen, M., Kates, R. E., Shak, S., Clemens, M., Kraemer, S., Aktas, B., Küemmel, S., Reimer, T., et al. (2016) · Journal of Clinical Oncology · doi:10.1200/jco.2015.63.5383 · Cited by 325
Britschgi, A., Bill, A., Brinkhaus, H., Rothwell, C., Clay, I., Duss, S., Rebhan, M., Raman, P., Guy, C. T., Wetzel, K., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1217072110 · Cited by 328
Choudhry, H., Albukhari, A., Morotti, M., Haider, S. A., Moralli, D., Smythies, J., Schödel, J., Green, C., Camps, C., Buffa, F. M., et al. (2014) · Oncogene · doi:10.1038/onc.2014.378 · Cited by 323
Marra, A., Trapani, D., Viale, G., Criscitiello, C., & Curigliano, G. (2020) · npj Breast Cancer · doi:10.1038/s41523-020-00197-2 · Cited by 332
A Three-Gene Model to Robustly Identify Breast Cancer Molecular Subtypes
Haibe‐Kains, B., Desmedt, C., Loi, S., Culhane, A. C., Bontempi, G., Quackenbush, J. F., & Sotiriou, C. P. (2012) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djr545 · Cited by 321
Ramchandani, D., Berisa, M., Tavarez, D. A., Li, Z., Miele, M. M., Bai, Y., Lee, S. B., Ban, Y., Dephoure, N., Hendrickson, R. C., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-27559-z · Cited by 317
All roads lead to PP 2A: exploiting the therapeutic potential of this phosphatase
Sangodkar, J., Farrington, C. C., McClinch, K., Galsky, M. D., Kastrinsky, D. B., & Narla, G. (2016) · The FEBS Journal · doi:10.1111/febs.13573 · Cited by 312
Ross‐Adams, H., Lamb, A. D. G., Dunning, M., Halim, S., Lindberg, J., Massie, C. E., Egevad, L., Russell, R. B., Ramos‐Montoya, A., Vowler, S. L., et al. (2015) · EBioMedicine · doi:10.1016/j.ebiom.2015.07.017 · Cited by 319
Self-citationLock, E. F., & Dunson, D. B. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt425 · Cited by 320
Whole-genome sequencing of triple-negative breast cancers in a population-based clinical study
Staaf, J., Glodzik, D., Bosch, A., Vallon-Christersson, J., Reuterswärd, C., Häkkinen, J., Degasperi, A., Amarante, T. D., Saal, L. H., Hegardt, C., et al. (2019) · Nature Medicine · doi:10.1038/s41591-019-0582-4 · Cited by 307
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Li, Q., Seo, J.-H., Stranger, B. E., McKenna, A., Pe’er, I., LaFramboise, T., Brown, M. A., Tyekucheva, S., & Freedman, M. L. (2013) · Cell · doi:10.1016/j.cell.2012.12.034 · Cited by 313
Xu, J., Yang, P., Xue, S., Sharma, B., Sanchez-Martin, M., Wang, F., Beaty, K. A., Dehan, E., & Parikh, B. (2019) · Human Genetics · doi:10.1007/s00439-019-01970-5 · Cited by 305
TP53 Mutation Spectrum in Breast Cancer Is Subtype Specific and Has Distinct Prognostic Relevance
Silwal‐Pandit, L., Vollan, H. K. M., Chin, S., Rueda, O. M., McKinney, S., Osako, T., Quigley, D. A., Kristensen, V. N., Aparicio, S. A. J. R., Børresen‐Dale, A., et al. (2014) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-13-2943 · Cited by 304
Self-citationImaging mass cytometry and multiplatform genomics define the phenogenomic landscape of breast cancer
Ali, H. R., Jackson, H. W., Zanotelli, V. R., Danenberg, E., Fischer, J. R., Bardwell, H. A., Provenzano, E., CRUK IMAXT Grand Challenge Team, Ali, H. R., Sa’d, M. A., et al. (2020) · Nature Cancer · doi:10.1038/s43018-020-0026-6 · Cited by 313
Self-citationGLUT1 inhibition blocks growth of RB1-positive triple negative breast cancer
Wu, Q., Ba-Alawi, W., Deblois, G., Cruickshank, J., Duan, S., Lima‐Fernandes, E., Haight, J., Tonekaboni, S. A. M., Fortier, A.-M., Kuasne, H., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18020-8 · Cited by 305
Ali, H. R., Glont, S.-E., Blows, F. M., Provenzano, E., Dawson, S., Liu, B., Hiller, L., Dunn, J., Poole, C. J., Bowden, S. J., et al. (2015) · Annals of Oncology · doi:10.1093/annonc/mdv192 · Cited by 306
Self-citationA new genome‐driven integrated classification of breast cancer and its implications
Dawson, S., Rueda, O. M., Aparicio, S. A. J. R., & Caldas, C. (2013) · The EMBO Journal · doi:10.1038/emboj.2013.19 · Cited by 314
Self-citationTimperi, E., Gueguen, P., Molgora, M., Magagna, I., Kieffer, Y., Lopez‐Lastra, S., Sirven, P., Baudrin, L. G., Baulande, S., Nicolas, A., et al. (2022) · Cancer Research · doi:10.1158/0008-5472.can-22-1427 · Cited by 323
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Bashashati, A., Haffari, G., Ding, J., Ha, G., Lui, K., Rosner, J., Huntsman, D. D., Caldas, C., Aparicio, S. A. J. R., & Shah, S. P. (2012) · Genome biology · doi:10.1186/gb-2012-13-12-r124 · Cited by 301
Self-citationvan Schooneveld, E., Wildiers, H. P. M. W., Vergote, I. B., Vermeulen, P. B., Dirix, L. Y., & Laere, S. V. (2015) · Breast Cancer Research · doi:10.1186/s13058-015-0526-y · Cited by 297
Natural Categories and Human Kinds
Khalidi, M. A. (2013) · Cambridge University Press eBooks · doi:10.1017/cbo9780511998553 · Cited by 302
Maller, O., Drain, A. P., Barrett, A. S., Borgquist, S., Ruffell, B., Zakharevich, I., Pham, T. T. M., Gruosso, T., Kuasne, H., Lakins, J. N., et al. (2020) · Nature Materials · doi:10.1038/s41563-020-00849-5 · Cited by 307
D'Amato, N. C., Rogers, T. J., Gordon, M. A., Greene, L. I., Cochrane, D. R., Spoelstra, N. S., Nemkov, T. G., D'Alessandro, A., Hansen, K. C., & Richer, J. K. (2015) · Cancer Research · doi:10.1158/0008-5472.can-15-2011 · Cited by 294
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Heo, Y. J., Hwa, C., Lee, G.-H., Park, J.-M., & An, J.-Y. (2021) · Molecules and Cells · doi:10.14348/molcells.2021.0042 · Cited by 294
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Romero-Cordoba, S. L., Salido-Guadarrama, I., Rebollar‐Vega, R., Bautista‐Piña, V., Domínguez-Reyes, C. A., Tenorio‐Torres, A., Villegas‐Carlos, F., Fernández-López, J. C., Uribe-Figueroa, L., Alfaro-Ruíz, L. A., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-22478-5 · Cited by 293
Targeted Therapies for Triple-Negative Breast Cancer: Combating a Stubborn Disease
Kalimutho, M., Parsons, K., Mittal, D., López, J. A., Srihari, S., & Khanna, K. K. (2015) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2015.08.009 · Cited by 298
Molecularly targeted cancer therapy: some lessons from the past decade
Huang, M., Shen, A., Ding, J., & Geng, M. (2013) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2013.11.004 · Cited by 296
Earl, H. M., Hiller, L., Vallier, A.-L., Loi, S., McAdam, K., Hughes‐Davies, L., Harnett, A., Ah-See, M.-L., Simcock, R., Rea, D. W., et al. (2019) · The Lancet · doi:10.1016/s0140-6736(19)30650-6 · Cited by 294
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Chen, H., Lundberg, S., & Lee, S. (2022) · Nature Communications · doi:10.1038/s41467-022-31384-3 · Cited by 303
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Walerych, D., Napoli, M., Collavin, L., & Sal, G. D. (2012) · Carcinogenesis · doi:10.1093/carcin/bgs232 · Cited by 301
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Daemen, A., Griffith, O. L., Heiser, L. M., Wang, N. J., Enache, O. M., Sanborn, Z., Pepin, F., Durinck, S., Korkola, J. E., Griffith, M., et al. (2013) · Genome biology · doi:10.1186/gb-2013-14-10-r110 · Cited by 291
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Vasan, N., Razavi, P., Johnson, J. L., Shao, H., Shah, H., Antoine, A., Ladewig, E., Gorelick, A. N., Lin, T.-Y., Toska, E., et al. (2019) · Science · doi:10.1126/science.aaw9032 · Cited by 296
Lehmann, B. D., Colaprico, A., Silva, T. C., Chen, J., An, H., Ban, Y. J., Huang, H., Wang, L. H.-C., James, J. L., Balko, J. M., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-26502-6 · Cited by 298
Patient-derived xenograft models of breast cancer and their predictive power
Whittle, J. R., Lewis, M. T., Lindeman, G. J., & Visvader, J. E. (2015) · Breast Cancer Research · doi:10.1186/s13058-015-0523-1 · Cited by 293
Breast Tumor Heterogeneity: Source of Fitness, Hurdle for Therapy
Koren, S., & Bentires‐Alj, M. (2015) · Molecular Cell · doi:10.1016/j.molcel.2015.10.031 · Cited by 289
Predicting Cancer-Specific Vulnerability via Data-Driven Detection of Synthetic Lethality
Jerby‐Arnon, L., Pfetzer, N., Waldman, Y. Y., McGarry, L., James, D. T., Shanks, E. J., Seashore-Ludlow, B. A., Weinstock, A., Geiger, T., Clemons, P. A., et al. (2014) · Cell · doi:10.1016/j.cell.2014.07.027 · Cited by 282
Lee, G., Lee, H. Y., Park, H., Schiebler, M. L., van Beek, E. J. R., Ohno, Y., Seo, J. B., & Leung, A. N. C. (2016) · European Journal of Radiology · doi:10.1016/j.ejrad.2016.09.005 · Cited by 281
Collagen prolyl 4-hydroxylase 1 is essential for HIF-1α stabilization and TNBC chemoresistance
Xiong, G., Stewart, R. L., Chen, J., Gao, T., Scott, T. L., Samayoa, L. M., O’Connor, K. L., Lane, A. N., & Xu, R. (2018) · Nature Communications · doi:10.1038/s41467-018-06893-9 · Cited by 283
Mechanism-based cancer therapy: resistance to therapy, therapy for resistance
Ramos, P. M., & Bentires‐Alj, M. (2014) · Oncogene · doi:10.1038/onc.2014.314 · Cited by 287
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Russnes, H. G., Lingjærde, O. C., Børresen‐Dale, A., & Caldas, C. (2017) · American Journal Of Pathology · doi:10.1016/j.ajpath.2017.04.022 · Cited by 277
Self-citationA Comprehensive Immunologic Portrait of Triple-Negative Breast Cancer
Liu, Z., Li, M., Jiang, Z., & Wang, X. (2018) · Translational Oncology · doi:10.1016/j.tranon.2018.01.011 · Cited by 275
Targeting BCL-2 with the BH3 Mimetic ABT-199 in Estrogen Receptor-Positive Breast Cancer
Vaillant, F., Mérino, D., Lee, L., Breslin, K. A., Pal, B., Ritchie, M. E., Smyth, G. K., Christie, M., Phillipson, L. J., Burns, C. J., et al. (2013) · Cancer Cell · doi:10.1016/j.ccr.2013.06.002 · Cited by 275
Molecular classification of breast cancer
Vuong, D., Simpson, P. T., Green, B., Cummings, M. C., & Lakhani, S. R. (2014) · Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin · doi:10.1007/s00428-014-1593-7 · Cited by 299
The genomic landscape of breast cancer and its interaction with host immunity
Luen, S. J., Virassamy, B., Savas, P. S., Salgado, R., & Loi, S. (2016) · The Breast · doi:10.1016/j.breast.2016.07.015 · Cited by 279
Metadata
- Authors
- METABRIC Group, Curtis, C., Shah, S. P., Chin, S.-F., Turashvili, G., Rueda, O. M., Dunning, M. J., Speed, D., Lynch, A. G., Samarajiwa, S., Yuan, Y., Gräf, S., Ha, G., Haffari, G., Bashashati, A., Russell, R., McKinney, S., Langerød, A., Green, A., Provenzano, E., Wishart, G., Pinder, S., Watson, P., Markowetz, F., Murphy, L., Ellis, I., Purushotham, A., Børresen-Dale, A.-L., Brenton, J. D., Tavaré, S., Caldas, C., & Aparicio, S.
- Affiliations
- University of Cambridge (GB)
- University of British Columbia (CA)
- Oslo University Hospital (NO)
- University of Nottingham (GB)
- Cambridge University Hospitals NHS Foundation Trust (GB)
- King's College London (GB)
- University of Southern California (US)
- Corresponding author
- Caldas, Carlos
- Aparicio, Samuel
- ORCID
- Curtis, Christina
- Shah, Sohrab P.
- Chin, Suet-Feung
- Turashvili, Gulisa
- Rueda, Oscar M.
- Dunning, Mark J.
- Speed, Doug
- Lynch, Andy G.
- Samarajiwa, Shamith
- Yuan, Yinyin
- Gräf, Stefan
- Ha, Gavin
- Haffari, Gholamreza
- Bashashati, Ali
- Green, Andrew
- Provenzano, Elena
- Wishart, Gordon
- Pinder, Sarah
- Watson, Peter
- Markowetz, Florian
- Murphy, Leigh
- Ellis, Ian
- Purushotham, Arnie
- Brenton, James D.
- Tavaré, Simon
- Caldas, Carlos
- Aparicio, Samuel
- Venue
- Nature
- Published
- 2012-04-18
- Volume
- 486
- Issue
- 7403
- Pages
- 346-352
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3440846
- OpenAlex
- W2005895632
- Cited by
- 6,097
- References
- 32
- Citations by year
- 2026: 341 · 2025: 411 · 2024: 458 · 2023: 497 · 2022: 496 · 2021: 615 · 2020: 533 · 2019: 449 · 2018: 426 · 2017: 361 · 2016: 373 · 2015: 378 · 2014: 339 · 2013: 291 · 2012: 119
- FWCI
- 119.67
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Minerva Access (University of Melbourne) (submittedVersion)
- Research Portal (King's College London) (submittedVersion)
- Apollo (University of Cambridge) (submittedVersion)
- Apollo
- Funders
- University of Southern California
- Michael Smith Health Research BC
- Cancer Research UK (A7199, 15601, 19556)
- National Institute for Health and Care Research (ACF-2012-14-006, NF-SI-0611-10154)
- University of Cambridge
- King's College London
- National Institutes of Health
- BC Cancer Agency
- NIHR Cambridge Biomedical Research Centre
- National Human Genome Research Institute (P50-HG02790, P50HG002790)
- Division of Mathematical Sciences
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
- Keywords
- breast cancer, copy number alterations, somatic copy number alterations, gene expression, single nucleotide polymorphisms, PPP2R2A, MTAP, MAP2K4, estrogen receptor-positive breast cancer, adaptive immune response, basal-like breast cancer, chromosome 5 deletion, molecular stratification, prognosis
- MeSH terms
- Breast Neoplasms, Female, Humans, Prognosis, Genome, Human, Gene Expression Regulation, Neoplastic, Treatment Outcome, Polymorphism, Single Nucleotide, Gene Expression Profiling, Genomics, MAP Kinase Kinase 4, Genes, Neoplasm, Kaplan-Meier Estimate, Gene Regulatory Networks, Protein Phosphatase 2, DNA Copy Number Variations
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