Clinical management of breast cancer heterogeneity

Nature Reviews Clinical Oncology

Volumn 12, Issue 7, 2015, Pages 381-394

  Zardavas, Dimitrios ^a   Irrthum, Alexandre ^a   Swanton, Charles ^b   Piccart, Martine ^a  

^a JULES BORDET INSTITUTE   (Belgium)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BORTEZOMIB; DOXORUBICIN; MITOGEN ACTIVATED PROTEIN KINASE INHIBITOR; PROTEIN TYROSINE KINASE INHIBITOR;

ANTINEOPLASTIC ACTIVITY; BREAST CANCER; CANCER CELL; CANCER CLASSIFICATION; CANCER COMBINATION CHEMOTHERAPY; CANCER GRADING; CANCER PROGNOSIS; CANCER RESISTANCE; CANCER STEM CELL; CELL PROLIFERATION; CLINICAL TRIAL (TOPIC); COMPARATIVE GENOMIC HYBRIDIZATION; DNA METHYLATION; DRUG EFFICACY; DRUG MECHANISM; DRUG RESPONSE; ESR1 GENE; GATA3 GENE; GENE AMPLIFICATION; GENE EXPRESSION; GENE FUSION; GENETIC HETEROGENEITY; HUMAN; IMMUNE RESPONSE; JAK2 GENE; MCL1 GENE; NONHUMAN; ONCOGENE; ONCOGENE NEU; PHARMACOLOGICAL BLOCKING; PIK3CA GENE; PRIORITY JOURNAL; REVIEW; SOMATIC MUTATION; TP53 GENE; TRIPLE NEGATIVE BREAST CANCER; TUMOR MICROENVIRONMENT; BIOLOGICAL MODEL; BREAST NEOPLASMS; DISEASE COURSE; FEMALE; GENE EXPRESSION PROFILING; GENETICS; PATHOLOGY; PROCEDURES;

BREAST NEOPLASMS; DISEASE PROGRESSION; FEMALE; GENE EXPRESSION PROFILING; GENETIC HETEROGENEITY; HUMANS; MODELS, BIOLOGICAL; NEOPLASTIC STEM CELLS; TUMOR MICROENVIRONMENT;

EID: 84933278862     PISSN: 17594774     EISSN: 17594782     Source Type: Journal    
DOI: 10.1038/nrclinonc.2015.73     Document Type: Review

References (171)

1. Bloom H. J. & Richardson W. W. Histological grading and prognosis in breast cancer; a study of 1409 cases of which 359 have been followed for 15 years. Br. J. Cancer 11, 359-377 (1957
2. Frierson H. F. Grade and flow cytometric analysis of ploidy for infiltrating ductal carcinomas. Hum. Pathol. 24, 24-29 (1993
3. Genestie C., et al. Comparison of the prognostic value of Scarff-Bloom-Richardson and Nottingham histological grades in a series of 825 cases of breast cancer: major importance of the mitotic count as a component of both grading systems. Anticancer Res. 18, 571-576 (1998
4. Sotiriou C. & Pusztai L. Gene-expression signatures in breast cancer. N. Engl. J. Med. 360, 790-800 (2009
5. Russnes H. G., Navin N., Hicks J. & Borresen Dale A. L. Insight into the heterogeneity of breast cancer through next-generation sequencing. J. Clin. Invest. 121, 3810-3818 (2011
6. Desmedt C., Voet T., Sotiriou C. & Campbell P. J. Next-generation sequencing in breast cancer: first take home messages. Curr. Opin. Oncol. 24, 597-604 (2012
7. Bedard P. L., Hansen A. R., Ratain M. J. & Siu L. L. Tumour heterogeneity in the clinic. Nature 501, 355-364 (2013
8. Burrell R. A., McGranahan N., Bartek J. & Swanton C. The causes and consequences of genetic heterogeneity in cancer evolution. Nature 501, 338-345 (2013
9. Yap T. A., Gerlinger M., Futreal P. A., Pusztai L. & Swanton C. Intratumour heterogeneity: seeing the wood for the trees. Sci. Transl. Med. 4, 127ps10 (2012
10. Campbell P. J., et al. The patterns and dynamics of genomic instability in metastatic pancreatic cancer. Nature 467, 1109-1113 (2010
11. Gerlinger M., et al. Intratumour heterogeneity and branched evolution revealed by multiregion sequencing. N. Engl. J. Med. 366, 883-892 (2012
12. Hammond M. E. H., et al. American Society of Clinical Oncology/College Of American Pathologists guideline recommendations for immunohistochemical testing of oestrogen and progesterone receptors in breast cancer. J. Clin. Oncol. 28, 2784-2795 (2010
13. 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
14. Curtit E., et al. Discordances in oestrogen receptor status, progesterone receptor status, and HER2 status between primary breast cancer and metastasis. Oncologist 18, 667-674 (2013
15. Khasraw M., Brogi E. & Seidman A. D. The need to examine metastatic tissue at the time of progression of breast cancer: is re biopsy a necessity or a luxury?. Curr. Oncol. Rep. 13, 17-25 (2011
16. Pusztai L., Viale G., Kelly C. M. & Hudis C. A. Oestrogen and HER 2 receptor discordance between primary breast cancer and metastasis. Oncologist 15, 1164-1168 (2010
17. Ribelles N., Santonja A., Pajares B., Llácer C. & Alba E. The seed and soil hypothesis revisited: current state of knowledge of inherited genes on prognosis in breast cancer. Cancer Treat. Rev. 40, 293-299 (2014
18. Ma X. J., Dahiya S., Richardson E., Erlander M. & Sgroi D. C. Gene expression profiling of the tumour microenvironment during breast cancer progression. Breast Cancer Res. 11, R7 (2009
19. Qiu W., et al. No evidence of clonal somatic genetic alterations in cancer-associated fibroblasts from human breast and ovarian carcinomas. Nat. Genet. 40, 650-655 (2008
20. Zardavas D., Baselga J. & Piccart M. Emerging targeted agents in metastatic breast cancer. Nat. Rev. Clin. Oncol. 10, 191-210 (2013
21. Zardavas D., Pugliano L. & Piccart M. Personalized therapy for breast cancer: a dream or a reality?. Future Oncol. 9, 1105-1119 (2013
22. Gillies R. J., Flowers C. I., Drukteinis J. S. & Gatenby R. A. A unifying theory of carcinogenesis, and why targeted therapy doesn't work. Eur. J. Radiol. 81 (Suppl. 1), S48-S50 (2012
23. Tan P. H. & Ellis I. O. Myoepithelial and epithelial-myoepithelial, mesenchymal and fibroepithelial breast lesions: updates from the WHO Classification of Tumours of the Breast 2012. J. Clin. Pathol. 66, 465-470 (2013
24. Li C. I., Uribe D. J. & Daling J. R. Clinical characteristics of different histologic types of breast cancer. Br. J. Cancer 93, 1046-1052 (2005
25. Huober J., et al. Prognosis of medullary breast cancer: analysis of 13 International Breast Cancer Study Group (IBCSG) trials. Ann. Oncol. 23, 2843-2851 (2012
26. Cooper C. L., et al. Molecular alterations in metaplastic breast carcinoma. J. Clin. Pathol. 66, 522-528 (2013
27. Nelson R. A., Guye M. L., Luu T. & Lai L. L. Survival outcomes of metaplastic breast cancer patients: results from a US population-based analysis. Ann. Surg. Oncol. 22, 24-31 (2015
28. Perou C. M., et al. Molecular portraits of human breast tumours. Nature 406, 747-752 (2000
29. Sorlie T., et al. Repeated observation of breast tumour subtypes in independent gene expression data sets. Proc. Natl Acad. Sci. USA 100, 8418-8423 (2003
30. Sørlie T., et al. Gene expression patterns of breast carcinomas distinguish tumour subclasses with clinical implications. Proc. Natl Acad. Sci. USA 98, 10869-10874 (2001
31. Sotiriou C., et al. Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc. Natl Acad. Sci. USA 100, 10393-10398 (2003
32. Ades F., et al. Luminal B breast cancer: molecular characterization, clinical management, and future perspectives. J. Clin. Oncol. 32, 2794-2803 (2014
33. Herschkowitz J. I., et al. Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumours. Genome Biol. 8, R76 (2007
34. Prat A., et al. Phenotypic and molecular characterization of the claudin-low intrinsic subtype of breast cancer. Breast Cancer Res. 12, R68 (2010
35. Farmer P., et al. Identification of molecular apocrine breast tumours by microarray analysis. Oncogene 24, 4660-4671 (2005
36. Lehmann B. D., et al. Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J. Clin. Invest. 121, 2750-2767 (2011
37. Curtis C., et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 486, 346-352 (2012
38. Walerych D., Napoli M., Collavin L. & Del Sal G. The rebel angel: mutant p53 as the driving oncogene in breast cancer. Carcinogenesis 33, 2007-2017 (2012
39. Zardavas D., Phillips W. A. & Loi S. PIK3CA mutations in breast cancer: reconciling findings from preclinical and clinical data. Breast Cancer Res. 16, 201 (2014
40. Usary J., et al. Mutation of GATA3 in human breast tumours. Oncogene 23, 7669-7678 (2004
41. Stephens P. J., et al. The landscape of cancer genes and mutational processes in breast cancer. Nature 486, 400-404 (2012
42. Banerji S., et al. Sequence analysis of mutations and translocations across breast cancer subtypes. Nature 486, 405-409 (2012
43. Koboldt D. C., et al. Comprehensive molecular portraits of human breast tumours. Nature 490, 61-70 (2012
44. Geyer F. C., et al. Molecular analysis reveals a genetic basis for the phenotypic diversity of metaplastic breast carcinomas. J. Pathol. 220, 562-573 (2010
45. Patani N., et al. Direct evidence for concurrent morphological and genetic heterogeneity in an invasive ductal carcinoma of triple-negative phenotype. J. Clin. Pathol. 64, 822-828 (2011
46. Navin N., et al. Inferring tumour progression from genomic heterogeneity. Genome Res. 20, 68-80 (2010
47. Yates L. R. & Campbell P. J. Evolution of the cancer genome. Nat. Rev. Genet. 13, 795-806 (2012
48. Nik-Zainal S., et al. Mutational processes molding the genomes of 21 breast cancers. Cell 149, 979-993 (2012
49. Nik-Zainal S., et al. The life history of 21 breast cancers. Cell 149, 994-1007 (2012
50. Gerlinger M. & Swanton C. How Darwinian models inform therapeutic failure initiated by clonal heterogeneity in cancer medicine. Br. J. Cancer 103, 1139-1143 (2010
51. Balko J. M., et al. Molecular profiling of the residual disease of triple-negative breast cancers after neoadjuvant chemotherapy identifies actionable therapeutic targets. Cancer Discov. 4, 232-245 (2014
52. Zardavas D., et al. The AURORA initiative for metastatic breast cancer. Br. J. Cancer 111, 18881-18887 (2014
53. Burstein H. J., Polyak K., Wong J. S., Lester S. C. & Kaelin C. M. Ductal carcinoma in situ of the breast. N. Engl. J. Med. 350, 1430-1441 (2004
54. Simpson P. T., Reis-Filho J. S., Gale T. & Lakhani S. R. Molecular evolution of breast cancer. J. Pathol. 205, 248-254 (2005
55. Miron A., et al. PIK3CA mutations in in situ and invasive breast carcinomas. Cancer Res. 70, 5674-5678 (2010
56. Kalinsky K., Heguy A., Bhanot U. K., Patil S. & Moynahan M. E. PIK3CA mutations rarely demonstrate genotypic intratumoral heterogeneity and are selected for in breast cancer progression. Breast Cancer Res. Treat. 129, 635-643 (2011
57. Heselmeyer-Haddad K., et al. Single-cell genetic analysis of ductal carcinoma in situ and invasive breast cancer reveals enormous tumour heterogeneity yet conserved genomic imbalances and gain of MYC during progression. Am. J. Pathol. 181, 1807-1822 (2012
58. Hernandez L., et al. Genomic and mutational profiling of ductal carcinomas in situ and matched adjacent invasive breast cancers reveals intra-tumour genetic heterogeneity and clonal selection. J. Pathol. 227, 42-52 (2012
59. Kuukasjärvi T., et al. Genetic heterogeneity and clonal evolution underlying development of asynchronous metastasis in human breast cancer. Cancer Res. 57, 1597-1604 (1997
60. Shah S. P., et al. Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution. Nature 461, 809-813 (2009
61. Ding L., et al. Genome remodelling in a basal-like breast cancer metastasis and xenograft. Nature 464, 999-1005 (2010
62. Desmedt C., et al. Unraveling breast cancer progression through geographical and temporal sequencing [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, a986
63. Navin N., et al. Tumour evolution inferred by single-cell sequencing. Nature 472, 90-94 (2011
64. Wang Y., et al. Clonal evolution in breast cancer revealed by single nucleus genome sequencing. Nature 512, 155-160 (2014
65. Schmitt M. W., et al. Detection of ultra-rare mutations by next-generation sequencing. Proc. Natl Acad. Sci. USA 109, 14508-14513 (2012
66. Fox E. J. & Loeb L. A. Cancer: One cell at a time. Nature 512, 143-144 (2014
67. Polyak K. Breast cancer: origins and evolution. J. Clin. Invest. 117, 3155-3163 (2007
68. Meacham C. E. & Morrison S. J. Tumour heterogeneity and cancer cell plasticity. Nature 501, 328-337 (2013
69. Chaffer C. L., et al. Normal and neoplastic nonstem cells can spontaneously convert to a stem-like state. Proc. Natl Acad. Sci. USA 108, 7950-7955 (2011
70. Gupta P. B., et al. Stochastic state transitions give rise to phenotypic equilibrium in populations of cancer cells. Cell 146, 633-644 (2011
71. Nowell P. The clonal evolution of tumour cell populations. Science 194, 23-28 (1976
72. Sun X., et al. IL 6 secreted by cancer-associated fibroblasts induces tamoxifen resistance in luminal breast cancer. Oncogene http://dx.doi.org/10.1038/onc.2014.158 (2014
73. Junttila M. R. & De Sauvage F. J. Influence of tumour micro-environment heterogeneity on therapeutic response. Nature 501, 346-354 (2013
74. Bissell M. J., Hall H. G. & Parry G. How does the extracellular matrix direct gene expression?. J. Theor. Biol. 99, 31-68 (1982
75. Swanton C., Burrell R. A. & Futreal P. A. Breast cancer genome heterogeneity: a challenge to personalised medicine?. Breast Cancer Res. 13, 104 (2011
76. Turke A. B., et al. Preexistence and clonal selection of MET amplification in EGFR mutant NSCLC. Cancer Cell 17, 77-88 (2010
77. Sequist L. V., et al. Genotypic and histological evolution of lung cancers acquiring resistance to EGFR inhibitors. Sci. Transl. Med. 3, 75ra26 (2011
78. Su K. Y., et al. Pretreatment epidermal growth factor receptor (EGFR) T790M mutation predicts shorter EGFR tyrosine kinase inhibitor response duration in patients with non small cell lung cancer. J. Clin. Oncol. 30, 433-440 (2012
79. Choi Y. L., et al. EML4-ALK mutations in lung cancer that confer resistance to ALK inhibitors. N. Engl. J. Med. 363, 1734-1739 (2010
80. Katayama R., et al. Mechanisms of acquired crizotinib resistance in ALK-rearranged lung Cancers. Sci. Transl. Med. 4, 120ra17 (2012
81. Goldie J. H. & Coldman A. J. A mathematic model for relating the drug sensitivity of tumours to their spontaneous mutation rate. Cancer Treat. Rep. 63, 1727-1733 (1979
82. Goldie J. H., Coldman A. J. & Gudauskas G. A. Rationale for the use of alternating non cross resistant chemotherapy. Cancer Treat. Rep. 66, 439-449 (1982
83. Kao K. C. & Sherlock G. Molecular characterization of clonal interference during adaptive evolution in asexual populations of Saccharomyces cerevisiae. Nat. Genet. 40, 1499-1504 (2008
84. Lang G. I., et al. Pervasive genetic hitchhiking and clonal interference in forty evolving yeast populations. Nature 500, 571-574 (2013
85. Weller M., et al. EANO guideline for the diagnosis and treatment of anaplastic gliomas and glioblastoma. Lancet Oncol. 15, e395-e403 (2014
86. Szerlip N. J., et al. Intratumoral heterogeneity of receptor tyrosine kinases EGFR and PDGFRA amplification in glioblastoma defines subpopulations with distinct growth factor response. Proc. Natl Acad. Sci. USA 109, 3041-3046 (2012
87. Duncan J. S., et al. Dynamic reprogramming of the kinome in response to targeted MEK inhibition in triple-negative breast cancer. Cell 149, 307-321 (2012
88. De Mattos-Arruda L., et al. Circulating tumour cells and cell-free DNA as tools for managing breast cancer. Nat. Rev. Clin. Oncol. 10, 377-389 (2013
89. Klempner S. J., Myers A. P. & Cantley L. C. What a tangled web we weave: emerging resistance mechanisms to inhibition of the phosphoinositide 3 kinase pathway. Cancer Discov. 3, 1345-1354 (2013
90. Mirzoeva O. K., et al. Basal subtype and MAPK/ERK kinase (MEK)-phosphoinositide 3 kinase feedback signalling determine susceptibility of breast cancer cells to MEK inhibition. Cancer Res. 69, 565-572 (2009
91. Hoeflich K. P., et al. In vivo antitumour activity of MEK and phosphatidylinositol 3 kinase inhibitors in basal-like breast cancer models. Clin. Cancer Res. 15, 4649-4664 (2009
92. Saini K. S., et al. Targeting the PI3K/AKT/mTOR and Raf/MEK/ERK pathways in the treatment of breast cancer. Cancer Treat. Rev. 39, 935-946 (2013
93. Zhao B., Pritchard J. R., Lauffenburger D. A. & Haemann M. T. Addressing genetic tumour heterogeneity through computationally predictive combination therapy. Cancer Discov. 4, 166-174 (2014
94. Zhao B., Haemann M. T. & Lauffenburger D. A. Intratumour heterogeneity alters most effective drugs in designed combinations. Proc. Natl Acad. Sci. USA 111, 10773-10778 (2014
95. Carter S. L., et al. Absolute quantification of somatic DNA alterations in human cancer. Nat. Biotechnol. 30, 413-421 (2012
96. Amir E., et al. Oncogenic targets, magnitude of benefit, and market pricing of antineoplastic drugs. J. Clin. Oncol. 29, 2543-2549 (2011
97. Tirelli U., Berretta M., Bearz A. & Carbone A. Grouping of molecularly targeted anti-cancer agents based on cost-effectiveness analysis. Eur. Rev. Med. Pharmacol. Sci. 15, 1355-1356 (2011
98. Futreal P. A., et al. A census of human cancer genes. Nat. Rev. Cancer 4, 177-183 (2004
99. Andersen M. H., Schrama D., Thor Straten P. & Becker J. C. Cytotoxic T cells. J. Invest. Dermatol. 126, 32-41 (2006
100. Geiler-Samerotte K. A., et al. Misfolded proteins impose a dosage-dependent fitness cost and trigger a cytosolic unfolded protein response in yeast. Proc. Natl Acad. Sci. USA 108, 680-685 (2011
101. Neznanov N., Komarov A. P., Neznanova L., Stanhope-Baker P. & Gudkov A. V. Proteotoxic stress targeted therapy (PSTT): induction of protein misfolding enhances the antitumour effect of the proteasome inhibitor bortezomib. Oncotarget 2, 209-221 (2011
102. McFarland C. D., Korolev K. S., Kryukov G. V., Sunyaev S. R. & Mirny L. A. Impact of deleterious passenger mutations on cancer progression. Proc. Natl Acad. Sci. USA 110, 2910-2915 (2013
103. Lynch M., Bürger R., Butcher D. & Gabriel W. The mutational meltdown in asexual populations. J. Hered. 84, 339-344 (1993
104. Birkbak N. J., et al. Paradoxical relationship between chromosomal instability and survival outcome in cancer. Cancer Res. 71, 3447-3452 (2011
105. Roylance R., et al. Relationship of extreme chromosomal instability with long-term survival in a retrospective analysis of primary breast cancer. Cancer Epidemiol. Biomark. 20, 2183-2194 (2011
106. Sheltzer J. M., et al. Aneuploidy drives genomic instability in yeast. Science 333, 1026-1030 (2011
107. De Raedt T., et al. Exploiting cancer cell vulnerabilities to develop a combination therapy for RAS-driven tumours. Cancer Cell 20, 400-413 (2011
108. Palumbo A. & Anderson K. Multiple myeloma. N. Engl. J. Med. 364, 1046-1060 (2011
109. Dai C., Whitesell L., Rogers A. B. & Lindquist S. Heat shock factor 1 is a powerful multifaceted modifier of carcinogenesis. Cell 130, 1005-1018 (2007
110. Irvin W. J., et al. Phase II study of bortezomib and pegylated liposomal doxorubicin in the treatment of metastatic breast cancer. Clin. Breast Cancer 10, 465-470 (2010
111. Trinh X. B., et al. A phase II study of the combination of endocrine treatment and bortezomib in patients with endocrine-resistant metastatic breast cancer. Oncol. Rep. 27, 657-663 (2012
112. Petrocca F., et al. A genome-wide siRNA screen identifies proteasome addiction as a vulnerability of basal-like triple-negative breast cancer cells. Cancer Cell 24, 182-196 (2013
113. Keats J. J., et al. Clonal competition with alternating dominance in multiple myeloma. Blood 120, 1067-1076 (2012
114. Haffner M. C., et al. Tracking the clonal origin of lethal prostate cancer. J. Clin. Invest. 123, 4918-4922 (2013
115. Fuqua S. A. W., Gu G. & Rechoum Y. Oestrogen receptor (ER) a mutations in breast cancer: hidden in plain sight. Breast Cancer Res. Treat. 144, 11-19 (2014
116. Li S., et al. Endocrine therapy resistant ESR1 variants revealed by genomic characterization of breast cancer derived xenografts. Cell Rep. 4, 1116-1130 (2013
117. Merenbakh-Lamin K., et al. D538G mutation in oestrogen receptor a: a novel mechanism for acquired endocrine resistance in breast cancer. Cancer Res. 73, 6856-6864 (2013
118. Toy W., et al. ESR1 ligand-binding domain mutations in hormone-resistant breast cancer. Nat. Genet. 45, 1439-1445 (2013
119. Jeselsohn R., et al. Emergence of constitutively active oestrogen receptor a mutations in pretreated advanced oestrogen receptor-positive breast cancer. Clin. Cancer Res. 20, 1757-1767 (2014
120. Frei E., Elias A., Wheeler C., Richardson P. & Hryniuk W. The relationship between high-dose treatment and combination chemotherapy: the concept of summation dose intensity. Clin. Cancer Res. 4, 2027-2037 (1998
121. Ades F., Zardavas D., Aftimos P. & Awada A. Anticancer drug development: moving away from the old habits. Curr. Opin. Oncol. 26, 334-339 (2014
122. Norton L. & Simon R. Tumour size, sensitivity to therapy, and design of treatment schedules. Cancer Treat. Rep. 61, 1307-1317 (1977
123. Norton L. & Simon R. The Norton-Simon hypothesis revisited. Cancer Treat. Rep. 70, 163-169 (1986
124. Pasquier E., Kavallaris M. & André N. Metronomic chemotherapy: new rationale for new directions. Nat. Rev. Clin. Oncol. 7, 455-465 (2010
125. André N., Carré M. & Pasquier E. Metronomics: towards personalized chemotherapy?. Nat. Rev. Clin. Oncol. 11, 413-431 (2014
126. Montagna E., Cancello G., Dellapasqua S., Munzone E. & Colleoni M. Metronomic therapy and breast cancer: a systematic review. Cancer Treat. Rev. 40, 942-950 (2014
127. Gatenby R. A., Silva A. S., Gillies R. J. & Frieden B. R. Adaptive therapy. Cancer Res. 69, 4894-4903 (2009
128. Silva A. S., et al. Evolutionary approaches to prolong progression-free survival in breast cancer. Cancer Res. 72, 6362-6370 (2012
129. Maley C. C., Reid B. J. & Forrest S. Cancer prevention strategies that address the evolutionary dynamics of neoplastic cells: simulating benign cell boosters and selection for chemosensitivity. Cancer Epidemiol. Biomark. 13, 1375-1384 (2004
130. ISRCTN registry [online], http://www.controlled-trials.com/ISRCTN06473203 (2014
131. Hanahan D. & Weinberg R. A. Hallmarks of cancer: the next generation. Cell 144, 646-674 (2011
132. Hanahan D. & Coussens L. M. Accessories to the crime: functions of cells recruited to the tumour microenvironment. Cancer Cell 21, 309-322 (2012
133. Chang H. Y., et al. Gene expression signature of fibroblast serum response predicts human cancer progression: similarities between tumours and wounds. PLoS Biol. 2, E7 (2004
134. Finak G., et al. Stromal gene expression predicts clinical outcome in breast cancer. Nat. Med. 14, 518-527 (2008
135. Bergamaschi A., et al. Extracellular matrix signature identifies breast cancer subgroups with different clinical outcome. J. Pathol. 214, 357-367 (2008
136. Finak G., et al. Stromal gene expression predicts clinical outcome in breast cancer. Nat. Med. 14, 518-527 (2008
137. Shree T., et al. Macrophages and cathepsin proteases blunt chemotherapeutic response in breast cancer. Genes Dev. 25, 2465-2479 (2011
138. Kim H., Park G. S., Lee J. E. & Kim J. H. A leukotriene B4 receptor 2 is associated with paclitaxel resistance in MCF 7/DOX breast cancer cells. Br. J. Cancer 109, 351-359 (2013
139. DeNardo D. G., et al. Leucocyte complexity predicts breast cancer survival and functionally regulates response to chemotherapy. Cancer Discov. 1, 54-67 (2011
140. Fang H. & DeClerck Y. A. Targeting the tumour microenvironment: from understanding pathways to effective clinical trials. Cancer Res. 73, 4965-4977 (2013
141. Marusyk A., et al. Non cell autonomous driving of tumour growth supports sub-clonal heterogeneity. Nature 514, 54-58 (2014
142. Gravitz L. Cancer immunotherapy. Nature 504, S1-S1 (2013
143. Pardoll D. M. The blockade of immune checkpoints in cancer immunotherapy. Nat. Rev. Cancer 12, 252-264 (2012
144. Barker A. D., et al. I SPY 2: an adaptive breast cancer trial design in the setting of neoadjuvant chemotherapy. Clin. Pharmacol. Ther. 86, 97-100 (2009
145. US National Library of Medicine. ClinicalTrials.gov [online], https://clinicaltrials.gov/ct2/show/NCT02299999 (2014
146. Andre F., Delaloge S. & Soria J. C. Biology driven phase II trials: what is the optimal model for molecular selection?. J. Clin. Oncol. 29, 1236-1238 (2011
147. Crowley E., Di Nicolantonio F., Loupakis F. & Bardelli A. Liquid biopsy: monitoring cancer-genetics in the blood. Nat. Rev. Clin. Oncol. 10, 472-484 (2013
148. De Mattos-Arruda L., et al. Capturing intra-tumour genetic heterogeneity by De novo mutation profiling of circulating cell-free tumour DNA: a proof of principle. Ann. Oncol. 25, 1729-1735 (2014
149. Alix-Panabières C. & Pantel K. Challenges in circulating tumour cell research. Nat. Rev. Cancer 14, 623-631 (2014
150. Lianidou E. S., Mavroudis D. & Georgoulias V. Clinical challenges in the molecular characterization of circulating tumour cells in breast cancer. Br. J. Cancer 108, 2426-2432 (2013
151. Krebs M. G., et al. Molecular analysis of circulating tumour cells-biology and biomarkers. Nat. Rev. Clin. Oncol. 11, 129-144 (2014
152. Bidard F. C., et al. Clinical validity of circulating tumour cells in patients with metastatic breast cancer: a pooled analysis of individual patient data. Lancet Oncol. 15, 406-414 (2014
153. Dawson S. J., et al. Analysis of circulating tumour DNA to monitor metastatic breast cancer. N. Engl. J. Med. 368, 1199-1209 (2013
154. Anderson A. R. A. & Quaranta V. Integrative mathematical oncology. Nat. Rev. Cancer 8, 227-234 (2008
155. Byrne H. M. Dissecting cancer through mathematics: from the cell to the animal model. Nat. Rev. Cancer 10, 221-230 (2010
156. Beckman R. A., Schemmann G. S. & Yeang C. H. Impact of genetic dynamics and single-cell heterogeneity on development of nonstandard personalized medicine strategies for cancer. Proc. Natl Acad. Sci. USA 109, 14586-14591 (2012
157. Yankeelov T. E., et al. Clinically relevant modeling of tumour growth and treatment response. Sci. Transl. Med. 5, 187ps9 (2013
158. Werner H. M. J., Mills G. B. & Ram P. T. Cancer Systems Biology: a peek into the future of patient care?. Nat. Rev. Clin. Oncol. 11, 167-176 (2014
159. Tentner A. R., et al. Combined experimental and computational analysis of DNA damage signalling reveals context-dependent roles for Erk in apoptosis and G1/S arrest after genotoxic stress. Mol. Syst. Biol. 8, 568 (2012
160. Pritchard J. R., et al. Defining principles of combination drug mechanisms of action. Proc. Natl Acad. Sci. USA 110, E170-179 (2013
161. Shah S. P., et al. The clonal and mutational evolution spectrum of primary triple-negative breast cancers. Nature 486, 395-399 (2012
162. Cibulskis K., et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat. Biotechnol. 31, 213-219 (2013
163. Garralda E., et al. Integrated next-generation sequencing and avatar mouse models for personalized cancer treatment. Clin. Cancer Res. 20, 2476-2484 (2014
164. Malaney P., Nicosia S. V. & Davé V. One mouse, one patient paradigm: new avatars of personalized cancer therapy. Cancer Lett. 344, 1-12 (2014
165. Clohessy J. & Pandolfi P. P. Mouse hospital and co-clinical trial project: from bench to bedside. Nat Rev. Clin. Oncol. http://dx.doi.org/10.1038/nrclinonc.2015.62 (2015
166. Ellis M. J., et al. Whole-genome analysis informs breast cancer response to aromatase inhibition. Nature 486, 353-360 (2012
167. Regitnig P., Schippinger W., Lindbauer M., Samonigg H. & Lax S. F. Change of HER-2/neu status in a subset of distant metastases from breast carcinomas. J. Pathol. 203, 918-926 (2004
168. Amir E., et al. Prospective study evaluating the impact of tissue confirmation of metastatic disease in patients with breast cancer. J. Clin. Oncol. 30, 587-592 (2012
169. Niikura N., et al. Loss of human epidermal growth factor receptor 2 (HER2) expression in metastatic sites of HER2-overexpressing primary breast tumors. J. Clin. Oncol. 30, 593-599 (2012
170. Li B. D., Byskosh A., Molteni A. & Duda R. B. Estrogen and progesterone receptor concordance between primary and recurrent breast cancer. J. Surg. Oncol. 57, 71-77 (1994
171. Liu J., et al. Comparison of ER/PR and HER2 statuses in primary and paired liver metastatic sites of breast carcinoma in patients with or without treatment. J. Cancer Res. Clin. Oncol. 138, 837-842 (2012