Intrinsic cancer subtypes-next steps into personalized medicine

Cellular Oncology

Volumn 38, Issue 1, 2015, Pages 3-16

  Santos, Cristina ^a   Sanz Pamplona, Rebeca ^a   Nadal, Ernest ^b   Grasselli, Julieta ^a   Pernas, Sonia ^a   Dienstmann, Rodrigo ^c   Moreno, Victor ^a,d   Tabernero, Josep ^e   Salazar, Ramon ^a  

^a HOSPITAL UNIVERSITARI DE BELLVITGE   (Spain)

^b UNIVERSITY OF MICHIGAN COMPREHENSIVE CANCER CENTER   (United States)

^c SAGE BIONETWORKS   (United States)

^d UNIVERSITY OF BARCELONA   (Spain)

^e HOSPITAL UNIVERSITARI VALL D HEBRON   (Spain)

Author keywords

Breast neoplasms; Colorectal neoplasms; Gene expression profiling; Intrinsic subtypes; Lung neoplasms; Unsupervised analysis

Indexed keywords

TRANSCRIPTOME;

ARTICLE; BREAST CANCER; CANCER CHEMOTHERAPY; CANCER PATIENT; CANCER STAGING; CANCER SURVIVAL; COLORECTAL CANCER; COMPARATIVE STUDY; DISEASE FREE SURVIVAL; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENOMICS; HEALTH CARE COST; HEALTH CARE QUALITY; HUMAN; MICROSATELLITE INSTABILITY; NEOPLASM; OVERALL SURVIVAL; PERSONALIZED MEDICINE; PRIORITY JOURNAL; SOMATIC MUTATION; TUMOR SUPPRESSOR GENE; CLASSIFICATION; GENETICS; MOLECULARLY TARGETED THERAPY; NEOPLASMS; PROCEDURES;

HUMANS; MOLECULAR TARGETED THERAPY; NEOPLASMS; PRECISION MEDICINE;

EID: 84925483701     PISSN: 22113428     EISSN: 22113436     Source Type: Journal    
DOI: 10.1007/s13402-014-0203-7     Document Type: Article

References (106)

1. A. Jemal et al., Global cancer statistics. CA Cancer J. Clin. 61(2), 69–90 (2011)
2. I. Nishisho et al., Mutations of chromosome 5q21 genes in FAP and colorectal cancer patients. Science 253(5020), 665–669 (1991)
3. W. Eiermann, Trastuzumab combined with chemotherapy for the treatment of HER2-positive metastatic breast cancer: pivotal trial data. Ann. Oncol. 12(Suppl 1), S57–S62 (2001)
4. A. Goldhirsch, et al., 2 years versus 1 year of adjuvant trastuzumab for HER2-positive breast cancer (HERA): an open-label, randomised controlled trial. Lancet 382(9897), 1021–1028
5. S.M. Swain et al., Pertuzumab, trastuzumab, and docetaxel for HER2-positive metastatic breast cancer (CLEOPATRA study): overall survival results from a randomised, double-blind, placebo-controlled, phase 3 study. Lancet Oncol. 14(6), 461–471 (2013)
6. B. Boyraz et al., Trastuzumab emtansine (T-DM1) for HER2-positive breast cancer. Curr. Med. Res. Opin. 29(4), 405–414 (2013)
7. M. Cronin et al., Analytical validation of the Oncotype DX genomic diagnostic test for recurrence prognosis and therapeutic response prediction in node-negative, estrogen receptor-positive breast cancer. Clin. Chem. 53(6), 1084–1091 (2007)
8. M.J. van de Vijver et al., A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med. 347(25), 1999–2009 (2002)
9. R. Salazar et al., Gene expression signature to improve prognosis prediction of stage II and III colorectal cancer. J. Clin. Oncol. 29(1), 17–24 (2010)
10. Director’s Challenge Consortium for the Molecular Classification of Lung, A et al., Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study. Nat. Med. 14(8), 822–827 (2008)
11. C.M. Perou et al., Molecular portraits of human breast tumours. Nature 406(6797), 747–752 (2000)
12. L.H. Sobin, TNM: evolution and relation to other prognostic factors. Semin. Surg. Oncol. 21(1), 3–7 (2003)
13. M. Cianfrocca, L.J. Goldstein, Prognostic and predictive factors in early-stage breast cancer. Oncologist 9(6), 606–616 (2004)
14. T. Utsumi, N. Kobayashi, H. Hanada, Recent perspectives of endocrine therapy for breast cancer. Breast Cancer 14(2), 194–199 (2007)
15. C.A. Hudis, Trastuzumab–mechanism of action and use in clinical practice. N. Engl. J. Med. 357(1), 39–51 (2007)
16. M.C. Paterson et al., Correlation between c-erbB-2 amplification and risk of recurrent disease in node-negative breast cancer. Cancer Res. 51(2), 556–567 (1991)
17. V. Guarneri, P.F. Conte, The curability of breast cancer and the treatment of advanced disease. Eur. J. Nucl. Med. Mol. Imaging 31(Suppl 1), S149–S161 (2004)
18. X. Lu, Y. Kang, Organotropism of breast cancer metastasis. J. Mammary Gland Biol. Neoplasia 12(2–3), 153–162 (2007)
19. M. Gnant et al., Predicting distant recurrence in receptor-positive breast cancer patients with limited clinicopathological risk: using the PAM50 Risk of Recurrence score in 1478 postmenopausal patients of the ABCSG-8 trial treated with adjuvant endocrine therapy alone. Ann. Oncol. 25(2), 339–345 (2014)
20. M. Martin et al., Clinical validation of the EndoPredict test in node-positive, chemotherapy-treated ER+/HER2- breast cancer patients: results from the GEICAM 9906 trial. Breast Cancer Res. 16(2), R38 (2014)
21. R. Sanz-Pamplona et al., Expression of endoplasmic reticulum stress proteins is a candidate marker of brain metastasis in both ErbB-2+ and ErbB-2- primary breast tumors. Am. J. Pathol. 179(2), 564–579 (2011)
22. Y. Kang et al., A multigenic program mediating breast cancer metastasis to bone. Cancer Cell 3(6), 537–549 (2003)
23. A.J. Minn et al., Genes that mediate breast cancer metastasis to lung. Nature 436(7050), 518–524 (2005)
24. K. Driouch et al., Gene arrays for diagnosis, prognosis and treatment of breast cancer metastasis. Clin. Exp. Metastasis 24(8), 575–585 (2007)
25. T. Sorlie et al., Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc. Natl. Acad. Sci. U. S. A. 98(19), 10869–10874 (2001)
26. A. Prat, C.M. Perou, Deconstructing the molecular portraits of breast cancer. Mol. Oncol. 5(1), 5–23 (2011)
27. T. Sorlie et al., Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc. Natl. Acad. Sci. U. S. A. 100(14), 8418–8423 (2003)
28. R.D. Baird, C. Caldas, Genetic heterogeneity in breast cancer: the road to personalized medicine? BMC Med. 11, 151 (2013)
29. M. Smid et al., Subtypes of breast cancer show preferential site of relapse. Cancer Res. 68(9), 3108–3114 (2008)
30. R. Rouzier et al., Breast cancer molecular subtypes respond differently to preoperative chemotherapy. Clin. Cancer Res. 11(16), 5678–5685 (2005)
31. J.S. Parker et al., Supervised risk predictor of breast cancer based on intrinsic subtypes. J. Clin. Oncol. 27(8), 1160–1167 (2009)
32. M. Dowsett et al., Comparison of PAM50 risk of recurrence score with oncotype DX and IHC4 for predicting risk of distant recurrence after endocrine therapy. J. Clin. Oncol. 31(22), 2783–2790 (2013)
33. J.I. Herschkowitz et al., Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumors. Genome Biol. 8(5), R76 (2007)
34. A. Prat et al., Phenotypic and molecular characterization of the claudin-low intrinsic subtype of breast cancer. Breast Cancer Res. 12(5), R68 (2010)
35. C. Curtis et al., The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 486(7403), 346–352 (2012)
36. Comprehensive molecular portraits of human breast tumours. Nature 490(7418), 61–70
37. P.J. Stephens et al., The landscape of cancer genes and mutational processes in breast cancer. Nature 486(7403), 400–404 (2012)
38. M.J. Ellis et al., Whole-genome analysis informs breast cancer response to aromatase inhibition. Nature 486(7403), 353–360 (2012)
39. S. Banerji et al., Sequence analysis of mutations and translocations across breast cancer subtypes. Nature 486(7403), 405–409 (2012)
40. M.J. Ellis, C.M. Perou, The genomic landscape of breast cancer as a therapeutic roadmap. Cancer Discov. 3(1), 27–34 (2013)
41. A. Goldhirsch et al., Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013. Ann. Oncol. 24(9), 2206–2223 (2013)
42. J.B. O’Connell, M.A. Maggard, C.Y. Ko, Colon cancer survival rates with the new American Joint Committee on Cancer sixth edition staging. J. Natl. Cancer Inst. 96(19), 1420–1425 (2004)
43. T. Andre et al., Oxaliplatin, fluorouracil, and leucovorin as adjuvant treatment for colon cancer. N. Engl. J. Med. 350(23), 2343–2351 (2004)
44. S. Gill et al., Pooled analysis of fluorouracil-based adjuvant therapy for stage II and III colon cancer: who benefits and by how much? J. Clin. Oncol. 22(10), 1797–1806 (2004)
45. A.B. Benson 3rd et al., American Society of Clinical Oncology recommendations on adjuvant chemotherapy for stage II colon cancer. J. Clin. Oncol. 22(16), 3408–3419 (2004)
46. E. Van Cutsem, J. Oliveira, Primary colon cancer: ESMO clinical recommendations for diagnosis, adjuvant treatment and follow-up. Ann. Oncol. 20(Suppl 4), 49–50 (2009)
47. E.R. Fearon, Molecular genetics of colorectal cancer. Annu. Rev. Pathol. 6, 479–507 (2011)
48. C. Sweeney et al., Oncogenetic tree model of somatic mutations and DNA methylation in colon tumors. Genes Chromosom. Cancer 48(1), 1–9 (2009)
49. M. Toyota et al., CpG island methylator phenotype in colorectal cancer. Proc. Natl. Acad. Sci. U. S. A. 96(15), 8681–8686 (1999)
50. J.R. Jass, Classification of colorectal cancer based on correlation of clinical, morphological and molecular features. Histopathology 50(1), 113–130 (2007)
51. S. Ogino, A. Goel, Molecular classification and correlates in colorectal cancer. J. Mol. Diagn. 10(1), 13–27 (2008)
52. G.P. Kim et al., Prognostic and predictive roles of high-degree microsatellite instability in colon cancer: a National Cancer Institute-National Surgical Adjuvant Breast and Bowel Project Collaborative Study. J. Clin. Oncol. 25(7), 767–772 (2007)
53. G. Hutchins et al., Value of mismatch repair, KRAS, and BRAF mutations in predicting recurrence and benefits from chemotherapy in colorectal cancer. J. Clin. Oncol. 29(10), 1261–1270 (2011)
54. G. Yothers et al., Validation of the 12-gene colon cancer recurrence score in NSABP C-07 as a predictor of recurrence in patients with stage II and III colon cancer treated with fluorouracil and leucovorin (FU/LV) and FU/LV plus oxaliplatin. J. Clin. Oncol. 31(36), 4512–4519 (2013)
55. S. Kopetz, et al., Genomic classifier (ColoPrint) to predict outcome and chemotherapy benefit in stage II and III colon cancer patients. J. Clin. Oncol. 31, (2013). ((suppl; abstr 3612))
56. L. Marisa et al., Gene expression classification of colon cancer into molecular subtypes: characterization, validation, and prognostic value. PLoS Med. 10(5), e1001453 (2013)
57. A. Loboda et al., EMT is the dominant program in human colon cancer. BMC Med. Genom. 4, 9 (2011)
58. E. Budinska et al., Gene expression patterns unveil a new level of molecular heterogeneity in colorectal cancer. J. Pathol. 231(1), 63–76 (2013)
59. P. Roepman et al., Colorectal cancer intrinsic subtypes predict chemotherapy benefit, deficient mismatch repair and epithelial-to-mesenchymal transition. Int. J. Cancer 134(3), 552–562 (2013)
60. B. Perez-Villamil et al., Colon cancer molecular subtypes identified by expression profiling and associated to stroma, mucinous type and different clinical behavior. BMC Cancer 12, 260 (2012)
61. E.M.F. De Sousa et al., Poor-prognosis colon cancer is defined by a molecularly distinct subtype and develops from serrated precursor lesions. Nat. Med. 19(5), 614–618 (2013)
62. A. Schlicker et al., Subtypes of primary colorectal tumors correlate with response to targeted treatment in colorectal cell lines. BMC Med. Genom. 5, 66 (2013)
63. A. Sadanandam et al., A colorectal cancer classification system that associates cellular phenotype and responses to therapy. Nat. Med. 19(5), 619–625 (2013)
64. Comprehensive molecular characterization of human colon and rectal cancer. Nature 487(7407), 330–337 (2012)
65. S.C. Oh et al., Prognostic gene expression signature associated with two molecularly distinct subtypes of colorectal cancer. Gut 61(9), 1291–1298 (2012)
66. R. Dienstmann, et al., Colorectal Cancer Subtyping Consortium (CRCSC) identification of a consensus of molecular subtypes. J. Clin. Oncol. 32, (2014). ((suppl; abstr 3511))
67. W.D. Travis et al., International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society: international multidisciplinary classification of lung adenocarcinoma: executive summary. Proc. Am. Thorac. Soc. 8(5), 381–385 (2011)
68. A. Warth et al., The novel histologic International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification system of lung adenocarcinoma is a stage-independent predictor of survival. J. Clin. Oncol. 30(13), 1438–1446 (2012)
69. F.C. Detterbeck, D.J. Boffa, L.T. Tanoue, The new lung cancer staging system. Chest 136(1), 260–271 (2009)
70. National Comprehensive Cancer Network. Non-Small Cell Lung Cancer (v 3.2014). Available from: http://www.nccn.org/professionals/physician_gls/pdf/nscl.pdf
71. L.M. Sholl et al., EGFR mutation is a better predictor of response to tyrosine kinase inhibitors in non-small cell lung carcinoma than FISH, CISH, and immunohistochemistry. Am. J. Clin. Pathol. 133(6), 922–934 (2010)
72. K. Takeuchi et al., RET, ROS1 and ALK fusions in lung cancer. Nat. Med. 18(3), 378–381 (2012)
73. B.E. Johnson, et al., A multicenter effort to identify driver mutations and employ targeted therapy in patients with lung adenocarcinomas: the Lung Cancer Mutation Consortium (LCMC). J Clin Oncol. 31, (2013). (suppl; abstr 8019)
74. F. Barlesi, et al., Biomarkers (BM) France: Results of routine EGFR, HER2, KRAS, BRAF, PI3KCA mutations detection and EML4-ALK gene fusion assessment on the first 10,000 non-small cell lung cancer (NSCLC) patients (pts). J. Clin. Oncol. 31, (2013). (suppl; abstr 8000)
75. L. West et al., A novel classification of lung cancer into molecular subtypes. PLoS One 7(2), e31906 (2012)
76. A. Bhattacharjee et al., Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses. Proc. Natl. Acad. Sci. U. S. A. 98(24), 13790–13795 (2001)
77. M.E. Garber et al., Diversity of gene expression in adenocarcinoma of the lung. Proc. Natl. Acad. Sci. U. S. A. 98(24), 13784–13789 (2001)
78. D.G. Beer et al., Gene-expression profiles predict survival of patients with lung adenocarcinoma. Nat. Med. 8(8), 816–824 (2002)
79. S. Tomida et al., Gene expression-based, individualized outcome prediction for surgically treated lung cancer patients. Oncogene 23(31), 5360–5370 (2004)
80. T. Takeuchi et al., Expression profile-defined classification of lung adenocarcinoma shows close relationship with underlying major genetic changes and clinicopathologic behaviors. J. Clin. Oncol. 24(11), 1679–1688 (2006)
81. S. Tomida et al., Relapse-related molecular signature in lung adenocarcinomas identifies patients with dismal prognosis. J. Clin. Oncol. 27(17), 2793–2799 (2009)
82. Y. Yatabe, T. Mitsudomi, T. Takahashi, TTF-1 expression in pulmonary adenocarcinomas. Am. J. Surg. Pathol. 26(6), 767–773 (2002)
83. H.Y. Chen et al., A five-gene signature and clinical outcome in non-small-cell lung cancer. N. Engl. J. Med. 356(1), 11–20 (2007)
84. A. Potti et al., A genomic strategy to refine prognosis in early-stage non-small-cell lung cancer. N. Engl. J. Med. 355(6), 570–580 (2006)
85. C.M. Bryant et al., Clinically relevant characterization of lung adenocarcinoma subtypes based on cellular pathways: an international validation study. PLoS One 5(7), e11712 (2010)
86. D.N. Hayes et al., Gene expression profiling reveals reproducible human lung adenocarcinoma subtypes in multiple independent patient cohorts. J. Clin. Oncol. 24(31), 5079–5090 (2006)
87. M.D. Wilkerson et al., Differential pathogenesis of lung adenocarcinoma subtypes involving sequence mutations, copy number, chromosomal instability, and methylation. PLoS One 7(5), e36530 (2012)
88. B. Angulo et al., Expression signatures in lung cancer reveal a profile for EGFR-mutant tumours and identify selective PIK3CA overexpression by gene amplification. J. Pathol. 214(3), 347–356 (2008)
89. D. Chitale et al., An integrated genomic analysis of lung cancer reveals loss of DUSP4 in EGFR-mutant tumors. Oncogene 28(31), 2773–2783 (2009)
90. H. Okayama et al., Identification of genes upregulated in ALK-positive and EGFR/KRAS/ALK-negative lung adenocarcinomas. Cancer Res. 72(1), 100–111 (2012)
91. M. Planck et al., Genomic and transcriptional alterations in lung adenocarcinoma in relation to EGFR and KRAS mutation status. PLoS One 8(10), e78614 (2013)
92. M. Planck et al., Identification of transcriptional subgroups in EGFR-mutated and EGFR/KRAS wild-type lung adenocarcinoma reveals gene signatures associated with patient outcome. Clin. Cancer Res. 19(18), 5116–5126 (2013)
93. K. Inamura et al., Two subclasses of lung squamous cell carcinoma with different gene expression profiles and prognosis identified by hierarchical clustering and non-negative matrix factorization. Oncogene 24(47), 7105–7113 (2005)
94. J.E. Larsen et al., Expression profiling defines a recurrence signature in lung squamous cell carcinoma. Carcinogenesis 28(3), 760–766 (2007)
95. M. Raponi et al., Gene expression signatures for predicting prognosis of squamous cell and adenocarcinomas of the lung. Cancer Res. 66(15), 7466–7472 (2006)
96. M.D. Wilkerson et al., Lung squamous cell carcinoma mRNA expression subtypes are reproducible, clinically important, and correspond to normal cell types. Clin. Cancer Res. 16(19), 4864–4875 (2010)
97. Comprehensive genomic characterization of squamous cell lung cancers. Nature 489(7417), 519–525 (2012)
98. C.Q. Zhu et al., Prognostic and predictive gene signature for adjuvant chemotherapy in resected non-small-cell lung cancer. J. Clin. Oncol. 28(29), 4417–4424 (2010)
99. D.T. Chen et al., Prognostic and predictive value of a malignancy-risk gene signature in early-stage non-small cell lung cancer. J. Natl. Cancer Inst. 103(24), 1859–1870 (2011)
100. Y.Y. Park et al., Development and validation of a prognostic gene-expression signature for lung adenocarcinoma. PLoS One 7(9), e44225 (2012)
101. H. Tang et al., A 12-gene set predicts survival benefits from adjuvant chemotherapy in non-small cell lung cancer patients. Clin. Cancer Res. 19(6), 1577–1586 (2013)
102. J. Subramanian, R. Simon, Gene expression-based prognostic signatures in lung cancer: ready for clinical use? J. Natl. Cancer Inst. 102(7), 464–474 (2010)
103. B. Vogelstein et al., Cancer genome landscapes. Science 339(6127), 1546–1558 (2013)
104. A. Calon et al., Dependency of colorectal cancer on a TGF-beta-driven program in stromal cells for metastasis initiation. Cancer Cell 22(5), 571–584 (2012)
105. U. Sack et al., S100A4-induced cell motility and metastasis is restricted by the Wnt/beta-catenin pathway inhibitor calcimycin in colon cancer cells. Mol. Biol. Cell 22(18), 3344–3354 (2011)
106. R. Dienstmann et al., Genomic medicine frontier in human solid tumors: prospects and challenges. J. Clin. Oncol. 31(15), 1874–1884 (2013)