A comprehensive analysis of prognostic signatures reveals the high predictive capacity of the Proliferation, Immune response and RNA splicing modules in breast cancer

Breast Cancer Research

Volumn 10, Issue 6, 2008, Pages

  Reyal, Fabien ^a,b,c   van Vliet, Martin H ^a,d   Armstrong, Nicola J ^a   Horlings, Hugo M ^a   de Visser, Karin E ^a   Kok, Marlen ^a   Teschendorff, Andrew E ^e   Mook, Stella ^a   van 't Veer, Laura ^a   Caldas, Carlos ^e   Salmon, Remy J ^c   Vijver, Marc J V D ^a,f   Wessels, Lodewyk F A ^a,d  

^a NETHERLANDS CANCER INSTITUTE   (Netherlands)

^b INSTITUT CURIE   (France)

^c INSTITUT CURIE   (France)

^d DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

^e UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^f ACADEMIC MEDICAL CENTER   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BIOLOGY; BREAST TUMOR; CELL PROLIFERATION; COMPARATIVE STUDY; FEMALE; GENE EXPRESSION PROFILING; GENETIC DATABASE; GENETICS; HUMAN; IMMUNITY; METABOLISM; PATHOLOGY; PHYSIOLOGY; PROGNOSIS; RNA SPLICING; SURVIVAL RATE;

BREAST NEOPLASMS; CELL PROLIFERATION; COMPUTATIONAL BIOLOGY; DATABASES, GENETIC; FEMALE; GENE EXPRESSION PROFILING; HUMANS; IMMUNE SYSTEM PROCESSES; PROGNOSIS; RNA SPLICING; SURVIVAL RATE;

EID: 63849148854     PISSN: 14655411     EISSN: 1465542X     Source Type: Journal    
DOI: 10.1186/bcr2192     Document Type: Article

References (59)

1. Goldhirsch A, Wood WC, Gelber RD, Coates AS, Thürlimann B, Senn H-J. Progress and promise: highlights of the international expert consensus on the primary therapy of early breast cancer 2007. Ann Oncol 2007, 18:1133-1144.
2. Eifel P, Axelson JA, Costa J, Crowley J, Curran WJ, Deshler A, Fulton S, Hendricks CB, Kemeny M, Kornblith AB, Louis TA, Markman M, Mayer R, Roter D. National Institutes of Health Consensus Development Conference Statement: adjuvant therapy for breast cancer, November 1-3, 2000. J Natl Cancer Inst 2001, 93:979-989.
3. Blamey RW, Ellis IO, Pinder SE, Lee AHS, Macmillan RD, Morgan DAL, Robertson JFR, Mitchell MJ, Ball GR, Haybittle JL, Elston CW. Survival of invasive breast cancer according to the Nottingham Prognostic Index in cases diagnosed in 1990-1999. Eur J Cancer 2007, 43:1548-1555.
4. Ravdin PM, Siminoff LA, Davis GJ, Mercer MB, Hewlett J, Gerson N, Parker HL. Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer. J Clin Oncol 2001, 19:980-991.
5. Early Breast Cancer Trialists' Collaborative Group Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet 2005, 365:1687-1717. Early Breast Cancer Trialists' Collaborative Group.
6. van 't Veer LJ, Dai H, Vijver MJ, He YD, Hart AAM, Mao M, Peterse HL, Kooy K, Marton MJ, Witteveen AT, Schreiber GJ, Kerhoven RM, Roberts C, Linsley PS, Bernards R, Friend SH. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002, 415:530-536.
7. Vijver MJ, He YD, van 't Veer LJ, Dai H, Hart AAM, Voskuil DW, Schreiber GJ, Peterse JL, Roberts C, Marton MJ, Parrish M, Atsma D, Witteveen A, Glas A, Delahaye L, Velde T, Bartelink H, Rodenhuis S, Rutgers ET, Friend SH, Bernards R. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 2002, 347:1999-2009.
8. Wang Y, Klijn JG, Zhang Y, Sieuwerts AM, Look MP, Yang F, Talantov D, Timmermans M, Meijer-van Gelder ME, Yu J, Jatkoe T, Berns EM, Atkins D, Foekens JA. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. The Lancet 2005, 365:671-679. 15721472.
9. Desmedt C, Piette F, Loi S, Wang Y, Lallemand F, Haibe-Kains B, Viale G, Delorenzi M, Zhang Y, d'Assignies MS, Bergh J, Lidereau R, Ellis P, Harris AL, Klijn JGM, Foekens JA, Cardoso F, Piccart MJ, Buyse M, Sotiriou C. Strong time dependence of the 76-gene prognostic signature for node-negative breast cancer patients in the TRANSBIG multicenter independent validation series. Clin Cancer Res 2007, 13:3207-3214.
10. Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M, Baehner FL, Walker MG, Watson D, Park T, Hiller W, Fisher ER, Wickerham DL, Bryant J, Wolmark N. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 2004, 351:2817-2826.
11. Bogaerts J, Cardoso F, Buyse M, Braga S, Loi S, Harrison JA, Bines J, Mook S, Decker N, Ravdin P, Therasse P, Rutgers E, van 't Veer LJ, Piccart M, . the TRANSBIG consortium Gene signature evaluation as a prognostic tool: challenges in the design of the MINDACT trial. Nat Clin Pract Oncol 2006, 3:540-551. the TRANSBIG consortium.
12. Paik S. Development and clinical utility of a 21-gene recurrence score prognostic assay in patients with early breast cancer treated with tamoxifen. Oncologist 2007, 12:631-635.
13. Carter SL, Eklund AC, Kohane IS, Harris LN, Szallasi Z. A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers. Nat Genet 2006, 38:1043-1048.
14. Chang HY, Nuyten DS, Sneddon JB, Hastie T, Tibshirani R, Sorlie T, Dai H, He YD, van 't Veer LJ, Bartelink H, van Rijn M, Brown PO, Vijver MJ. Robustness, scalability, and integration of a wound-response gene expression signature in predicting breast cancer survival. Proc Natl Acad Sci USA 2005, 102:3738-3743. 548329, 15701700.
15. Hu Z, Cheng F, Oh DS, Marron JS, He X, Qaqish BF, Livasy C, Carey LA, Reynolds E, Dressler L, Nobel A, Parker J, Ewend MG, Sawyer LR, Wu J, Liu Y, Nanda R, Tretiakova M, Orrico AR, Dreher D, Palazzo JP, Perreard L, Nelson E, Mone M, Hansen H, Mullins M, Quackenbush JF, Ellis MJ, Olopade OI, Bernard PS, Perou CM. The molecular portraits of breast tumors are conserved across microarray platforms. BMC Genomics 2006, 7:96. 1468408, 16643655.
16. Liu R, Wang X, Grace YC, Dalerba P, Gurney A, Hoey T, Sherlock G, Lewicki J, Shedden K, Clarke MF. The prognostic role of a gene signature from tumorigenic breast-cancer cells. N Engl J Med 2007, 356:217-226.
17. Loi S, Haibe-Kains B, Desmedt C, Lallemand F, Tutt AM, Gillet C, Ellis P, Harris A, Bergh J, Foekens JA, Klijn JGM, Larsimont D, Buyse M, Bontempi G, Delorenzi M, Piccart MJ, Sotiriou C. Definition of clinically distinct molecular subtypes in estrogen receptor-positive breast carcinomas through genomic grade. J Clin Oncol 2007, 25:1239-1246.
18. Miller LD, Smeds J, George J, Vega VB, Vergara L, Ploner A, Pawitan Y, Hall P, Klaar S, Liu ET, Bergh J. An expression signature for p53 status in human breast cancer predicts mutation status, transcriptional effects, and patient survival. Proc Natl Acad Sci USA 2005, 102:13550-13555. 1197273, 16141321.
19. Minn AJ, Gupta GP, Siegel PM, Bos PD, Shu WP, Giri DD, Viale A, Olshen AB, Gerald WL, Massague J. Genes that mediate breast cancer metastasis to lung. Nature 2005, 436:518-524. 1283098, 16049480.
20. Teschendorff AE, Naderi A, Barbosa-Morais NL, Pinder SE, Ellis IO, Aparicio S, Brenton JD, Caldas C. A consensus prognostic gene expression classifier for ER positive breast cancer. Genome Biol 2006, 7:R101. 1794561, 17076897.
21. Teschendorff AE, Miremadi A, Pinder S, Ellis I, Caldas C. An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer. Genome Biol 2007, 8:R157. 2374988, 17683518.
22. Sotiriou C, Piccart MJ. Taking gene-expression profiling to the clinic: when will molecular signatures become relevant to patient care?. Nat Rev Cancer 2007, 7:545-553.
23. Ein-Dor L, Zuk O, Domany E. Thousands of samples are needed to generate a robust gene list for predicting outcome in cancer. Proc Natl Acad Sci USA 2006, 103:5923-5928. 1458674, 16585533.
24. Fan C, Oh DS, Wessels L, Weigelt B, Nuyten DS, Nobel AB, van't Veer LJ, Perou CM. Concordance among gene-expression-based predictors for breast cancer. N Engl J Med 2006, 355:560-569.
25. Sotiriou C, Wirapati P, Loi S, Harris A, Fox S, Smeds J, Nordgren H, Farmer P, Praz V, Haibe-Kains B, Desmedt C, Larsimont D, Cardoso F, Peterse H, Nuyten D, Buyse M, Vijver MJ, Bergh J, Piccart M, Delorenzi M. Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst 2006, 98:262-272.
26. Mook S, Schmidt MK, Viale G, Pruneri G, Eekhout I, Floore A, Glas AM, Bogaerts J, Cardoso F, Piccart-Gebhart MJ, Rutgers ET, Van't Veer LJ, . On behalf of the TRANSBIG consortium The 70-gene prognosis-signature predicts disease outcome in breast cancer patients with 1-3 positive lymph nodes in an independent validation study. Breast Cancer Res Treat 2008, On behalf of the TRANSBIG consortium.
27. Goldstein LJ, Gray R, Badve S, Childs BH, Yoshizawa C, Rowley S, Shak S, Baehner FL, Ravdin PM, Davidson NE, Sledge GW, Perez EA, Shulman LN, Martino S, Sparano JA. Prognostic utility of the 21-gene assay in hormone receptor-positive operable breast cancer compared with classical clinicopathologic features. J Clin Oncol 2008, 26:4063-4071.
28. Pawitan Y, Bjöhle J, Amler L, Borg A-L, Egyhazi S, Hall P, Han X, Holmberg L, Huang F, Klaar S, Liu ET, Miller L, Nordgren H, Ploner A, Sandelin K, Shaw PM, Smeds J, Skoog L, Wedrén S, Bergh J. Gene expression profiling spares early breast cancer patients from adjuvant therapy: derived and validated in two population-based cohorts. Breast Cancer Res 2005, 7:R953-R964. 1410752, 16280042.
29. Chin K, DeVries S, Fridlyand J, Spellman PT, Roydasgupta R, Kuo W-L, Lapuk A, Neve RM, Qian Z, Ryder T. Genomic and transcriptional aberrations linked to breast cancer pathophysiologies. Cancer Cell 2006, 10:529-541.
30. Gene Expression Omnibus. , http://www.ncbi.nlm.nih.gov/geo/
31. ArrayExpress repository. , http://www.ebi.ac.uk/microarray-as/ae/
32. R. , http://cran.r-project.org/
33. Bioconductor. , http://www.bioconductor.org
34. Matlab. , http://www.mathworks.com/
35. Gene Ontology. , http://www.ncbi.nlm.nih.gov/
36. Kyoto Encyclopedia of Genes and Genomes. , http://www.genome.ad.jp
37. Reactome. , http://www.reactome.org
38. Molecular Signatures Database. , http://www.broad.mit.edu/gsea/
39. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B 1995, 57:289-300.
40. Schemper M, Henderson R. Predictive accuracy and explained variation in Cox regression. Biometrics 2000, 56:249-255.
41. Lusa L, Miceli R, Mariani L. Estimation of predictive accuracy in survival analysis using R and S-PLUS. Comput Methods Programs Biomed 2007, 87:132-137.
42. Dunkler D, Michiels S, Schemper M. Gene expression profiling: does it add predictive accuracy to clinical characteristics in cancer prognosis?. Eur J Cancer 2007, 43:745-751.
43. Buyse M, Loi S, van't Veer L, Viale G, Delorenzi M, Glas AM, d'Assignies MS, Bergh J, Lidereau R, Ellis P, Harris A, Bogaerts J, Therasse P, Floore A, Amakrane M, Piette F, Rutgers E, Sotiriou C, Cardoso F, Piccart MJ, . the TRANSBIG Consortium Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer. J Natl Cancer Inst 2006, 98:1183-1192. the TRANSBIG Consortium.
44. Whitfield ML, George LK, Grant GD, Perou CM. Common markers of proliferation. Nat Rev Cancer 2006, 6:99-106.
45. Chung CH, Bernard PS, Perou CM. Molecular portraits and the family tree of cancer. Nat Genet 2002, 32(Suppl):533-540.
46. Yu J, Sieuwerts A, Zhang Y, Martens J, Smid M, Klijn J, Wang Y, Foekens J. Pathway analysis of gene signatures predicting metastasis of node-negative primary breast cancer. BMC Cancer 2007, 7:182. 2077336, 17894856.
47. de Visser KE, Coussens LM. The inflammatory tumor microenvironment and its impact on cancer development. Contrib Microbiol 2006, 13:118-137. 16627962.
48. Galon J, Costes A, Sanchez-Cabo F, Kirilovsky A, Mlecnik B, Lagorce-Pagès C, Tosolini M, Camus M, Berger A, Wind P, Zinzindohoué F, Bruneval P, Cugnenc P-H, Trajanoski Z, Fridman W-H, Pagès F. Type, density, and location of immune cells within human colorectal tumors predict clinical outcome. Science 2006, 313:1960-1964.
49. Venables JP. Aberrant and alternative splicing in cancer. Cancer Res 2004, 64:7647-7654.
50. Venables JP. Unbalanced alternative splicing and its significance in cancer. Bioessays 2006, 28:378-386.
51. Pajares MJ, Ezponda T, Catena R, Calvo A, Pio R, Montuenga LM. Alternative splicing: an emerging topic in molecular and clinical oncology. Lancet Oncol 2007, 8:349-357.
52. Mazoyer S, Puget N, Perrin-Vidoz L, Lynch HT, Serova-Sinilnikova OM, Lenoir GM. A BRCA1 nonsense mutation causes exon skipping. Am J Hum Genet 1998, 62:713-715. 1376962, 9497265.
53. Chen LL, Sabripour M, Wu EF, Prieto VG, Fuller GN, Frazier ML. A mutation-created novel intra-exonic pre-mRNA splice site causes constitutive activation of KIT in human gastrointestinal stromal tumors. Oncogene 2005, 24:4271-4280.
54. Watermann DO, Tang Y, Hausen AZ, Jäger M, Stamm S, Stickeler E. Splicing factor Tra2-beta1 is specifically induced in breast cancer and regulates alternative splicing of the CD44 gene. Cancer Res 2006, 66:4774-4780.
55. Hayes GM, Carrigan PE, Miller LJ. Serine-arginine protein kinase 1 overexpression is associated with tumorigenic imbalance in mitogen-activated protein kinase pathways in breast, colonic, and pancreatic carcinomas. Cancer Res 2007, 67:2072-2080.
56. Hayes GM, Carrigan PE, Beck AM, Miller LJ. Targeting the RNA splicing machinery as a novel treatment strategy for pancreatic carcinoma. Cancer Res 2006, 66:3819-3827.
57. Yang ZQS, Katie L, Ray ME, Abrams J, Ethier SP. Multiple interacting oncogenes on the 8p11-p12 amplicon in human breast cancer. Cancer Res 2006, 66:11632-11643.
58. Streicher KL, Yang ZQ, Draghici S, Ethier SP. Transforming function of the LSM1 oncogene in human breast cancers with the 8p11-12 amplicon. Oncogene 2007, 26:2104-2114. 2435249, 17001308.
59. van Vliet MH, Reyal F, Horlings HM, Vijver MJ, Reinders MJ, Wessels LF. Pooling breast cancer datasets has a synergetic effect on classification performance and improves signature stability. BMC Genomics 2008, 9:375. 2527336, 18684329.