Bioinformatics and breast cancer: What can high-throughput genomic approaches actually tell us?

Journal of Clinical Pathology

Volumn 62, Issue 10, 2009, Pages 879-885

  Sims, A H ^a  

^a WESTERN GENERAL HOSPITAL   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COMPLEMENTARY DNA;

BIOINFORMATICS; BREAST CANCER; CANCER CLASSIFICATION; CANCER RESISTANCE; CANCER THERAPY; CHROMATIN IMMUNOPRECIPITATION; CLINICAL PROTOCOL; COMPARATIVE GENOMIC HYBRIDIZATION; DIAGNOSTIC ACCURACY; DNA MICROARRAY; EXPERIMENTAL STUDY; FEMALE; GENE EXPRESSION; GENE SEQUENCE; GENE TARGETING; HIGH THROUGHPUT SCREENING; HISTOPATHOLOGY; HUMAN; MASS FRAGMENTOGRAPHY; METHODOLOGY; MOLECULAR MECHANICS; NUCLEAR MAGNETIC RESONANCE; POLYMERASE CHAIN REACTION; PRIMARY TUMOR; PRIORITY JOURNAL; PROGNOSIS; REPRODUCIBILITY; REVERSE TRANSCRIPTION POLYMERASE CHAIN REACTION; REVIEW; RNA TRANSLATION; SERIAL ANALYSIS OF GENE EXPRESSION; SINGLE NUCLEOTIDE POLYMORPHISM; VALIDATION PROCESS;

BREAST NEOPLASMS; FEMALE; GENETIC PREDISPOSITION TO DISEASE; GENOMICS; HUMANS; META-ANALYSIS AS TOPIC; PROGNOSIS; REPRODUCIBILITY OF RESULTS; TECHNOLOGY TRANSFER; TISSUE ARRAY ANALYSIS;

EID: 70349696552     PISSN: 00219746     EISSN: 14724146     Source Type: Journal    
DOI: 10.1136/jcp.2008.060376     Document Type: Review

References (55)

1. Sims AH, Ong KR, Clarke RB, et al. High-throughput genomic technology in research and clinical management of breast cancer. Exploiting the potential of gene expression profiling: is it ready for the clinic? Breast Cancer Res 2006;8:214.
2. Howell A, Sims AH, Ong KR, et al. Mechanisms of Disease: prediction and prevention of breast cancer-cellular and molecular interactions. Nat Clin Pract Oncol 2005;2:635-646 (Pubitemid 43179725)
3. Perou CM, Sorlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature 2000;406:747-752
4. Sorlie T, Perou CM, Tibshirani R, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A 2001;98:10869-10874
5. Sorlie T, Tibshirani R, Parker J, et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci U S A 2003;100:8418-8423 (Pubitemid 36842560)
6. Clarke R, Ressom HW, Wang A, et al. The properties of high-dimensional data spaces: implications for exploring gene and protein expression data. Nat Rev Cancer 2008;8:37-49.
7. Miller WR, Larionov A, Anderson TJ, et al. Predicting response and resistance to endocrine therapy: profiling patients on aromatase inhibitors. Cancer 2008;112:689-694 (Pubitemid 351186390)
8. Kendall A, Anderson H, Dunbier AK, et al. Impact of estrogen deprivation on gene expression profiles of normal postmenopausal breast tissue in vivo. Cancer Epidemiol Biomarkers Prev 2008;17:855-863
9. Sorlie T, Wang Y, Xiao C, et al. Distinct molecular mechanisms underlying clinically relevant subtypes of breast cancer: Gene expression analyses across three different platforms. BMC Genomics 2006;7:127. (Pubitemid 44027496)
10. Hu Z, Fan C, Oh DS, et al. The molecular portraits of breast tumors are conserved across microarray platforms. BMC Genomics 2006;7:96. (Pubitemid 43786485)
11. Lockhart DJ, Dong H, Byrne MC, et al. Expression monitoring by hybridization to high-density oligonucleotide arrays. Nat Biotechnol 1996;14:1675-1680 (Pubitemid 26414810)
12. DeRisi JL, Iyer VR, Brown PO. Exploring the metabolic and genetic control of gene expression on a genomic scale. Science 1997;278:680-686
13. Brazma A, Kapushesky M, Parkinson H, et al. Data storage and analysis in Array Express. Methods Enzymol 2006;411:370-386 (Pubitemid 44291436)
14. Barrett T, Suzek TO, Troup DB, et al. NCBI GEO: mining millions of expression profiles-database and tools. Nucleic Acids Res 2005;33:D562-6. (Pubitemid 40207937)
15. MGED Society. http://www.mged.org (accessed 7 July 2009).
16. Tan PK, Downey TJ, Spitznagel EL Jr, et al. Evaluation of gene expression measurements from commercial microarray platforms. Nucleic Acids Res 2003;31:5676-5684 (Pubitemid 37441938)
17. Dai M, Wang P, Boyd AD, et al. Evolving gene/transcript definitions significantly alter the interpretation of Gene Chip data. Nucleic Acids Res 2005;33:e175. (Pubitemid 41806403)
18. Sims AH, Howell A, Howell SJ, et al. Origins of breast cancer subtypes and therapeutic implications. Nat Clin Pract Oncol 2007;4:516-525 (Pubitemid 47351462)
19. Sorlie T, Perou CM, Fan C, et al. Gene expression profiles do not consistently predict the clinical treatment response in locally advanced breast cancer. Mol Cancer Ther 2006;5:2914-2918 (Pubitemid 44849019)
20. Fan C, Oh DS, Wessels L, et al. Concordance among gene-expression-based predictors for breast cancer. N Engl J Med 2006;355:560-569 (Pubitemid 44200649)
21. Farmer P, Bonnefoi H, Becette V, et al. Identification of molecular apocrine breast tumours by microarray analysis. Oncogene 2005;24:4660-4671 (Pubitemid 41032603)
22. Richardson AL, Wang ZC, De Nicolo A, et al. X chromosomal abnormalities in basallike human breast cancer. Cancer Cell 2006;9:121-132 (Pubitemid 43202662)
23. Teschendorff AE, Miremadi A, Pinder SE, et al. An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer. Genome Biol 2007;8:R157. (Pubitemid 351891480)
24. van de Vijver MJ, He YD, van't Veer LJ, et al. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 1999-2009, 2002:347.
25. van't Veer LJ, Dai H, van de Vijver MJ, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002;415:530-536
26. Desmedt C, Piette F, Loi S, et al. 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 (Pubitemid 46944903)
27. Wang Y, Klijn JG, Zhang Y, et al. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 2005;365:671-679 (Pubitemid 40260888)
28. Ein-Dor L, Kela I, Getz G, et al. Outcome signature genes in breast cancer: is there a unique set? Bioinformatics 2005;21:171-178
29. Anders CK, Hsu DS, Broadwater G, et al. Young age at diagnosis correlates with worse prognosis and defines a subset of breast cancers with shared patterns of gene expression. J Clin Oncol 2008;26:3324-3330
30. Carey LA, Perou CM, Livasy CA, et al. Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA 2006;295:2492-2502 (Pubitemid 43854964)
31. Anders CK, Acharya CR, Hsu DS, et al. Age-specific differences in oncogenic pathway deregulation seen in human breast tumors. PLoS ONE 2008;3:e1373.
32. Sims AH, Smethurst GJ, Hey Y, et al. The removal of multiplicative, systematic bias allows integration of breast cancer gene expression datasets - improving metaanalysis and prediction of prognosis. BMC Med Genomics 2008;1:42.
33. Warnat P, Eils R, Brors B. Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes. BMC Bioinformatics 2005;6:265. (Pubitemid 41645660)
34. Shen R, Ghosh D, Chinnaiyan AM. Prognostic meta-signature of breast cancer developed by two-stage mixture modeling of microarray data. BMC Genomics 2004;5:94. (Pubitemid 41357639)
35. Shabalin AA, Tjelmeland H, Fan C, et al. Merging two gene-expression studies via cross-platform normalization. Bioinformatics 2008;24:1154-1160 (Pubitemid 351594164)
36. Benito M, Parker J, Du Q, et al. Adjustment of systematic microarray data biases. Bioinformatics 2004;20:105-114 (Pubitemid 38094234)
37. Johnson WE, Li C, Rabinovic A. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 2007;8:118-127 (Pubitemid 44906106)
38. Wirapati P, Sotiriou C, Kunkel S, et al. Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Res 2008;10:R65.
39. Acharya CR, Hsu DS, Anders CK, et al. Gene expression signatures, clinicopathological features, and individualized therapy in breast cancer. JAMA 2008;299:1574-1587
40. Ben-Porath I, Thomson MW, Carey VJ, et al. An embryonic stem cell-like gene expression signature in poorly differentiated aggressive human tumors. Nat Genet 2008;40:499-507. (Pubitemid 351601215)
41. Teschendorff AE, Naderi A, Barbosa-Morais NL, et al. A consensus prognostic gene expression classifier for ER positive breast cancer. Genome Biol 2006;7:R101. (Pubitemid 46442938)
42. Goldhirsch A, Glick JH, Gelber RD, et al. Meeting highlights: international expert consensus on the primary therapy of early breast cancer 2005. Ann Oncol 2005;16:1569-1583
43. Haybittle JL, Blamey RW, Elston CW, et al. A prognostic index in primary breast cancer. Br J Cancer 1982;45:361-366
44. Sotiriou C, Wirapati P, Loi S, et al. Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst 2006;98:262-272 (Pubitemid 43264710)
45. Oh DS, Troester MA, Usary J, et al. Estrogen-regulated genes predict survival in hormone receptor-positive breast cancers. J Clin Oncol 2006;24:1656-1664 (Pubitemid 46622136)
46. Paik S, Shak S, Tang G, et al. A multigene assay to predict recurrence of tamoxifentreated, node-negative breast cancer. N Engl J Med 2004;351:2817-2826 (Pubitemid 40051905)
47. Habel LA, Shak S, Jacobs MK, et al. A population-based study of tumor gene expression and risk of breast cancer death among lymph node-negative patients. Breast Cancer Res 2006;8:R25. (Pubitemid 43827376)
48. Paik S, Tang G, Shak S, et al. Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J Clin Oncol 2006;24:3726-3734 (Pubitemid 46622311)
49. Esteva FJ, Sahin AA, Cristofanilli M, et al. Prognostic role of a multigene reverse transcriptase-PCR assay in patients with node-negative breast cancer not receiving adjuvant systemic therapy. Clin Cancer Res 2005;11:3315-3319 (Pubitemid 40627881)
50. Harris L, Fritsche H, Mennel R, et al. American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer. J Clin Oncol 2007;25:5287-5312
51. Buyse M, Loi S, van't Veer L, et al. 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 (Pubitemid 44390989)
52. Lonning PE, Sorlie T, Borresen-Dale AL. Genomics in breast cancer-therapeutic implications. Nat Clin Pract Oncol 2005;2:26-33.
53. Bogaerts J, Cardoso F, Buyse M, et al. Gene signature evaluation as a prognostic tool: challenges in the design of the MINDACT trial. Nat Clin Pract Oncol 2006;3:540-551 (Pubitemid 44781724)
54. Cardoso F, Van't Veer L, Rutgers E, et al. Clinical application of the 70-gene profile: the MINDACT trial. J Clin Oncol 2008;26:729-735
55. Foekens JA, Atkins D, Zhang Y, et al. Multicenter validation of a gene expressionbased prognostic signature in lymph node-negative primary breast cancer. J Clin Oncol 2006;24:1665-1671 (Pubitemid 46622137)