Integrated analysis of gene expression profiling studies - Examples in breast cancer

Bioinformatics: A Swiss Perspective

Volumn , Issue , 2009, Pages 85-114

  Wirapati, Pratyaksha ^a   Goldstein, Darlene R ^a,b   Delorenzi, Mauro ^a  

^a SWISS INSTITUTE OF BIOINFORMATICS   (Switzerland)

^b EPFL   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

BREAST CANCER; GENE EXPRESSION PROFILING; INTEGRATED ANALYSIS;

GENE EXPRESSION;

EID: 84970976503     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1142/9789812838780_0004     Document Type: Chapter

References (54)

1. Edgar R, Domrachev M, Lash AE. (2002) Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res 30: 207-210.
2. Barrett T, Suzek TO, Troup DB et al. (2005) NCBI GEO: mining millions of expression profiles database and tools. Nucleic Acids Res 33: D562-566.
3. Parkinson H, Sarkans U, Shojatalab M et al. (2005) ArrayExpress a public repository for microarray gene expression data at the EBI. Nucleic Acids Res 33: D553-555.
4. Sutton AJ, Abrams KR, Jones DR et al. (2000) Methods for Meta-analysis in Medical Research. New York, NY: John Wiley &Sons.
5. Chalmers I. (1993) The Cochrane Collaboration: preparing, maintaining, anddisseminating systematic reviews of the effects of health care. Ann NY Acad Sci 703: 156-165.
6. Punt CJA, Buyse M, Köhne CH et al. (2007) Endpoints in adjuvant treatment trials: a systematic review of the literature in colon cancer and proposed definitions for future trials. J Natl Cancer Inst 99: 998-1003.
7. Hedges LV, Olkin I. (1985) Statistical Methods for Meta-analysis. New York, NY: Academic Press.
8. Altman DG, Deeks JJ. (2002) Meta-analysis, Simpson’s paradox and the number needed to treat. BMC Med Res Methodol 2: 3.
9. Benito M, Parker J, Du Q et al. (2004) Adjustment of systematic microarray data biases. Bioinformatics 20: 105 14.
10. Goldstein DR, Delorenzi M, Luthi-Carter R, Sengstag T. (2009) Meta-analysis of microarray studies. In: Guerra R, Goldstein DR (eds.). Meta-analysis and Combining Information in Genetics. Boca Raton, FL: Chapman-Hall/CRC Press.
11. Choi JK, Yu U, Kim S, Yoo OJ. (2003) Combining multiple microarray studies and modeling inter study variation. Bioinformatics 19(Suppl 1): i84–90.
12. Cooper HM, Hedges LV. (1994) The Handbook of Research Synthesis. New York, NY: Russell Sage Foundation.
13. Stevens JR, Doerge RW. (2005) Combining Affymetrix microarray results. BMC Bioinformatics 6: 57.
14. Grützmann R, Boriss H, Ammerpohl O et al. (2005) Meta-analysis of microarray data on pancreatic cancer defines a set of commonly dysregulated genes. Oncogene 24: 5079-5088.
15. Ghosh D, Barette TR, Rhodes D, Chinnaiyan AM. (2003) Statistical issues and methods for meta-analysis of microarray data: a case study in prostate cancer. Funct Integr Genomics 3: 180-188.
16. Kulinskaya E, Morgenthaler S, Staudte RG. (2008) A Guide to Calibrating and Combining Statistical Evidence. New York, NY: Wiley-Interscience.
17. Westfall PH, Young SS. (1993) Resampling-based Multiple Testing: Examples and Methods for p-Value Adjustment. New York, NY: Wiley.
18. Yekutieli D, Benjamini Y. (1999) Resampling-based false discovery rate controlling multiple test procedures for correlated test statistics. J Stat Plan Inference 82: 171-196.
19. Fisher RA. (1932) Statistical Methods for Research Workers, 4th ed. Oxford, UK: Oxford University Press.
20. Rhodes DR, Barrette TR, Rubin MA et al. (2002) Meta-analysis of microarrays: interstudy validation of gene expression profiles reveals pathway dysregulation in prostate cancer. Cancer Res 62: 4427-4433.
21. Wise LH, Lanchbury JS, Lewis CM. (1999) Meta-analysis of genome searches. Ann Hum Genet 63: 263-72.
22. Breitling R, Armengaud P, Amtmann A, Herzyk P. (2004) Rank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments. FEBS Lett 573: 83-92.
23. Cahan P, Ahmad AM, Burke H et al. (2005) List of lists-annotated (LOLA): a database for annotation and comparison of published microarray gene lists.Gene 360: 78-82.
24. Pirooznia M, Nagarajan V, Deng Y. (2007) GeneVenn a web application for comparing gene lists using Venn diagrams. Bioinformation 10: 420-422.
25. Wilkinson B. (1951) A statisical consideration in psychological research. Psychol Bull 48: 156-158.
26. Birnbaum A. (1954) Combining independent tests of significance. J Am Stat Assoc 49: 559-574.
27. Koziol JA, Perlman MD. (1978) Combining independent chi-squared tests. J Am Stat Assoc 73: 753-763.
28. McCullagh P, Nelder JA. (1989) Generalized Linear Models, 2nd ed. London, UK: Chapman &Hall.
29. Benjamini Y, Hochberg Y. (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B 57: 289-300.
30. van’t Veer LJ, Dai H, van de Vijver MJ et al. (2002) Gene expression profiling predicts clinical outcome of breast cancer. Nature 415: 530-536.
31. van de Vijver MJ, He YD, van’t Veer LJ et al. (2002) A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 347: 1999-2009.
32. Wang Y, Klijn JGM, Zhang Y et al. (2005) Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 365: 671-679.
33. Miller LD, Smeds J, George J et al. (2005) An expression signature for p53 status in human breast cancer predicts mutation status, transcriptional effects and patient survival. Proc Natl Acad Sci USA 102: 13550-13555.
34. Calza S, Hall P, Auer G et al. (2006) Intrinsic molecular signature of breast cancer in a population-based cohort of 412 patients. Breast Cancer Res 8: R34.
35. Pawitan Y, Bjöhle J, Amler L et al. (2005) Gene expression profiling spares early breast cancer patients from adjuvant therapy: derived and validated in two population-based cohorts. Breast Cancer Res 7: R953-964.
36. Huang E, Cheng SH, Dressman H et al. (2003) Gene expression predictors of breast cancer outcomes. Lancet 361: 1590-1596.
37. Bild AH, Yao G, Chang JT et al. (2006) Oncogenic pathway signatures in human cancers as a guide to targeted therapies. Nature 439: 353-357.
38. Korkola JE, DeVries S, Fridlyand J et al. (2003) Differentiation of lobular versus ductal breast carcinomas by expression microarray analysis. Cancer Res 63: 7167-7175.
39. Hu Z, Fan C, Oh DS et al. (2006) The molecular portraits of breast tumors are conserved across microarray platforms. BMC Genomics 7: 96.
40. Naderi A, Teschendorff AE, Barbosa-Morais NL et al. (2006) A gene-expression signature to predict survival in breast cancer across independent data sets. Oncogene 26: 1507-1516.
41. Sorlie T, Perou CM, Tibshirani R et al. (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA 98: 10869-10874.
42. Sorlie T, Tibshirani R, Parker J et al. (2003) Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci USA 100: 8418-8423.
43. Sotiriou C, Neo SY, McShane L et al. (2003) Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci USA 100: 10393-10398.
44. Sotiriou C, Wirapati P, Loi S et al. (2006) Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst 98: 262-272.
45. Ma XJ, Wang Z, Ryan PD et al. (2004) A two-gene expression ratio predicts clinical outcome in breast cancer patients treated with tamoxifen. Cancer Cell 5: 607-616.
46. Paik S, Shak S, Tang G et al. (2004) A multigene assay to predict recurrence of tamoxifentreated, node-negative breast cancer. N Engl J Med 351: 2817-2826.
47. Teschendorff AE, Naderi A, Barbosa-Morais NL et al. (2006) A consensus prognostic gene expression classifier for ER positive breast cancer. Genome Biol 7: R101.
48. Chang HY, Sneddon JB, Alizadeh AA et al. (2004) Gene expression signature of fibroblast serum response predicts human cancer progression similarities between tumors and wounds. PLoS Biol 2: 206-214.
49. Liu R, Wang X, Chen GY et al. (2007) The prognostic role of a gene signature from tumorigenic breast-cancer cells. New Engl J Med 356: 217-226.
50. Whitfield ML, Sherlock G, Saldanha AJ et al. (2002) Identification of genes periodically expressed in the human cell cycle and their expression in tumors. Mol Biol Cell 13: 1977-2000.
51. Maglott D, Ostell J, Pruitt KD, Tatusova T. (2005) Entrez Gene: genecentered information at NCBI. Nucleic Acids Res 33: D53-8.
52. Chang HY, Nuyten DSA, Sneddon JB et al. (2005) Robustness, scalability and integration of wound-response gene expression signature in predicting breast cancer survival. Proc Natl Acad Sci USA 102: 3738-3743.
53. Esteva FJ, Hortobagyi GN. (2004) Prognostic molecular markers in early breast cancer. Breast Cancer Res 6: 109-118.
54. Hartung J. (1999) A note on combining dependent tests of significance. Biom J 41: 849-855.