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Breast Cancer Research

Erschienen in:

01.06.2005 | Commentary

Microarrays and breast cancer clinical studies: forgetting what we have not yet learnt

verfasst von: Ahmed Ashour Ahmed, James D Brenton

Erschienen in: Breast Cancer Research | Ausgabe 3/2005

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Abstract

This review takes a sceptical view of the impact of breast cancer studies that have used microarrays to identify predictors of clinical outcome. In addition to discussing general pitfalls of microarray experiments, we also critically review the key breast cancer studies to highlight methodological problems in cohort selection, statistical analysis, validation of results and reporting of raw data. We conclude that the optimum use of microarrays in clinical studies requires further optimisation and standardisation of methodology and reporting, together with improvements in clinical study design.

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Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, Hastie T, Eisen MB, van de Rijn M, Jeffrey SS, et al: Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA. 2001, 98: 10869-10874. 10.1073/pnas.191367098.CrossRefPubMedPubMedCentral

van 't Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M, Peterse HL, van der Kooy K, Marton MJ, Witteveen AT, et al: Gene expression profiling predicts clinical outcome of breast cancer. Nature. 2002, 415: 530-536. 10.1038/415530a.CrossRefPubMed

van de Vijver MJ, He YD, van 't Veer LJ, Dai H, Hart AA, Voskuil DW, Schreiber GJ, Peterse JL, Roberts C, Marton MJ, et al: A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med. 2002, 347: 1999-2009. 10.1056/NEJMoa021967.CrossRefPubMed

Ahr A, Karn T, Solbach C, Seiter T, Strebhardt K, Holtrich U, Kaufmann M: Identification of high risk breast-cancer patients by gene expression profiling. Lancet. 2002, 359: 131-132. 10.1016/S0140-6736(02)07337-3.CrossRefPubMed

Chang JC, Wooten EC, Tsimelzon A, Hilsenbeck SG, Gutierrez MC, Elledge R, Mohsin S, Osborne CK, Chamness GC, Allred DC, et al: Gene expression profiling for the prediction of therapeutic response to docetaxel in patients with breast cancer. Lancet. 2003, 362: 362-369. 10.1016/S0140-6736(03)14023-8.CrossRefPubMed

Sotiriou C, Neo SY, McShane LM, Korn EL, Long PM, Jazaeri A, Martiat P, Fox SB, Harris AL, Liu ET: Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci USA. 2003, 100: 10393-10398. 10.1073/pnas.1732912100.CrossRefPubMedPubMedCentral

Huang E, Cheng SH, Dressman H, Pittman J, Tsou MH, Horng CF, Bild A, Iversen ES, Liao M, Chen CM, et al: Gene expression predictors of breast cancer outcomes. Lancet. 2003, 361: 1590-1596. 10.1016/S0140-6736(03)13308-9.CrossRefPubMed

Liu ET, Karuturi KR: Microarrays and clinical investigations. N Engl J Med. 2004, 350: 1595-1597. 10.1056/NEJMp048050.CrossRefPubMed

Wang E, Miller LD, Ohnmacht GA, Liu ET, Marincola FM: High-fidelity mRNA amplification for gene profiling. Nat Biotechnol. 2000, 18: 457-459. 10.1038/74546.CrossRefPubMed

10.

Perou CM, Jeffrey SS, van de Rijn M, Rees CA, Eisen MB, Ross DT, Pergamenschikov A, Williams CF, Zhu SX, Lee JC, et al: Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. Proc Natl Acad Sci USA. 1999, 96: 9212-9217. 10.1073/pnas.96.16.9212.CrossRefPubMedPubMedCentral

11.

Hu L, Wang J, Baggerly K, Wang H, Fuller GN, Hamilton SR, Coombes KR, Zhang W: Obtaining reliable information from minute amounts of RNA using cDNA microarrays. BMC Genomics. 2002, 3: 16-10.1186/1471-2164-3-16.CrossRefPubMedPubMedCentral

12.

't Hoen PA, de Kort F, van Ommen GJ, den Dunnen JT: Fluorescent labelling of cRNA for microarray applications. Nucleic Acids Res. 2003, 31: e20-10.1093/nar/gng020.CrossRefPubMedPubMedCentral

13.

Naderi A, Ahmed AA, Barbosa-Morais NL, Aparicio S, Brenton JD, Caldas C: Expression microarray reproducibility is improved by optimising purification steps in RNA amplification and labelling. BMC Genomics. 2004, 5: 9-10.1186/1471-2164-5-9.CrossRefPubMedPubMedCentral

14.

Hughes TR, Mao M, Jones AR, Burchard J, Marton MJ, Shannon KW, Lefkowitz SM, Ziman M, Schelter JM, Meyer MR, et al: Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer. Nat Biotechnol. 2001, 19: 342-347. 10.1038/86730.CrossRefPubMed

15.

Taylor S, Smith S, Windle B, Guiseppi-Elie A: Impact of surface chemistry and blocking strategies on DNA microarrays. Nucleic Acids Res. 2003, 31: e87-10.1093/nar/gng086.CrossRefPubMedPubMedCentral

16.

Lee JK, Bussey KJ, Gwadry FG, Reinhold W, Riddick G, Pelletier SL, Nishizuka S, Szakacs G, Annereau JP, Shankavaram U, et al: Comparing cDNA and oligonucleotide array data: concordance of gene expression across platforms for the NCI-60 cancer cells. Genome Biol. 2003, 4: R82-10.1186/gb-2003-4-12-r82.CrossRefPubMedPubMedCentral

17.

Zorn KK, Jazaeri AA, Awtrey CS, Gardner GJ, Mok SC, Boyd J, Birrer MJ: Choice of normal ovarian control influences determination of differentially expressed genes in ovarian cancer expression profiling studies. Clin Cancer Res. 2003, 9: 4811-4818.PubMed

18.

Ahmed AA, Vias M, Iyer NG, Caldas C, Brenton JD: Microarray segmentation methods significantly influence data precision. Nucleic Acids Res. 2004, 32: e50-10.1093/nar/gnh047.CrossRefPubMedPubMedCentral

19.

Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, Aach J, Ansorge W, Ball CA, Causton HC, et al: Minimum information about a microarray experiment (MIAME) -toward standards for microarray data. Nat Genet. 2001, 29: 365-371. 10.1038/ng1201-365.CrossRefPubMed

20.

Park PJ, Cao YA, Lee SY, Kim JW, Chang MS, Hart R, Choi S: Current issues for DNA microarrays: platform comparison, double linear amplification, and universal RNA reference. J Biotechnol. 2004, 112: 225-245. 10.1016/j.jbiotec.2004.05.006.CrossRefPubMed

21.

Tan PK, Downey TJ, Spitznagel EL, Xu P, Fu D, Dimitrov DS, Lempicki RA, Raaka BM, Cam MC: Evaluation of gene expression measurements from commercial microarray platforms. Nucleic Acids Res. 2003, 31: 5676-5684. 10.1093/nar/gkg763.CrossRefPubMedPubMedCentral

22.

Tumor Analysis Best Practices Working Group: Expression profiling – best practices for data generation and interpretation in clinical trials. Nat Rev Genet. 2004, 5: 229-237.CrossRef

23.

Altman DG: Systematic reviews of evaluations of prognostic variables. BMJ. 2001, 323: 224-228. 10.1136/bmj.323.7306.224.CrossRefPubMedPubMedCentral

24.

Riley RD, Abrams KR, Sutton AJ, Lambert PC, Jones DR, Heney D, Burchill SA: Reporting of prognostic markers: current problems and development of guidelines for evidence-based practice in the future. Br J Cancer. 2003, 88: 1191-1198. 10.1038/sj.bjc.6600886.CrossRefPubMedPubMedCentral

25.

Chollet P, Amat S, Cure H, de Latour M, Le Bouedec G, Mouret-Reynier MA, Ferriere JP, Achard JL, Dauplat J, Penault-Llorca F: Prognostic significance of a complete pathological response after induction chemotherapy in operable breast cancer. Br J Cancer. 2002, 86: 1041-1046. 10.1038/sj.bjc.6600210.CrossRefPubMedPubMedCentral

26.

Simon R: Diagnostic and prognostic prediction using gene expression profiles in high-dimensional microarray data. Br J Cancer. 2003, 89: 1599-1604. 10.1038/sj.bjc.6601326.CrossRefPubMedPubMedCentral

27.

Simon R: When is a genomic classifier ready for prime time?. Nat Clin Pract Oncol. 2004, 1: 4-5. 10.1038/ncponc0006.CrossRefPubMed

28.

Tibshirani RJ, Effron B: Pre-validation and inference in microarrays. Statist Applic Genet Mol Biol. 2002, 1 (1): article 1

29.

Ihaka R, Gentleman R: R: a language for data analysis and graphics. J Comput Graph Stat. 1996, 5: 299-314.

30.

Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, et al: Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 2004, 5: R80-10.1186/gb-2004-5-10-r80.CrossRefPubMedPubMedCentral

31.

Ruschhaupt M, Huber W, Poustka A, Mansmann U: A compendium to ensure computational reproducibility in high-dimensional classification tasks. Statist Applic Genet Mol Biol. 2004, 3: article 37

Titel: Microarrays and breast cancer clinical studies: forgetting what we have not yet learnt
verfasst von: Ahmed Ashour Ahmed
James D Brenton
Publikationsdatum: 01.06.2005
Verlag: BioMed Central
Erschienen in: Breast Cancer Research / Ausgabe 3/2005
Elektronische ISSN: 1465-542X
DOI: https://doi.org/10.1186/bcr1017

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Microarrays and breast cancer clinical studies: forgetting what we have not yet learnt

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