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Published in: Breast Cancer Research 6/2008

01-12-2008 | Editorial

Approaches towards expression profiling the response to treatment

Authors: Andrew H Sims, John MS Bartlett

Published in: Breast Cancer Research | Issue 6/2008

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Abstract

Over the past 8 years there has been a wealth of breast cancer gene expression studies. The majority of these studies have focused upon characterising a tumour at presentation, before treatment, rather than looking at the effects of treatment on the tumour. More recently, a number of groups have moved from predicting prognosis based upon long-term follow-up to alternative approaches of using expression profiling to measure the effect of treatment on breast tumours and potentially predict response to therapy using either post-treatment samples or both pre-treatment and post-treatment samples. Whilst this provides great potential to further our understanding of the mode of action of treatments and to more accurately select which patients will benefit from a particular treatment, serious issues of experimental design must be considered.
Literature
1.
go back to reference Vendrell JA, Robertson KE, Ravel P, Bray SE, Bajard A, Purdie CA, Nguyen C, Hadad SM, Bieche I, Chabaud S, Bachelot T, Thompson AM, Cohen PA: A candidate molecular signature associated with tamoxifen failure in primary breast cancer. Breast Cancer Res. 2008, 10: R88-10.1186/bcr2158.CrossRefPubMedPubMedCentral Vendrell JA, Robertson KE, Ravel P, Bray SE, Bajard A, Purdie CA, Nguyen C, Hadad SM, Bieche I, Chabaud S, Bachelot T, Thompson AM, Cohen PA: A candidate molecular signature associated with tamoxifen failure in primary breast cancer. Breast Cancer Res. 2008, 10: R88-10.1186/bcr2158.CrossRefPubMedPubMedCentral
2.
go back to reference Mackay A, Urruticoechea A, Dixon JM, Dexter T, Fenwick K, Ashworth A, Drury S, Larionov A, Young O, White S, Miller WR, Evans DB, Dowsett M: Molecular response to aromatase inhibitor treatment in primary breast cancer. Breast Cancer Res. 2007, 9: R37-10.1186/bcr1732.CrossRefPubMedPubMedCentral Mackay A, Urruticoechea A, Dixon JM, Dexter T, Fenwick K, Ashworth A, Drury S, Larionov A, Young O, White S, Miller WR, Evans DB, Dowsett M: Molecular response to aromatase inhibitor treatment in primary breast cancer. Breast Cancer Res. 2007, 9: R37-10.1186/bcr1732.CrossRefPubMedPubMedCentral
3.
go back to reference Harvell DM, Spoelstra NS, Singh M, McManaman JL, Finlayson C, Phang T, Trapp S, Hunter L, Dye WW, Borges VF, Elias A, Horwitz KB, Richer JK: Molecular signatures of neoadjuvant endocrine therapy for breast cancer: characteristics of response or intrinsic resistance. Breast Cancer Res Treat. 2008, 112: 475-488. 10.1007/s10549-008-9897-4.CrossRefPubMed Harvell DM, Spoelstra NS, Singh M, McManaman JL, Finlayson C, Phang T, Trapp S, Hunter L, Dye WW, Borges VF, Elias A, Horwitz KB, Richer JK: Molecular signatures of neoadjuvant endocrine therapy for breast cancer: characteristics of response or intrinsic resistance. Breast Cancer Res Treat. 2008, 112: 475-488. 10.1007/s10549-008-9897-4.CrossRefPubMed
4.
go back to reference Miller WR, Larionov A, Anderson TJ, Walker JR, Krause A, Evans DB, Dixon JM: Predicting response and resistance to endocrine therapy: profiling patients on aromatase inhibitors. Cancer. 2008, 112 (3 Suppl): 689-694. 10.1002/cncr.23187.CrossRefPubMed Miller WR, Larionov A, Anderson TJ, Walker JR, Krause A, Evans DB, Dixon JM: Predicting response and resistance to endocrine therapy: profiling patients on aromatase inhibitors. Cancer. 2008, 112 (3 Suppl): 689-694. 10.1002/cncr.23187.CrossRefPubMed
5.
go back to reference Bonnefoi H, Potti A, Delorenzi M, Mauriac L, Campone M, Tubiana-Hulin M, Petit T, Rouanet P, Jassem J, Blot E, Becette V, Farmer P, Andre S, Acharya CR, Mukherjee S, Cameron D, Bergh J, Nevins JR, Iggo RD: Validation of gene signatures that predict the response of breast cancer to neoadjuvant chemotherapy: a substudy of the EORTC 10994/BIG 00-01 clinical trial. Lancet Oncol. 2007, 8: 1071-1078. 10.1016/S1470-2045(07)70345-5.CrossRefPubMed Bonnefoi H, Potti A, Delorenzi M, Mauriac L, Campone M, Tubiana-Hulin M, Petit T, Rouanet P, Jassem J, Blot E, Becette V, Farmer P, Andre S, Acharya CR, Mukherjee S, Cameron D, Bergh J, Nevins JR, Iggo RD: Validation of gene signatures that predict the response of breast cancer to neoadjuvant chemotherapy: a substudy of the EORTC 10994/BIG 00-01 clinical trial. Lancet Oncol. 2007, 8: 1071-1078. 10.1016/S1470-2045(07)70345-5.CrossRefPubMed
6.
go back to reference 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: R101-10.1186/gb-2006-7-10-r101.CrossRefPubMedPubMedCentral 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: R101-10.1186/gb-2006-7-10-r101.CrossRefPubMedPubMedCentral
7.
go back to reference 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: 94-10.1186/1471-2164-5-94.CrossRefPubMedPubMedCentral 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: 94-10.1186/1471-2164-5-94.CrossRefPubMedPubMedCentral
8.
go back to reference Acharya CR, Hsu DS, Anders CK, Anguiano A, Salter KH, Walters KS, Redman RC, Tuchman SA, Moylan CA, Mukherjee S, Barry WT, Dressman HK, Ginsburg GS, Marcom KP, Garman KS, Lyman GH, Nevins JR, Potti A: Gene expression signatures, clinicopathological features, and individualized therapy in breast cancer. JAMA. 2008, 299: 1574-1587. 10.1001/jama.299.13.1574.CrossRefPubMed Acharya CR, Hsu DS, Anders CK, Anguiano A, Salter KH, Walters KS, Redman RC, Tuchman SA, Moylan CA, Mukherjee S, Barry WT, Dressman HK, Ginsburg GS, Marcom KP, Garman KS, Lyman GH, Nevins JR, Potti A: Gene expression signatures, clinicopathological features, and individualized therapy in breast cancer. JAMA. 2008, 299: 1574-1587. 10.1001/jama.299.13.1574.CrossRefPubMed
9.
go back to reference Sims AH, Ong KR, Clarke RB, Howell A: 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: 214-10.1186/bcr1605.CrossRefPubMedPubMedCentral Sims AH, Ong KR, Clarke RB, Howell A: 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: 214-10.1186/bcr1605.CrossRefPubMedPubMedCentral
10.
go back to reference Habibi G, Leung S, Law JH, Gelmon K, Masoudi H, Turbin D, Pollak M, Nielsen TO, Huntsman D, Dunn SE: Re-defining prognostic factors for breast cancer: YB-1 is a stronger predictor of relapse and disease specific survival than estrogen receptor or HER-2 across all tumor subtypes. Breast Cancer Res. 2008, 10: R86-10.1186/bcr2156.CrossRefPubMedPubMedCentral Habibi G, Leung S, Law JH, Gelmon K, Masoudi H, Turbin D, Pollak M, Nielsen TO, Huntsman D, Dunn SE: Re-defining prognostic factors for breast cancer: YB-1 is a stronger predictor of relapse and disease specific survival than estrogen receptor or HER-2 across all tumor subtypes. Breast Cancer Res. 2008, 10: R86-10.1186/bcr2156.CrossRefPubMedPubMedCentral
11.
go back to reference 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. 10.1056/NEJMoa052933.CrossRefPubMed 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. 10.1056/NEJMoa052933.CrossRefPubMed
Metadata
Title
Approaches towards expression profiling the response to treatment
Authors
Andrew H Sims
John MS Bartlett
Publication date
01-12-2008
Publisher
BioMed Central
Published in
Breast Cancer Research / Issue 6/2008
Electronic ISSN: 1465-542X
DOI
https://doi.org/10.1186/bcr2196

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