The Gene Expression Grade Index: A Potential Predictor of Relapse for Endocrine-treated Breast Cancer Patients in the BIG 1–98 Trial

DSpace/Manakin Repository

The Gene Expression Grade Index: A Potential Predictor of Relapse for Endocrine-treated Breast Cancer Patients in the BIG 1–98 Trial

Show simple item record

dc.contributor.author Desmedt, Christine
dc.contributor.author Giobbie-Hurder, Anita
dc.contributor.author Neven, Patrick
dc.contributor.author Paridaens, Robert
dc.contributor.author Christiaens, Marie-Rose
dc.contributor.author Smeets, Ann
dc.contributor.author Lallemand, Françoise
dc.contributor.author Viale, Giuseppe
dc.contributor.author Piccart, Martine
dc.contributor.author Sotiriou, Christos
dc.contributor.author Haibe-Kains, Benjamin
dc.contributor.author Gelber, Richard David
dc.date.accessioned 2012-02-09T20:33:45Z
dc.date.issued 2009
dc.identifier.citation Desmedt, Christine, Anita Giobbie-Hurder, Patrick Neven, Robert Paridaens, Marie-Rose Christiaens, Ann Smeets, Françoise Lallemand, et al. 2009. The Gene expression Grade Index: a potential predictor of relapse for endocrine-treated breast cancer patients in the BIG 1–98 trial. BMC Medical Genomics 2: 40. en_US
dc.identifier.issn 1755-8794 en_US
dc.identifier.uri http://nrs.harvard.edu/urn-3:HUL.InstRepos:8148897
dc.description.abstract Background: We have previously shown that the Gene expression Grade Index (GGI) was able to identify two subtypes of estrogen receptor (ER)-positive tumors that were associated with statistically distinct clinical outcomes in both untreated and tamoxifen-treated patients. Here, we aim to investigate the ability of the GGI to predict relapses in postmenopausal women who were treated with tamoxifen (T) or letrozole (L) within the BIG 1–98 trial. Methods: We generated gene expression profiles (Affymetrix) and computed the GGI for a matched, case-control sample of patients enrolled in the BIG 1–98 trial from the two hospitals where frozen samples were available. All relapses (cases) were identified from patients randomized to receive monotherapy or from the switching treatment arms for whom relapse occurred before the switch. Each case was randomly matched with four controls based upon nodal status and treatment (T or L). The prognostic value of GGI was assessed as a continuous predictor and divided at the median. Predictive accuracy of GGI was estimated using time-dependent area under the curve (AUC) of the ROC curves. Results: Frozen samples were analyzable for 48 patients (10 cases and 38 controls). Seven of the 10 cases had been assigned to receive L. Cases and controls were comparable with respect to menopausal and nodal status, local and chemotherapy, and HER2 positivity. Cases were slightly older than controls and had a larger proportion of large, poorly differentiated ER+/PgR- tumors. The GGI was significantly and linearly related to risk of relapse: each 10-unit increase in GGI resulted in an increase of approximately 11% in the hazard rate (p = 0.02). Within the subgroups of patients with node-positive disease or who were treated with L, the hazard of relapse was significantly greater for patients with GGI at or above the median. AUC reached a maximum of 78% at 27 months. Conclusion: This analysis supports the GGI as a good predictor of relapse for ER-positive patients, even among patients who receive L. Validation of these results, in a larger series from BIG 1–98, is planned using the simplified GGI represented by a smaller set of genes and tested by qRT-PCR on paraffin-embedded tissues. en_US
dc.language.iso en_US en_US
dc.publisher BioMed Central en_US
dc.relation.isversionof doi://10.1186/1755-8794-2-40 en_US
dc.relation.hasversion http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2713270/pdf/ en_US
dash.license LAA
dc.title The Gene Expression Grade Index: A Potential Predictor of Relapse for Endocrine-treated Breast Cancer Patients in the BIG 1–98 Trial en_US
dc.type Journal Article en_US
dc.description.version Version of Record en_US
dc.relation.journal BMC Medical Genomics en_US
dash.depositing.author Haibe-Kains, Benjamin
dc.date.available 2012-02-09T20:33:45Z
dash.affiliation.other SPH^Biostatistics en_US
dash.affiliation.other HMS^Pediatrics-Children's Hospital en_US

Files in this item

Files Size Format View
2713270.pdf 269.2Kb PDF View/Open

This item appears in the following Collection(s)

Show simple item record

 
 

Search DASH


Advanced Search
 
 

Submitters