The Gene expression Grade Index: A potential predictor of relapse for endocrine-treated breast cancer patients in the BIG 198 trial

Christine Desmedt, Anita Giobbie-Hurder, Patrick Neven, Robert Paridaens, Marie Rose Christiaens, Ann Smeets, Françoise Lallemand, Benjamin Haibe-Kains, Giuseppe Viale, Richard D. Gelber, Martine Piccart, Christos Sotiriou

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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 198 trial. Methods. We generated gene expression profiles (Affymetrix) and computed the GGI for a matched, case-control sample of patients enrolled in the BIG 198 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 198, is planned using the simplified GGI represented by a smaller set of genes and tested by qRT-PCR on paraffin-embedded tissues.

Original languageEnglish
Article number40
JournalBMC Medical Genomics
Volume2
DOIs
Publication statusPublished - 2009

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Breast Neoplasms
Gene Expression
Recurrence
Estrogen Receptors
letrozole
Tamoxifen
Area Under Curve
Transcriptome
ROC Curve
Paraffin
Neoplasms
Drug Therapy
Polymerase Chain Reaction
Therapeutics
Genes

ASJC Scopus subject areas

  • Genetics(clinical)
  • Genetics

Cite this

Desmedt, C., Giobbie-Hurder, A., Neven, P., Paridaens, R., Christiaens, M. R., Smeets, A., ... Sotiriou, C. (2009). The Gene expression Grade Index: A potential predictor of relapse for endocrine-treated breast cancer patients in the BIG 198 trial. BMC Medical Genomics, 2, [40]. https://doi.org/10.1186/1755-8794-2-40

The Gene expression Grade Index : A potential predictor of relapse for endocrine-treated breast cancer patients in the BIG 198 trial. / Desmedt, Christine; Giobbie-Hurder, Anita; Neven, Patrick; Paridaens, Robert; Christiaens, Marie Rose; Smeets, Ann; Lallemand, Françoise; Haibe-Kains, Benjamin; Viale, Giuseppe; Gelber, Richard D.; Piccart, Martine; Sotiriou, Christos.

In: BMC Medical Genomics, Vol. 2, 40, 2009.

Research output: Contribution to journalArticle

Desmedt, C, Giobbie-Hurder, A, Neven, P, Paridaens, R, Christiaens, MR, Smeets, A, Lallemand, F, Haibe-Kains, B, Viale, G, Gelber, RD, Piccart, M & Sotiriou, C 2009, 'The Gene expression Grade Index: A potential predictor of relapse for endocrine-treated breast cancer patients in the BIG 198 trial', BMC Medical Genomics, vol. 2, 40. https://doi.org/10.1186/1755-8794-2-40
Desmedt, Christine ; Giobbie-Hurder, Anita ; Neven, Patrick ; Paridaens, Robert ; Christiaens, Marie Rose ; Smeets, Ann ; Lallemand, Françoise ; Haibe-Kains, Benjamin ; Viale, Giuseppe ; Gelber, Richard D. ; Piccart, Martine ; Sotiriou, Christos. / The Gene expression Grade Index : A potential predictor of relapse for endocrine-treated breast cancer patients in the BIG 198 trial. In: BMC Medical Genomics. 2009 ; Vol. 2.
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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 198 trial. Methods. We generated gene expression profiles (Affymetrix) and computed the GGI for a matched, case-control sample of patients enrolled in the BIG 198 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 198, is planned using the simplified GGI represented by a smaller set of genes and tested by qRT-PCR on paraffin-embedded tissues.",
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AU - Neven, Patrick

AU - Paridaens, Robert

AU - Christiaens, Marie Rose

AU - Smeets, Ann

AU - Lallemand, Françoise

AU - Haibe-Kains, Benjamin

AU - Viale, Giuseppe

AU - Gelber, Richard D.

AU - Piccart, Martine

AU - Sotiriou, Christos

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N2 - 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 198 trial. Methods. We generated gene expression profiles (Affymetrix) and computed the GGI for a matched, case-control sample of patients enrolled in the BIG 198 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 198, is planned using the simplified GGI represented by a smaller set of genes and tested by qRT-PCR on paraffin-embedded tissues.

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