Alessandra Gennari1, Mariapia Sormani2, Matteo Puntoni3, Veronica Martini1, Adriana Amaro4, Paolo Bruzzi5, Ulrich Pfeffer4. 1. Division of Oncology, Department of Translational Medicine, University of Eastern Piedmont, Novara, Italy. 2. DISSAL, University of Genoa, Genoa, Italy. 3. Clinical Trial Unit, Galliera Hospital Genoa, Genoa, Italy. 4. Tumor Epigenetics, IRCCS Ospedale Policlinico San Martino, Genoa, Italy. 5. Clinical Epidemiology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.
Abstract
INTRODUCTION: Insulin and the insulin-like growth factor (IGF) family play a key role in breast cancer (BC). OBJECTIVE: In this study, we evaluated on a genomic scale the potential prognostic value of insulin signaling in early BC. METHODS: Candidate genes were selected from the published literature and gene expression profiling experiments. Three publicly available BC datasets, containing gene expression data on 502 cases, were used to test the prognostic ability of the score. The gene signature was developed on GSE1456, containing microarray data from 159 patients, split into a training set (102 breast tumors) and a validation set (n = 57). GSE3494 and GSE2990 (350 patients) were used for external validation. Univariate Mann-Whitney test was used to identify genes differentially expressed between relapsed and nonrelapsed patients. Expression of genes significantly correlated with relapse was combined in a linear score. Patients were classified as low or high risk with respect to the median value. RESULTS: On the training set, 15 genes turned out to be differentially expressed: 8-year disease-free survival (DFS) was 51 and 91% in the high- and low-risk group (p < 0.001), respectively. In the validation set, DFS was 97 and 54% (p = 0.009), respectively. External validation: 8-year DFS was 72 and 61%, respectively, in GSE3494 (p = 0.03) and 74 and 55% in GSE2990 (p = 0.03). By multivariate analyses, the insulin signature was significantly associated with DFS, independently of age, hormone receptor status, nodal status, and grade. CONCLUSIONS: Our findings indicate that the insulin pathway is involved in BC prognosis at a genomic level and provide a window of selectivity for preventive and treatment strategies targeting the insulin/IGF pathway in BC patients.
INTRODUCTION: Insulin and the insulin-like growth factor (IGF) family play a key role in breast cancer (BC). OBJECTIVE: In this study, we evaluated on a genomic scale the potential prognostic value of insulin signaling in early BC. METHODS: Candidate genes were selected from the published literature and gene expression profiling experiments. Three publicly available BC datasets, containing gene expression data on 502 cases, were used to test the prognostic ability of the score. The gene signature was developed on GSE1456, containing microarray data from 159 patients, split into a training set (102 breast tumors) and a validation set (n = 57). GSE3494 and GSE2990 (350 patients) were used for external validation. Univariate Mann-Whitney test was used to identify genes differentially expressed between relapsed and nonrelapsed patients. Expression of genes significantly correlated with relapse was combined in a linear score. Patients were classified as low or high risk with respect to the median value. RESULTS: On the training set, 15 genes turned out to be differentially expressed: 8-year disease-free survival (DFS) was 51 and 91% in the high- and low-risk group (p < 0.001), respectively. In the validation set, DFS was 97 and 54% (p = 0.009), respectively. External validation: 8-year DFS was 72 and 61%, respectively, in GSE3494 (p = 0.03) and 74 and 55% in GSE2990 (p = 0.03). By multivariate analyses, the insulin signature was significantly associated with DFS, independently of age, hormone receptor status, nodal status, and grade. CONCLUSIONS: Our findings indicate that the insulin pathway is involved in BC prognosis at a genomic level and provide a window of selectivity for preventive and treatment strategies targeting the insulin/IGF pathway in BC patients.
Authors: O Nanni; D Amadori; A De Censi; A Rocca; A Freschi; A Bologna; L Gianni; F Rosetti; L Amaducci; L Cavanna; F Foca; S Sarti; P Serra; L Valmorri; P Bruzzi; D Corradengo; A Gennari Journal: Breast Cancer Res Treat Date: 2018-12-07 Impact factor: 4.872
Authors: Marilyn J Borugian; Samuel B Sheps; Charmaine Kim-Sing; Cheri Van Patten; John D Potter; Bruce Dunn; Richard P Gallagher; T Gregory Hislop Journal: Cancer Epidemiol Biomarkers Prev Date: 2004-07 Impact factor: 4.254
Authors: Jennifer A Ligibel; Nancy Campbell; Ann Partridge; Wendy Y Chen; Taylor Salinardi; Haiyan Chen; Kristie Adloff; Aparna Keshaviah; Eric P Winer Journal: J Clin Oncol Date: 2008-02-20 Impact factor: 44.544