In:
Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 18, No. 5 ( 2012-03-01), p. 1374-1385
Abstract:
Purpose: High-grade serous ovarian cancers are heterogeneous not only in terms of clinical outcome but also at the molecular level. Our aim was to establish a novel risk classification system based on a gene expression signature for predicting overall survival, leading to suggesting novel therapeutic strategies for high-risk patients. Experimental Design: In this large-scale cross-platform study of six microarray data sets consisting of 1,054 ovarian cancer patients, we developed a gene expression signature for predicting overall survival by applying elastic net and 10-fold cross-validation to a Japanese data set A (n = 260) and evaluated the signature in five other data sets. Subsequently, we investigated differences in the biological characteristics between high- and low-risk ovarian cancer groups. Results: An elastic net analysis identified a 126-gene expression signature for predicting overall survival in patients with ovarian cancer using the Japanese data set A (multivariate analysis, P = 4 × 10−20). We validated its predictive ability with five other data sets using multivariate analysis (Tothill's data set, P = 1 × 10−5; Bonome's data set, P = 0.0033; Dressman's data set, P = 0.0016; TCGA data set, P = 0.0027; Japanese data set B, P = 0.021). Through gene ontology and pathway analyses, we identified a significant reduction in expression of immune-response–related genes, especially on the antigen presentation pathway, in high-risk ovarian cancer patients. Conclusions: This risk classification based on the 126-gene expression signature is an accurate predictor of clinical outcome in patients with advanced stage high-grade serous ovarian cancer and has the potential to develop new therapeutic strategies for high-grade serous ovarian cancer patients. Clin Cancer Res; 18(5); 1374–85. ©2012 AACR.
Type of Medium:
Online Resource
ISSN:
1078-0432
,
1557-3265
DOI:
10.1158/1078-0432.CCR-11-2725
Language:
English
Publisher:
American Association for Cancer Research (AACR)
Publication Date:
2012
detail.hit.zdb_id:
1225457-5
detail.hit.zdb_id:
2036787-9
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