High-Risk Ovarian Cancer Based on 126-Gene Expression Signature Is Uniquely Characterized by Downregulation of Antigen Presentation Pathway

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 ¼ 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 ¼ 4 Â 10 À20 ). We validated its predictive ability with five other data sets using multivariate analysis (Tothill's data set, P ¼ 1 Â 10 À5 ; Bonome's data set, P ¼ 0.0033; Dressman's data set, P ¼ 0.0016; TCGA data set, P ¼ 0.0027; Japanese data set B, P ¼ 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.

Immunological metagene signatures derived from immunogenic cancer cell death associate with improved survival of patients with lung, breast or ovarian malignancies: A large-scale meta-analysis

“…first a MAS5 algorithm-based normalization on individual-chip level and a second scaling normalization to set the average expression on each chip to 1,000. 39 For the 'validation dataset' analysis, the cohorts consisting of >250 patients each for breast cancer (n D 285; GSE2034), 53 non-small cell lung cancer (n D 274; GSE41271) 54,55 and ovarian cancer (n D 259; GSE32062) 56 were analyzed as described above, using the PROGgeneV2 platform. 57 The available clinicopathological characteristics of the patients in these respective 'validation' cohorts are described in Table S2.…”

Expression Profiles of Loneliness-associated Genes for Survival Prediction in Cancer Patients

“…(Yoshino et al, 2011) Microarray datasets have also been widely used in discovering tumor types and tumor progression by comparing different stages of tumors (Privette Vinnedge et al, 2011;Yeoh et al, 2010). Moreover, some studies developed a gene expression signature for predicting overall survival of lung cancer with microarray data sets (Yoshihara et al, 2012).…”

Gene-expression signatures in ovarian cancer: Promise and challenges for patient stratification

“…Many early generation ovarian cancer gene expression profiling studies focused primarily on the prognostic value of gene expression signatures. Results of these early prognostic gene expression studies [6][7][8][9][10][11][12][13][14] and those following [15][16][17][18][19][20][21][22][23][24][25] are summarized in Table 1 (Table 1). Most of these studies have identified a group of prognostically relevant genes in relatively small training sets but did, to their credit, validate the prognostic relevance of the respective gene signatures in independent cohorts.…”

“…The ovarian cancer analysis showed a wide range of accuracy of published prognostic models and signatures. The top-ranked three models were those of the TCGA consortium [18,23], a signature by Yoshihara et al [20] and one by Bonome et al (optimally debulked patients) [10]. These achieved summary C-indices between 0.57 and 0.60.…”