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

Yoshihara, Kosuke; Tsunoda, Tatsuhiko; Shigemizu, Daichi; Fujiwara, Hiroyuki; Hatae, Masayuki; Fujiwara, Hisaya; Masuzaki, Hideaki; Katabuchi, Hidetaka; Kawakami, Yosuke; Okamoto, Aikou; Nogawa, Takayoshi; Matsumura, Noriomi; Udagawa, Yasuhiro; Saito, Tsuyoshi; Itamochi, Hiroaki; Takano, Masashi; Miyagi, Etsuko; Sudo, Tamotsu; Ushijima, Kimio; Iwase, Haruko; Seki, Hiroyuki; Terao, Yasuhisa; Enomoto, Takayuki; Mikami, Mikio; Akazawa, Kohei; Tsuda, Hitoshi; Moriya, Takuya; Tajima, Atsushi; Inoue, Ituro; Tanaka, Kenichi

doi:10.1158/1078-0432.22444916.v1

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

journal contribution

posted on 2023-03-31, 16:53 authored by Kosuke Yoshihara, Tatsuhiko Tsunoda, Daichi Shigemizu, Hiroyuki Fujiwara, Masayuki Hatae, Hisaya Fujiwara, Hideaki Masuzaki, Hidetaka Katabuchi, Yosuke Kawakami, Aikou Okamoto, Takayoshi Nogawa, Noriomi Matsumura, Yasuhiro Udagawa, Tsuyoshi Saito, Hiroaki Itamochi, Masashi Takano, Etsuko Miyagi, Tamotsu Sudo, Kimio Ushijima, Haruko Iwase, Hiroyuki Seki, Yasuhisa Terao, Takayuki Enomoto, Mikio Mikami, Kohei Akazawa, Hitoshi Tsuda, Takuya Moriya, Atsushi Tajima, Ituro Inoue, Kenichi Tanaka

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ARTICLE 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.