Establishment of a Novel Histopathological Classification of High-Grade Serous Ovarian Carcinoma Correlated with Prognostically Distinct Gene Expression Subtypes.
(Clinical Trial;Journal Article;Multicenter Study)
Recently, The Cancer Genome Atlas data revealed four molecular subtypes of high-grade serous ovarian carcinoma (HGSOC) exhibiting distinct prognoses. We developed four novel HGSOC histopathological subtypes by focusing on tumor microenvironment: mesenchymal transition, defined by a remarkable desmoplastic reaction; immune reactive by lymphocytes infiltrating the tumor; solid and proliferative by a solid growth pattern; and papilloglandular by a papillary architecture. Unsupervised hierarchical clustering revealed four clusters correlated with histopathological subtypes in both Kyoto and Niigata HGSOC transcriptome data sets (P < 0.001). Gene set enrichment analysis revealed pathways enriched in our histopathological classification significantly overlapped with the four molecular subtypes: mesenchymal, immunoreactive, proliferative, and differentiated (P < 0.0001, respectively). In 132 HGSOC cases, progression-free survival and overall survival were best in the immune reactive, whereas overall survival was worst in the mesenchymal transition (P < 0.001, respectively), findings reproduced in 89 validation cases (P < 0.05, respectively). The CLOVAR_MES_UP single-sample gene set enrichment analysis scores representing the mesenchymal molecular subtype were higher in paclitaxel responders than nonresponders (P = 0.002) in the GSE15622 data set. Taxane-containing regimens improved survival of cases with high MES_UP scores compared with nontaxane regimens (P < 0.001) in the GSE9891 data set. Our novel histopathological classification of HGSOC correlates with distinct prognostic transcriptome subtypes. The mesenchymal transition subtype might be particularly sensitive to taxane.
Murakami, R; Matsumura, N; Mandai, M; Yoshihara, K; Tanabe, H; Nakai, H; Yamanoi, K; Abiko, K; Yoshioka, Y; Hamanishi, J; Yamaguchi, K; Baba, T; Koshiyama, M; Enomoto, T; Okamoto, A; Murphy, SK; Mori, S; Mikami, Y; Minamiguchi, S; Konishi, I
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