Multi‐omics‐based analysis of high grade serous ovarian cancer subtypes reveals distinct molecular processes linked to patient prognosis. Issue 4 (24th February 2023)

• Record Type: Journal Article
• Authors: Wang, Yuanshuo Alice; Neff, Ryan; Song, Won‐min; Zhou, Xianxiao; Vatansever, Sezen; Walsh, Martin J.; Chen, Shu‐Hsia; Zhang, Bin
• Is Part Of: FEBS open bio. Volume 13:Issue 4(2023)
• Page Start: 617
• Page End: 637
• Publication Date: 2023-02-24
• Subjects: co‐expression network -- drug repositioning -- key regulator -- molecular subtypes -- ovarian cancer; Molecular biology -- Periodicals; Cytology -- Periodicals; Life sciences -- Periodicals; Biological Science Disciplines -- Periodicals; Molecular Biology -- Periodicals; Cell Biology -- Periodicals; Cytology; Life sciences; Molecular biology; Periodicals; 572.805
• DOI: 10.1002/2211-5463.13553
• Languages: English
• ISSNs: 2211-5463

Abstract

Abstract : Despite advancements in treatment, high‐grade serous ovarian cancer (HGSOC) is still characterized by poor patient outcomes. To understand the molecular heterogeneity of this disease, which underlies the challenge in selecting optimal treatments for HGSOC patients, we have integrated genomic, transcriptomic, and epigenetic information to identify seven new HGSOC subtypes using a multiscale clustering method. These subtypes not only have significantly distinct overall survival, but also exhibit unique patterns of gene expression, microRNA expression, DNA methylation, and copy number alterations. As determined by our analysis, patients with similar clinical outcomes have distinct profiles of activated or repressed cellular processes, including cell cycle, epithelial‐to‐mesenchymal transition, immune activation, interferon response, and cilium organization. Furthermore, we performed a multiscale gene co‐expression network analysis to identify subtype‐specific key regulators and predicted optimal targeted therapies based on subtype‐specific gene expression. In summary, this study provides new insights into the cellular heterogeneity of the HGSOC genomic, epigenetic, and transcriptomic landscapes and provides a basis for future studies into precision medicine for HGSOC patients. Abstract : We integrated multiomics information to identify seven novel HGSOC molecular subtypes using a multiscale clustering method. These subtypes have distinct survival, genetic, and epigenetic patterns. We also constructed a gene co‐expression network to identify subtype‐specific key regulators. We further predicted and validated targeted therapies for HGSOC molecular subtypes. This study provides a foundation for pecision medicine in HGSOC.