Immune-and Metabolism-Associated Molecular Classification of Ovarian Cancer

Ovarian cancer (OV) is a complex gynecological disease, and its molecular characteristics are not clear. In this study, the molecular characteristics of OV subtypes based on metabolic genes were explored through the comprehensive analysis of genomic data. A set of transcriptome data of 2752 known me...

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Published inFrontiers in oncology Vol. 12; p. 877369
Main Authors Chen, Zhenyue, Jiang, Weiyi, Li, Zhen, Zong, Yun, Deng, Gaopi
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 12.05.2022
Subjects
metabolic genes
molecular characteristics
Oncology
ovarian cancer
subtypes
tumor
metabolic genes
ovarian cancer
molecular characteristics
tumor
subtypes
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Summary:Ovarian cancer (OV) is a complex gynecological disease, and its molecular characteristics are not clear. In this study, the molecular characteristics of OV subtypes based on metabolic genes were explored through the comprehensive analysis of genomic data. A set of transcriptome data of 2752 known metabolic genes was used as a seed for performing non negative matrix factorization (NMF) clustering. Three subtypes of OV (C1, C2 and C3) were found in analysis. The proportion of various immune cells in C1 was higher than that in C2 and C3 subtypes. The expression level of immune checkpoint genes TNFRSF9 in C1 was higher than that of other subtypes. The activation scores of cell cycle, RTK-RAS, Wnt and angiogenesis pathway and ESTIMATE immune scores in C1 group were higher than those in C2 and C3 groups. In the validation set, grade was significantly correlated with OV subtype C1. Functional analysis showed that the extracellular matrix related items in C1 subtype were significantly different from other subtypes. Drug sensitivity analysis showed that C2 subtype was more sensitive to immunotherapy. Survival analysis of differential genes showed that the expression of PXDN and CXCL11 was significantly correlated with survival. The results of tissue microarray immunohistochemistry showed that the expression of PXDN was significantly correlated with tumor size and pathological grade. Based on the genomics of metabolic genes, a new OV typing method was developed, which improved our understanding of the molecular characteristics of human OV.
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Reviewed by: Congrong Liu, Department of Pathology of Peking University Health Science Center, China; Dong-Joo (Ellen) Cheon, Albany Medical College, United States
This article was submitted to Gynecological Oncology, a section of the journal Frontiers in Oncology
Edited by: Sandra Orsulic, University of California, Los Angeles, United States
ISSN:2234-943X
2234-943X
DOI:10.3389/fonc.2022.877369