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Epigenomic Profiling of Epithelial Ovarian Cancer Stem-Cell Differentiation Reveals GPD1 Associated Immune Suppressive Microenvironment and Poor Prognosis
Intraperitoneal metastasis is a challenging clinical scenario in epithelial ovarian cancer (EOC). As they are distinct from hematogenous metastasizing tumors, epithelial ovarian cancer cells primarily disseminate within the peritoneal cavity to form superficially invasive carcinomas. Unfavorable pha...
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Published in: | International journal of molecular sciences 2022-05, Vol.23 (9), p.5120 |
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Main Authors: | , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Intraperitoneal metastasis is a challenging clinical scenario in epithelial ovarian cancer (EOC). As they are distinct from hematogenous metastasizing tumors, epithelial ovarian cancer cells primarily disseminate within the peritoneal cavity to form superficially invasive carcinomas. Unfavorable pharmacokinetics for peritoneal tumors and gut toxicity collectively lead to a narrow therapeutic window and therefore limit the opportunities for a favorable clinical outcome. New insights into tumor metastasis in the peritoneal microenvironment are keenly awaited to develop new therapeutic strategies. Epithelial ovarian cancer stem cell (OCSC) seeding is considered to be a critical component of the peritoneal spread. Using a unique and stepwise process of the OCSC differentiation model may provide insight into the intraperitoneal metastasis. The transcriptome and epigenome of OCSC differentiation were characterized by expression array and MethylCap-Seq. The TCGA, AOCS, and KM-Plotter databases were used to evaluate the association between survival outcomes and the methylation/expression levels of candidate genes in the EOC datasets. The STRING database was used to investigate the protein-protein interaction (PPI) for candidates and their associated genes. The infiltration level of immune cells in EOC patients and the association between clinical outcome and OCSCs differentiation genes were estimated using the TIDE and TIME2.0 algorithms. We established an EOC differentiation model using OCSCs. After an integrated transcriptomics and methylomics analysis of OCSCs differentiation, we revealed that the genes associated with earlier OCSC differentiation were better able to reflect the patient's outcome. The OCSC differentiation genes were involved in regulating metabolism shift and the suppressive immune microenvironment. High
expression with high pro-tumorigenic immune cells (M2 macrophage, and cancer associated fibroblast) had worst survival. Moreover, we developed a methylation signature, constituted by
,
,
,
, and
, that may be useful for prognostic prediction in EOC. Our results revealed a novel role of epigenetic plasticity OCSC differentiation and suggested metabolic and immune intervention as a new therapeutic strategy. |
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ISSN: | 1422-0067 1661-6596 1422-0067 |
DOI: | 10.3390/ijms23095120 |