TY - JOUR
T1 - Article Epigenomic Profiling of Epithelial Ovarian Cancer Stem-Cell Differentiation Reveals GPD1 Associated Immune Suppressive Microenvironment and Poor Prognosis
AU - Chen, Lin Yu
AU - Huang, Rui Lan
AU - Su, Po Hsuan
AU - Lai, Hung Cheng
AU - Wen, Kuo Chang
AU - Chu, Ling Hui
AU - Weng, Yu Chun
AU - Wang, Hui Chen
N1 - Funding Information:
Funding: This work was supported by grants from the Ministry of Science and Technology, Taiwan [MOST 109-2314-B-038-052-MY3 and MOST 108-2314-B-038-096 to HCL; MOST 109-2314-B-038-055 and MOST 110-2314-B-038-059 to KCW; MOST 110-2314-B-038-060 to LYC; MOST 109-2314-B-038-107-MY3 to PHS], National Health Research Institutes, Taiwan [NHRI-EX106-10406BI to HCL], Taipei Medical University, Taiwan [TMU108-AE1-B54 to KCW; TMU108-AE1-B35 to RLH], and Taipei Medical University-Shuang Ho Hospital, Taiwan [109TMU-SHH-20 to LYC].
Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2022/5/1
Y1 - 2022/5/1
N2 - 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 GPD1 expression with high pro-tumorigenic immune cells (M2 macrophage, and cancer associated fibroblast) had worst survival. Moreover, we developed a methylation signature, constituted by GNPDA1, GPD1, GRASP, HOXC11, and MSLN, 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.
AB - 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 GPD1 expression with high pro-tumorigenic immune cells (M2 macrophage, and cancer associated fibroblast) had worst survival. Moreover, we developed a methylation signature, constituted by GNPDA1, GPD1, GRASP, HOXC11, and MSLN, 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.
KW - cancer stem cells
KW - epigenetics
KW - epithelial ovarian cancer
KW - prognostic biomarker
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U2 - 10.3390/ijms23095120
DO - 10.3390/ijms23095120
M3 - Article
AN - SCOPUS:85129397904
SN - 1661-6596
VL - 23
JO - International journal of molecular sciences
JF - International journal of molecular sciences
IS - 9
M1 - 5120
ER -