PTGIS May Be a Predictive Marker for Ovarian Cancer by Regulating Fatty Acid Metabolism. (2nd February 2023)

• Record Type: Journal Article
• Authors: Wu, Xiaoqing; Lu, Wenping; Xu, Chaojie; Jiang, Cuihong; Zhang, Weixuan; Zhang, Dongni; Cui, Shasha; Zhuo, Zhili; Cui, Yongjia; Mei, Heting; Wang, Ya'nan; Li, Chen
• Other Names: Tabarkiewicz Jacek Academic Editor.
• Is Part Of: Computational and mathematical methods in medicine. Volume 2023(2023)
• Publication Date: 2023-02-02
• Subjects: Medicine -- Computer simulation -- Periodicals; Medicine -- Mathematical models -- Periodicals; 610.11
• DOI: 10.1155/2023/2397728
• Languages: English
• ISSNs: 1748-670X

Abstract

Abstract : Background . Ovarian cancer tends to metastasize to the omentum, which is an organ mainly composed of adipose tissue. Many studies have found that fatty acid metabolism is related to the occurrence and metastasis of cancers. Therefore, it is possible that fatty acid metabolism-related genes (FAMRG) affect the prognosis of ovarian cancer patients. Methods . First, profiles of ovarian cancer and normal ovarian tissue transcriptomes were acquired from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases. A LASSO regression predictive model was developed via the "glmnet" R package. The nomogram was created via the "regplot." Gene Set Variation Analysis (GSVA), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Ontology (GO) analyses were conducted to determine the FAMRGs' roles. The percentage of immunocyte infiltration was calculated via CIBERSORT. Using "pRRophetic, " the sensitivity of eight regularly used medications and immunotherapy was anticipated. Results . 125 genes were determined as different expression genes (DEGs). Based on RXRA, ECI2, PTGIS, and ACACB, a prognostic model is created and the risk score is calculated. Analyses of univariate and multivariate regressions revealed that the risk score was a distinct prognostic factor (univariate: HR: 2.855, 95% CI: 1.756-4.739, P < 0.001 ; multivariate: HR: 2.943, 95% CI: 1.800-4.812, P < 0.001 ). The nomogram demonstrated that it properly predicted the 1-year survival rate. The expression of memory B molecular units, follicular helper T molecular units, regulatory T molecular units, and M1 macrophages differed remarkably between the groups at high and low risk (P < 0.05 ). Adipocytokine signaling pathways, cancer pathways, and degradation of valine, leucine, and isoleucine vary between high- and low-risk populations. The findings of the GO enrichment revealed that the extracellular matrix and cellular structure were the two most enriched pathways. PTGIS, which is an important gene in fatty acid metabolism, was identified as the hub gene. This result was verified in ovarian cancer and ovarian tissues. The connection between the gene and survival was statistically remarkable (P = 0.015 ). The pRRophetic algorithm revealed that the low-risk group was more adaptable to cisplatin, doxorubicin, 5-fluorouracil, and etoposide (P < 0.001 ). Conclusion . PTGIS may be an indicator of prognosis and a possible therapeutic target for the therapy of ovarian cancer patients. The fatty acid metabolism of immune cells may be controlled, which has an indirect effect on cancer cell growth.