Xiaoqing Wu

PTGIS May Be a Predictive Marker for Ovarian Cancer by Regulating Fatty Acid Metabolism

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.

Effect of ERCC1 polymorphisms on the response to platinum-based chemotherapy: A systematic review and meta-analysis based on Asian population

BackgroundPlatinum-based chemotherapy is one of the most common treatments for many cancers; however, the effect of chemotherapy varies from individual to individual. Excision repair cross complementation group 1 (ERCC1) is widely recognized as a key gene regulating nucleotide excision repair (NER) and is closely associated with platinum response. Many studies have yielded conflicting results regarding whether ERCC1 polymorphisms can affect the response to platinum and overall survival (OS). Therefore, it is necessary to perform a meta-analysis of patients with specific races and cancer types.MethodsEight databases (EMBASE, PubMed, Cochrane Library, Chinese National Knowledge Infrastructure, Scopus, VIP, China Biology Medicine disc and Wanfang databases) were searched. Results were expressed in terms of odds ratios (ORs), hazard ratios (HRs) and 95% CIs.ResultsIn this study, rs11615, rs2298881 and rs3212986 SNPs were studied. In the comparison between CT and TT on the response to platinum, esophageal cancer [I2= 0%, OR = 6.18, 95% CI(1.89,20.23), P = 0.003] and ovarian cancer [I2= 0%, OR = 4.94, 95% CI(2.21,11.04), P<0.001] showed that the rs11615 CT genotype predicted a better response. In the comparison between CC and TT, ovarian cancer [I2= 48.0%, OR = 6.15, 95% CI (2.56,14.29), P<0.001] indicated that the CC genotype predicted a better response. In the meta-analysis of OS, the CC genotype was related to longer OS than TT in ovarian cancer [TT vs CC: I2= 57.7%, HR = 1.71, 95% CI (1.18, 2.49), P<0.001].ConclusionThe ERCC1 rs11615 polymorphism was related to the response to platinum and OS, but the correlation is based on specific cancer types in the Asian population.

Macrophages Phenotype Regulated by IL-6 Are Associated with the Prognosis of Platinum-Resistant Serous Ovarian Cancer: Integrated Analysis of Clinical Trial and Omics

Background. The treatment of platinum-resistant recurrent ovarian cancer (PROC) is a clinical challenge and a hot topic. Tumor microenvironment (TME) as a key factor promoting ovarian cancer progression. Macrophage is a component of TME, and it has been reported that macrophage phenotype is related to the development of PROC. However, the mechanism underlying macrophage polarization and whether macrophage phenotype can be used as a prognostic indicator of PROC remains unclear. Methods. We used ESTIMATE to calculate the number of immune and stromal components in high-grade serous ovarian cancer (HGSOC) cases from The Cancer Genome Atlas database. The differential expression genes (DEGs) were analyzed via protein–protein interaction network, Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) analysis to reveal major pathways of DEGs. CD80 was selected for survival analysis. IL-6 was selected for gene set enrichment analysis (GSEA). A subsequent cohort study was performed to confirm the correlation of IL-6 expression with macrophage phenotype in peripheral blood and to explore the clinical utility of macrophage phenotype for the prognosis of PROC patients. Results. A total of 993 intersecting genes were identified as candidates for further survival analysis. Further analysis revealed that CD80 expression was positively correlated with the survival of HGSOC patients. The results of GO and KEGG analysis suggested that macrophage polarization could be regulated via chemokine pathway and cytokine–cytokine receptor interaction. GSEA showed that the genes were mainly enriched in IL-6-STAT-3. Correlation analysis for the proportion of tumor infiltration macrophages revealed that M2 was correlated with IL-6. The results of a cohort study demonstrated that the regulation of macrophage phenotype by IL-6 is bidirectional. The high M1% was a protective factor for progression-free survival. Conclusion. Thus, the macrophage phenotype is a prognostic indicator in PROC patients, possibly via a hyperactive IL-6-related pathway, providing an additional clue for the therapeutic intervention of PROC.