Prognostic effect of programmed death-ligand 1 (PD-L1) in ovarian cancer: a systematic review, meta-analysis and bioinformatics study

程序性死亡配体1 (PD-L1) 在卵巢癌中的预后作用:系统评价、荟萃分析和生物信息学研究

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Abstract

BACKGROUND: The expression of PD-L1 has been reported in ovarian cancer. However, the prognostic role of PD-L1 expression in ovarian carcinoma remained controversial. This study was performed to assess the prognostic value of PD-L1 expression on ovarian cancer. METHODS: The PubMed, Embase, EBSCO, and Cochrane Library databases were searched to identify available publications. The pooled odds ratio (OR) or hazard ratios (HRs: multivariate analysis) with their 95% confidence intervals (95% CIs) were calculated in this analysis. A bioinformatics study based on The Cancer Genome Atlas (TCGA) sequencing and microarray datasets was used to further validate the results of PD-L1 mRNA expression. Kaplan-Meier (KM) survival curves were performed to evaluate the prognostic effect of PD-L1 mRNA expression. RESULTS: Twelve studies with 1630 ovarian cancers regarding PD-L1 immunohistochemical expression were identified. Meta-analysis showed that PD-L1 protein expression was not associated with tumor grade, clinical stage, lymph node status, tumor histology, overall survival (OS), and progression-free survival (PFS). TCGA data showed no association between PD-L1 mRNA expression and ovarian cancer. Further validation using microarray data suggested that no association between PD-L1 mRNA expression and OS was found in large independent patient cohorts (1310 cases). PD-L1 mRNA expression was significantly linked to worse PFS in 1228 patients with ovarian cancer (227458_at: HR = 1.55, 95% CI = 1.28-1.88, P < 0.001; 223834_at: HR = 1.41, 95% CI = 1.14-1.75, P = 0.0015). CONCLUSIONS: Meta-analysis showed that PD-L1 may not be a prognostic factor for ovarian cancer. But a bioinformatics study showed that PD-L1 expression was significantly associated with worse PFS of ovarian cancer. More clinical studies are needed to further validate these findings.

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