PD-L1 and the Clinical Outcomes of Ovarian Cancer: Meta-Analysis and Bioinformatical Analysis

Shi, Xiaoling; Yun, Liu; Chaoqun Liu, Liu; Ding, Hui; Liang, Dan; Geng, Fang; Yu, Hainan; Ban, Jinxiu; Li, Jiajing; Jiang, Tao; Sun, Yi

doi:10.31557/APJCP.2022.23.7.2285

PD-L1 and the Clinical Outcomes of Ovarian Cancer: Meta-Analysis and Bioinformatical Analysis

Document Type : Research Articles

Authors

¹ Department of Toxicology, Guilin Medical University, Guilin 541004, China.

² Department of Gynaecology and Obstetrics, Kailuan General Hospital,Tangshan, Hebei, 063000, China.

³ Department of Nutrition, School of Medicine, Jinan University, Guangzhou, Guangdong, China.

⁴ Department of Pharmaceutical Analysis, School of Pharmacy Yancheng Teachers University, Yancheng, Jiangsu, China.

⁵ Department of Clinical Laboratory, Tangshan Maternity and Children & Health Care Hospital, Tangshan, Hebei, 063000, China.

10.31557/APJCP.2022.23.7.2285

Abstract

Objective: A meta-analysis was performed to analyze the association between PD-L1 expression and overall survival (OS) in various tumors and to identify potential targets through biological information analysis. Methods: the data were collected from PubMed and Cochrane library, the all analysis of our study were conducted by STATA software and online website. Results: Ten articles (including 11 studies) that met all inclusion criteria were obtained. The combined HR showed that high PD-L1 expression was significantly associated with poor overall survival (HR = 1.84, 95% CI: 1.15-2.93). Pathway analysis revealed that the upregulated genes were primarily involed in biological processes, including nucleic acid transcription, biosynthesis and negative regulation of cell metabolism. The downregulated genes were primarily involed in the regulation of cell cycle, including chromosome separation and DNA metabolism. The top ten genes that were identified were hub genes (CDK1, CCNB1, CCNA2, KIF11, CDC20, UBE2C, NCAPG, AURKA, AURKB, CHEK1), which had significant function in cell differentiation and virus infection. The Kaplan-Meier survival curve indicated that CCNB1, KIF11, UBE2C, NCAPG, AURKA and CHEK1 were statistically significant (P<0.05). Conclusion: PD-L1 was found to be a latent biomarker for predicting the prognostic value of cancer and also a therapeutic target.

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