Abstract
BACKGROUND: Breast cancer is a common malignant tumor in women. In recent years, its incidence is increasing year by year, and its morbidity and mortality rank the first place among female malignant tumors. Some key enzymes and intermediates in glycolysis are closely related to tumor development. Pyruvate kinase M2 (PKM2) is an important rate-limiting enzyme in glycolysis pathway. Meanwhile, it is highly expressed in proliferative cells, especially in tumor cells, and plays an important role in the formation of Warburg effect and tumorigenesis. Previous studies have explored the effects of PKM2 expression on the prognosis and clinical significance of breast cancer patients, while the results are contradictory and uncertain. This study uses controversial data for meta-analysis to accurately evaluate the problem. We collected relevant Oncomine and The Cancer Genome Atlas (TCGA) data to further verify the results. Through bioinformatics analysis, the mechanism and related pathways of PKM2 in breast cancer are explored. METHODS: We searched Wanfang, Chinese Biomedical Literature Database, Chinese National Knowledge Infrastructure, the Chongqing VIP Chinese Science and Technology Periodical Database, PubMed, Embase, and Web of Science databases from inception to March 2021. The language restrictions are Chinese and English. The published literatures on PKM2 expression and prognosis or clinicopathological characteristics of breast cancer patients were statistically analyzed. Combined hazard ratios (HRs), odds ratios (ORs), and 95% confidence intervals (95% CIs) were used to evaluate the effects of PKM2 on the prognosis and clinicopathological features of breast cancer. Stata 14.0 software was applied for meta-analysis. Oncomine and TCGA databases were used to meta-analyze the differences of PKM2 mRNA expression between breast cancer and normal breast tissues. The expression of PKM2 protein was verified by Human Protein Atlas (HPA) database. The relationship between the gene and the survival of breast cancer patients was analyzed by Gene Expression Profiling Interactive Analysis (GEPIA). The relationship between PKM2 gene and clinicopathological characteristics was analyzed by using LinkedOmics, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analysis was performed by using Metascape. Protein-protein interaction (PPI) network was constructed by String website. RESULTS: The results of this meta-analysis will be submitted to a peer-reviewed journal for publication. CONCLUSION: This study provides high-quality medical evidence for the correlation between the expression of PKM2 and the prognosis and clinicopathological features of breast cancer. Through bioinformatics analysis, this study further deepens the understanding of the mechanism and related pathways of PKM2 in breast cancer. ETHICS AND DISSEMINATION: The private information from individuals will not be published. This systematic review also should not damage participants' rights. Ethical approval is not available. The results may be published in a peer-reviewed journal or disseminated in relevant conferences. OSF REGISTRATION NUMBER: DOI 10.17605/OSF.IO/W52HB.