Identification of Three Potential Prognostic Genes in Platinum-Resistant Ovarian Cancer via Integrated Bioinformatics Analysis - Zhang X (Dove Medical Press, 2021)
Xue Zhang,1– 3 Xuan Wei,1– 3 Gaigai Bai,1– 3 Xueyao Huang,1– 3 Shunxue Hu,4 Hongluan Mao,1– 3 Peishu Liu1– 3 1Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan, Shandong, People’s Republic of China; 2Key Laboratory of Gynecology Oncology of Shandong Province, Qilu Hospital of Shandong University, Jinan, Shandong, People’s Republic of China; 3Shandong Engineering Laboratory for Urogynecology, Qilu Hospital of Shandong University, Jinan, Shandong, People’s Republic of China; 4Department of Pathology, Qilu Hospital of Shandong University, Jinan, Shandong, People’s Republic of ChinaCorrespondence: Hongluan Mao; Peishu LiuDepartment of Obstetrics and Gynecology, Qilu Hospital of Shandong University, 107 Wenhua Xi Road, Jinan, Shandong, People’s Republic of ChinaEmail hongluanmao@126.com; peishuliu@126.comPurpose: Ovarian cancer is the most lethal gynecologic malignancy. Resistance to platinum-based chemotherapy affects the overall survival of patients. This study used an integrated bioinformatics to find the poorly understood molecular mechanisms underlying platinum resistance in ovarian cancer.Methods: Based on the RNA-seq data of tissues in The Cancer Genome Atlas (TCGA) and RNA-seq data of cells from the Cancer Cell Encyclopedia (CCLE), we integrated differentially expressed genes (DEGs) in ovarian cancer tissue and cells. After screening for DEGs related to platinum resistance, we conducted survival analysis and built protein interaction networks to identify genes that may affect prognosis and interact with each other. Least absolute shrinkage and selection operator (Lasso) regression analysis was used to construct a predictive model. Immunohistochemistry and Western blot were used to validate the results. Finally, gene set enrichment analysis (GSEA) was performed on the expression of genes individually.Results: We found that ATPase Na+/K+ transporting subunit alpha 2 (ATP1A2), calsequestrin 2 (CASQ2) and ryanodine receptor 2 (RYR2) interacted with each other and could predict resistance to platinum-based therapy, correlating negatively with prognosis. Moreover, we constructed a predictive model based on nine genes, including ATP1A2 and CASQ2. Immunohistochemistry and Western blot validated the upregulation of these genes in ovarian cancer tissue samples and cell lines. The immunohistochemistry results also confirmed the prognostic value of ATP1A2, CASQ2 and RYR2. GSEA predicted that ATP1A2, CASQ2 and RYR2 may act on the KRAS and mTORC1 pathways and participate in metabolic reprogramming and regulation of calcium homeostasis in platinum-resistant cells.Conclusion: ATP1A2, CASQ2 and RYR2 were highly expressed in platinum-resistant ovarian cancer. ATP1A2 and CASQ2 were related to the prognosis of platinum-resistant ovarian cancer patients. These genes might act on KARS and mTORC1 pathways and participate in metabolic reprogramming and regulation of calcium homeostasis in platinum-resistant cells.Keywords: ovarian cancer, platinum resistance, prognosis, metabolic reprogramming, calcium homeostasis