International Journal of General Medicine (Feb 2022)

SCNN1A Overexpression Correlates with Poor Prognosis and Immune Infiltrates in Ovarian Cancer

  • Lou J,
  • Wei L,
  • Wang H

Journal volume & issue
Vol. Volume 15
pp. 1743 – 1763

Abstract

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Jiayan Lou, Lingjia Wei, He Wang Department of Gynecology and Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, People’s Republic of ChinaCorrespondence: He Wang, Department of Gynecology and Oncology, Guangxi Medical University Cancer Hospital, 71 He Di Road, Nanning, Guangxi, 530021, People’s Republic of China, Tel +86 13481138393, Email [email protected]: Ovarian cancer (OV) is a common malignancy affecting women globally; recognizing useful biomarkers has been one of the key priorities. Since SCNN1A was reported to be relevant to tumor progression in a variety of cancers, but rarely in ovarian cancer, we explored the roles of SCNN1A in OV.Methods: RNA sequencing data from TCGA and GEO were utilized to analyze the expression of SCNN1A and related differentially expressed genes (DEGs) in ovarian cancer. We performed GO, GSEA and immune cell infiltration analysis on SCNN1A-associated DEGs. Correlation of SCNN1A methylation levels and its mRNA expression was analyzed by cBioPortal and UCSC Xena databases. To assess the prognostic impact of SCNN1A, Kaplan–Meier plot analysis and Cox regression analysis were performed; ROC curves and nomogram were also plotted.Results: Compared to normal tissues, SCNN1A was highly expressed in ovarian cancer. The methylation level of SCNN1A negatively correlated with the SCNN1A expression. Moreover, high expression of SCNN1A was correlated with poor prognosis in OV patients and associated with immune infiltrates.Conclusion: High SCNN1A expression could be a promising biomarker for poor outcomes in OV and correlated with tumor immune cells infiltration. The findings might help illuminate the function of SCNN1A in tumorigenesis and lay a foundation for further research.Keywords: ovarian cancer, SCNN1A, biological function, prognostic biomarker, immune infiltrates

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