Comprehensive Biological Information Analysis of PTEN Gene in Pan-Cancer | Abstract
Journal of Clinical Trials

Journal of Clinical Trials
Open Access

ISSN: 2167-0870

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Comprehensive Biological Information Analysis of PTEN Gene in Pan-Cancer

Hang Zhang†, Wenhan Zhou, Xiaoyi Yang, Shuzhan Wen, Baicheng Zhao, Jiale Feng, Bozhou Chen, Shuying Chen*

Background: PTEN was a multifunctional tumor suppressor gene mutating at high frequency in a variety of cancers. However, its expression in pan-cancer, correlated genes, survival prognosis, and regulatory pathways were not completely described. Here, we aimed to conduct a comprehensive analysis from the above perspectives in order to provide reference for clinical application. Methods: We studied the expression levels in cancers by using data from TCGA and GTEx database. Obtain expression box plot from UALCAN database, performed mutation analysis on the cBioportal website, obtained
correlation genes on the GEPIA website, constructed protein network and perform KEGG and GO enrichment analysis on the STRING database and conducted prognostic analysis on the Kaplan-Meier Plotter website. We also performed transcription factor prediction on the PROMO database and RNA-RNA association/RNA-protein interaction on the RNAup Web server and RPISeq. The gene 3D structure, protein sequence and conserved domain were obtained from NCBI.
Results: PTEN was underexpressed in all cancers we studied. It was closely related to the clinical stage of tumors, suggesting PTEN may involve in cancer development and progression. The mutations of PTEN were present in a variety of cancers, most of which were truncation mutations and missense mutations. Among cancers (KIRC, LUAD, THYM, UCEC, gastric cancer, liver cancer, lung cancer, breast cancer), patients with low expression of PTEN had a shorter OS time and poorer OS prognosis. The low expression of PTEN can cause the deterioration of RFS in certain cancers (TGCT, UCEC, LIHC, LUAD, THCA), suggesting that the expression of PTEN was related to the clinical prognosis. Our study identified genes correlated with PTEN and performed GO enrichment analysis on 100 PTENrelated genes obtained from the GEPIA website. Conclusion: The understanding of PTEN gene and the in-depth exploration of its related regulatory pathways may provide insight for the discovery of tumor-specific biomarkers and clinical potential therapeutic targets.

Published Date: 2021-11-03; Received Date: 2021-10-06