Investigating the Role of Telomere and Telomerase Associated Genes and Proteins in Endometrial Cancer



Bradfield, Alice, Button, Lucy, Drury, Josephine ORCID: 0000-0002-2275-6664, Green, Daniel C, Hill, Christopher J ORCID: 0000-0003-3831-4569 and Hapangama, Dharani K ORCID: 0000-0003-0270-0150
(2020) Investigating the Role of Telomere and Telomerase Associated Genes and Proteins in Endometrial Cancer. METHODS AND PROTOCOLS, 3 (3). E63-.

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Abstract

Endometrial cancer (EC) is the commonest gynaecological malignancy. Current prognostic markers are inadequate to accurately predict patient survival, necessitating novel prognostic markers, to improve treatment strategies. Telomerase has a unique role within the endometrium, whilst aberrant telomerase activity is a hallmark of many cancers. The aim of the current in silico study is to investigate the role of telomere and telomerase associated genes and proteins (TTAGPs) in EC to identify potential prognostic markers and therapeutic targets. Analysis of RNA-seq data from The Cancer Genome Atlas identified differentially expressed genes (DEGs) in EC (568 TTAGPs out of 3467) and ascertained DEGs associated with histological subtypes, higher grade endometrioid tumours and late stage EC. Functional analysis demonstrated that DEGs were predominantly involved in cell cycle regulation, while the survival analysis identified 69 DEGs associated with prognosis. The protein-protein interaction network constructed facilitated the identification of hub genes, enriched transcription factor binding sites and drugs that may target the network. Thus, our in silico methods distinguished many critical genes associated with telomere maintenance that were previously unknown to contribute to EC carcinogenesis and prognosis, including <i>NOP56</i>, <i>WFS1</i>, <i>ANAPC4</i> and <i>TUBB4A</i>. Probing the prognostic and therapeutic utility of these novel TTAGP markers will form an exciting basis for future research.

Item Type: Article
Uncontrolled Keywords: telomere, telomerase, endometrial cancer, prognosis, bioinformatics analysis, transcriptome, TCGA
Depositing User: Symplectic Admin
Date Deposited: 14 Sep 2020 08:47
Last Modified: 16 Nov 2023 15:12
DOI: 10.3390/mps3030063
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3100800