Identification of key transcription factors in endometrial cancer by systems bioinformatics analysis

Song, Yong; Chen, Qiu‐Tong; He, Qi‐Qiang

doi:10.1002/jcb.28811

Cited by 10 publications

(6 citation statements)

References 36 publications

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“…It regulates many cell cycle effector proteins such as CDC6 and CCNA2 [ 170 , 171 ]. It is upregulated in EC and associated with poor prognosis [ 169 , 172 , 173 ]. The upregulation of E2F1 in EC is largely consistent with the expression of several of its target genes, such as PDK4 , BRCA1 and FOXM1 [ 174 , 175 , 176 ], in our differential expression analysis.…”

Section: Discussionmentioning

confidence: 99%

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

Bradfield

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Hill

et al. 2020

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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 NOP56, WFS1, ANAPC4 and TUBB4A. Probing the prognostic and therapeutic utility of these novel TTAGP markers will form an exciting basis for future research.

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Section: Discussionmentioning

confidence: 99%

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

Bradfield

Button

Hill

et al. 2020

MPs

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“…13 Furthermore, bioinformatics analysis using public databases was also applied in EC. Song et al 14 identified three candidate genes, which were closely correlated with the diagnosis and prognosis of EC and could be therapeutic targets for EC. Although several bioinformatical studies on EC have been reported in recent years, we could sieve through different target genes through analyzing distinct databases, which could assist us in further exploring and better studying the underlying mechanisms.…”

Section: Introductionmentioning

confidence: 99%

Identification of biomarkers correlated with diagnosis and prognosis of endometrial cancer using bioinformatics analysis

Zhao

Jiang

et al. 2020

J of Cellular Biochemistry

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Endometrial cancer (EC) is one of the most common malignancies in the female genital system, characterized by high mortality and recurrence rates. This study attempted to screen key genes and potential prognostic biomarkers for EC using bioinformatics analysis. Twenty-seven normal endometrial tissues and 135 EC samples were collected from four Gene Expression Omnibus (GEO) databases, then we identified the differentially expressed genes (DEGs) and conducted downstream analyses. Moreover, we screened hub genes by constructing a protein-protein interaction (PPI) network. Finally, we assessed the prognostic values and molecular mechanism of the potential prognostic genes using the Kaplan-Meier curve and Gene Set Enrichment Analysis (GSEA). As a result, 28 upregulated and 94 downregulated genes were determined after gene integration of these four GEO data sets. Gene Ontology analysis indicated that DEGs were mainly involved in transcriptional regulation and cell proliferation. The Kyoto Encyclopedia of Gene and Genome pathway analysis primarily related to transcriptional misregulation and apoptosis. Moreover, the PPI analysis revealed 10 hub genes (JUN, UBE2I, GATA2, WT1, PIAS1, FOXL2, RUNXI, EZR, TCF4, and NR2F2) with a high degree of connectivity, among them, the expression tendency of nine genes except UBE2I were consistent with messenger RNA level from The Cancer Genome Atlas data. Furthermore, only FOXL2, TCF4, and NR2F2 were significantly correlated with prognosis of EC patients, and their low expression associated biological pathways were enriched in the cell cycle and fatty acid metabolism. In conclusion, this study identified three key genes as biomarkers and potential therapeutic targets of EC on the basis of integrated bioinformatics analysis. The findings will improve our comprehension of the molecular mechanisms underlying the pathogenesis and prognosis of EC.

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“…Receiver operating characteristic (ROC) curves were used to analyze the association between lincRNAs and the survival status of patients with mutant or wild-type KRAS at 10 and 5 years. ROC curves were determined to evaluate the sensitivity and specificity of the expression level of each lincRNA in predicting mortality in patients ( 19 ). Forest plots were used to demonstrate the result of ROC.…”

Section: Methodsmentioning

confidence: 99%

Identification of prognostic long intergenic non‑coding RNAs as competing endogenous RNAs with KRAS mutations in colorectal cancer

Huang

2021

Oncol Lett

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Colorectal cancer (CRC) is recognized as a common type of human cancer, and KRAS mutations are correlated with poor CRC survival outcomes. The evaluation and prediction of CRC results remain challenging. In the present study, RNA sequencing and clinical data from The Cancer Genome Atlas were used to identify KRAS mutation-related prognostic long intergenic non-coding RNAs (lincRNAs) in CRC. Significantly dysregulated lincRNAs and independent prognostic lincRNAs with KRAS mutations in CRC were identified. Two lincRNAs with KRAS mutations, LINC00265 and AL390719.2, were selected as key prognostic lincRNAs for both 10- and 5-year survival rates. In addition, competing endogenous (ce)RNA models were constructed to comprehensively assess the oncogenic performance of the two key lincRNAs. The ceRNA models suggested that LINC00265 and AL390719.2 are critical for the cell cycle and cancer pathways. Finally, reverse transcription-quantitative PCR was used to validate the ceRNA models in 12 pairs of CRC tissue samples. These prognostic lincRNAs may provide novel biomarkers for the prognostic prediction of CRC. The ceRNA model may also demonstrate the underlying mechanism of these lincRNAs in CRC.

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Identification of key transcription factors in endometrial cancer by systems bioinformatics analysis

Cited by 10 publications

References 36 publications

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

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

Identification of biomarkers correlated with diagnosis and prognosis of endometrial cancer using bioinformatics analysis

Identification of prognostic long intergenic non‑coding RNAs as competing endogenous RNAs with KRAS mutations in colorectal cancer

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