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TOP2A and CENPF are synergistic master regulators activated in cervical cancer.


ABSTRACT: BACKGROUND:Identification of master regulators (MRs) using transcriptome data in cervical cancer (CC) could help us to develop biomarkers and find novel drug targets to fight this disease. METHODS:We performed differential expression (DE) analyses of public microarray and RNA-seq transcriptome data of CC and normal cervical tissues (N). Virtual Inference of Protein activity by Enriched Regulon analysis (VIPER) was used to convert the DE outcomes to differential activity (DA) signature for MRs. Synergy analysis was conducted to study synergistic effect of MR-pairs. TCGA and microarray data were used to test the association of expression of a MR and a clinical feature or a molecular feature (e.g. somatic mutations). Various bioinformatic tools/websites (DAVID, GEPIA2, Oncomine, cBioPortal) were used to analyze the expression of the top MRs and their regulons. RESULTS:Ten DE and 10 DA signatures were generated for CC. Two MRs, DNA topoisomerase II alpha (TOP2A) and centromere protein F (CENPF) were found to be up-regulated, activated and synergistic in CC compared to N across the 10 datasets. The two MRs activate a common set of genes (regulons) with functions in cell cycle, chromosome, DNA damage etc. Higher expression of CENPF was associated with metastasis. High expression of both MRs is associated with somatic mutation of a set of genes including tumor suppressors (TP53, MSH2, RB1) and genes involved in cancer pathways, cell cycle, DNA damage and repair. The magnitude of up-regulation and the absolute expression level of both MRs in CC are significantly higher compared to many other cancer types. CONCLUSION:TOP2A and CENPF are a synergistic pair of MRs that are overexpressed and activated in CC. Their high expression is correlated with some prognosis features (e.g. metastasis) and molecular features (e.g. somatic mutations) and distinctly high in CC vs. many other cancer types. They may be good biomarkers and anticancer drug targets for CC.

SUBMITTER: Yu B 

PROVIDER: S-EPMC7541258 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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<h4>Background</h4>Identification of master regulators (MRs) using transcriptome data in cervical cancer (CC) could help us to develop biomarkers and find novel drug targets to fight this disease.<h4>Methods</h4>We performed differential expression (DE) analyses of public microarray and RNA-seq transcriptome data of CC and normal cervical tissues (N). Virtual Inference of Protein activity by Enriched Regulon analysis (VIPER) was used to convert the DE outcomes to differential activity (DA) signa  ...[more]

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