Oncology Reports · 2020 · 38 citations · 45 references
MedicineMolecular BiologyOncologyCancer GeneticsGene ExpressionMolecular OncologyCancer EpigenomicsCancer GenomicsCancer Molecular PathologyHepatocellular CarcinomaLiver CancerMolecular Classification Of TumorsBiological PrognosisComparative Cancer Gene Expression ProfilesE2f Transcription Factor RegulationE2f Transcription FactorsFunctional Genomics In CancerPrognostic BiomarkersTp53 MutationsTranscriptional Dysregulation In Cancer
E2F transcription factors are associated with the development of cancer. However, the E2F family genes have not yet been studied in a comprehensive manner. Using The Cancer Genome Atlas, the present study analyzed the functions of the E2F family genes across different types of tumor. It was revealed that compared with normal tissues, the E2F family genes are highly expressed in several types of tumor tissue. Furthermore, E2F transcription factors were significantly enriched in tumor samples across different types of tumor. The high expression levels of E2F family genes were associated with an unfavorable prognosis in liver hepatocellular carcinoma (LIHC) and lung adenocarcinoma (LUAD). Furthermore, patients with pathological T1 stage and iCluster2 molecular subtype of LIHC expressed particularly low levels of E2F family genes. The present study demonstrated that hypo‑DNA methylation, DNA amplification and TP53 mutation contributed to the high expression levels of E2F family genes in cancer cells. Finally, the present study revealed that, compared with other types of tumor, the E2F family genes were specifically downregulated in patients with LIHC. The expression levels and prognostic effects of the E2F family genes were validated using the Gene Expression Omnibus database. The results of the present study revealed the biological functions of E2F family genes in the development of cancer and provided potential biomarkers for further therapeutic studies, particularly for patients with LIHC and LUAD.
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The Cancer Genome Atlas Pan-Cancer analysis project
John N. Weinstein, Gordon B. Mills, Kenna Shaw et al. · Nature Genetics · 2013 · 9.5K citations · Full text
A pathology atlas of the human cancer transcriptome
Mathias Uhlén, Cheng Zhang, Sunjae Lee et al. · Science · 2017 · 3.5K citations · Full text
Medicine, Cancer Biology, Oncology +17