Functional impact of colorectal cancer-associated mutations in the transcription factor E2F4

Transcription factor E2F4 is an indicator of poor prognosis and is related to immune infiltration in hepatocellular carcinoma

Background: Recent studies have shown that the transcription factor E2F4 is involved in the progression of various tumors, but its expression and influence on immune cell infiltration and biological functions are largely unknown in hepatocellular carcinoma (HCC).

Methods: The Cancer Genome Atlas (TCGA) database, the Tumor Immune Estimation Resource (TIMER) and related online tools as well as a tissue microarray (TMA) were used for analyses in our study.

Results: E2F4 expression was elevated in HCC tumor tissue compared with adjacent normal tissue at both the mRNA and protein levels. Overexpression of E2F4 was markedly related to a poor prognosis in HCC patients. In addition, positively and negatively correlated significant genes of E2F4 were identified in HCC. Pathway enrichment analyses revealed that the top 100 positively correlated significant genes of E2F4 were closely related to nuclear splicing and degradation-related pathways. Furthermore, nine hub genes correlated with E2F4 expression were validated based on a protein-protein interaction (PPI) network. It was also demonstrated that E2F4 expression was negatively correlated to immune purity and positively correlated to immune cell infiltration.

Conclusion: E2F4 could serve as a novel biomarker for HCC diagnosis and prognosis prediction.

The E2F family as potential biomarkers and therapeutic targets in colon cancer

Background

The E2F family is a group of genes encoding a series of transcription factors in higher eukaryotes and participating in the regulation of cell cycle and DNA synthesis in mammals. This study was designed to investigate the role of E2F family in colon cancer.

Methods

In this study, the transcriptional levels of E2F1-8 in patients with colon cancer from GEPIA was examined. Meanwhile, the immunohistochemical data of the eight genes were also obtained in the The Human Protein Atlas website. Additionally, we re-identified the mRNA expression levels of these genes via real time PCR. Furthermore, the association between the levels of E2F family and stage plot as wells overall survival of patients with colon cancer were analyzed.

Results

We found that the mRNA and protein levels of E2F1, E2F2, E3F3, E2F5, E2F7 and E2F8 were significantly higher in colon cancer tissues than in normal colon tissues while the expression levels of E2F4 and E2F6 displayed no significant difference between colon cancer tissues and normal tissues. Additionally, E2F3, E2F4, E2F7 and E2F8 were significantly associated with the stages of colon cancer. The Kaplan-Meier Plotter showed that the high levels of E2F3 conferred a worse overall survival and disease free survival of patients with colon cancer. Also, high levels of E2F4 resulted in a worse overall survival.

Conclusion

Our study implied that E2F3, E2F4, E2F7 and E2F8 are potential targets of precision therapy for patients with colon cancer while E2F1, E2F2, E3F3, E2F5, E2F7 and E2F8 are potential biomarkers for the diagnosis of colon cancer.

E2F4 regulates transcriptional activation in mouse embryonic stem cells independently of the RB family

E2F transcription factors are central regulators of cell division and cell fate decisions. E2F4 often represents the predominant E2F activity in cells. E2F4 is a transcriptional repressor implicated in cell cycle arrest and whose repressive activity depends on its interaction with members of the RB family. Here we show that E2F4 is important for the proliferation and the survival of mouse embryonic stem cells. In these cells, E2F4 acts in part as a transcriptional activator that promotes the expression of cell cycle genes. This role for E2F4 is independent of the RB family. Furthermore, E2F4 functionally interacts with chromatin regulators associated with gene activation and we observed decreased histone acetylation at the promoters of cell cycle genes and E2F targets upon loss of E2F4 in RB family-mutant cells. Taken together, our findings uncover a non-canonical role for E2F4 that provide insights into the biology of rapidly dividing cells.

E2F transcription factors are regulators of cell division and cell fate decisions. Here the authors show that E2F4 is important for proliferation and survival of mouse ESCs, independent of the RB family, and that E2F4 interacts with chromatin regulators associated with gene activation.

Potential biomarkers and therapeutic targets in cervical cancer: Insights from the meta-analysis of transcriptomics data within network biomedicine perspective

The malignant neoplasm of the cervix, cervical cancer, has effects on the reproductive tract. Although infection with oncogenic human papillomavirus is essential for cervical cancer development, it alone is insufficient to explain the development of cervical cancer. Therefore, other risk factors such as host genetic factors should be identified, and their importance in cervical cancer induction should be determined. Although gene expression profiling studies in the last decade have made significant molecular findings about cervical cancer, adequate screening and effective treatment strategies have yet to be achieved. In the current study, meta-analysis was performed on cervical cancer-associated transcriptome data and reporter biomolecules were identified at RNA (mRNA, miRNA), protein (receptor, transcription factor, etc.), and metabolite levels by the integration of gene expression profiles with genome-scale biomolecular networks. This approach revealed already-known biomarkers, tumor suppressors and oncogenes in cervical cancer as well as various receptors (e.g. ephrin receptors EPHA4, EPHA5, and EPHB2; endothelin receptors EDNRA and EDNRB; nuclear receptors NCOA3, NR2C1, and NR2C2), miRNAs (e.g., miR-192-5p, miR-193b-3p, and miR-215-5p), transcription factors (particularly E2F4, ETS1, and CUTL1), other proteins (e.g., KAT2B, PARP1, CDK1, GSK3B, WNK1, and CRYAB), and metabolites (particularly, arachidonic acids) as novel biomarker candidates and potential therapeutic targets. The differential expression profiles of all reporter biomolecules were cross-validated in independent RNA-Seq and miRNA-Seq datasets, and the prognostic power of several reporter biomolecules, including KAT2B, PCNA, CD86, miR-192-5p and miR-215-5p was also demonstrated. In this study, we reported valuable data for further experimental and clinical efforts, because the proposed biomolecules have significant potential as systems biomarkers for screening or therapeutic purposes in cervical carcinoma.

Key signaling pathways, genes and transcription factors associated with hepatocellular carcinoma

The purpose of the present study was to investigate the underlying molecular mechanism of hepatocellular carcinoma (HCC) using bioinformatics approaches. The microarray dataset GSE64041 was downloaded from the Gene Expression Omnibus database, which included 60 tumor liver samples and 60 matched control samples. Differentially expressed genes (DEGs) between HCC and control groups were identified. Then functional enrichment analyses, protein‑protein interaction (PPI) network, sub‑network and integrated transcription factor (TF)‑microRNA (miRNA)‑target network analyses were performed for these DEGs. A total of 378 DEGs were obtained, including 101 upregulated and 277 downregulated DEGs. In addition, functional enrichment analysis for DEGs in the sub‑network revealed 'cell division' and 'cell cycle' as key Gene Ontology (GO) terms and pathways. Topoisomerase (DNA) IIα (TOP2A) and integrin subunit α2 (ITGA2) were hub nodes in the PPI network. TOP2A, cyclin dependent kinase 1 (CDK1) and polo like kinase 1 (PLK1) were revealed to be hub nodes in the sub‑network. Finally, 4 TFs including forkhead box M1 (FOXM1), E2F transcription factor 4 (E2F4), SIN3 transcription regulator family member A (SIN3A) and transcription factor 7 like 1 (TCF7L1) were obtained through integrated network analysis. TOP2A, ITGA2, PLK1 and CDK1 may be key genes involved in HCC development. 'Cell division' and 'cell cycle' were indicated to act as key GO terms and Kyoto Encyclopedia of Genes and Genomes pathways in HCC. In addition, FOXM1, TCF7L1, E2F4 and SIN3A were revealed to be key TFs associated with HCC.

Stressor-driven extracellular acidosis as tumor inducer via aberrant enzyme activation: A review on the mechanisms and possible prophylaxis

When the extracellular pH of human body vacillates in either direction, tissue homeostasis is compromised. Fluctuations in acidity have been linked to a wide variety of pathological conditions, including bone loss, cancer, allergies, and auto-immune diseases. Stress conditions affect oxygen tension, and the resultant hypoxia modulates the expression and/or activity of membrane-tethered transporters/pumps, transcription factors, enzymes and intercellular junctions. These modifications provoke erratic gene expression, aberrant tissue remodeling and oncogenesis. While the physiological optimization of pH in tissues is practically challenging, it is at least theoretically achievable and can be considered as a possible therapy to resolve a broad array of diseases.

In silico discovery of significant pathways in colorectal cancer metastasis using a two-stage optimisation approach

Accurate and reliable modelling of protein-protein interaction networks for complex diseases such as colorectal cancer can help better understand mechanism of diseases and potentially discover new drugs. Different machine learning methods such as empirical mode decomposition combined with least square support vector machine, and discrete Fourier transform have been widely utilised as a classifier and for automatic discovery of biomarkers for the diagnosis of the disease. The existing methods are, however, less efficient as they tend to ignore interaction with the classifier. In this study, the authors propose a two-stage optimisation approach to effectively select biomarkers and discover interactions among them. At the first stage, particle swarm optimisation (PSO) and differential evolution (DE) are used to optimise parameters of support vector machine recursive feature elimination algorithm, and dynamic Bayesian network is then used to predict temporal relationship between biomarkers across two time points. Results show that 18 and 25 biomarkers selected by PSO and DE-based approach, respectively, yields the same accuracy of 97.3% and F1-score of 97.7 and 97.6%, respectively. The stratified analysis reveals that Alpha-2-HS-glycoprotein was a dominant hub gene with multiple interactions to other genes including Fibrinogen alpha chain, which is also a potential biomarker for colorectal cancer.

MicroRNA‑135b regulates the stability of PTEN and promotes glycolysis by targeting USP13 in human colorectal cancers

Dysregulation of microRNAs has been reported to be involved in the progression of human colorectal cancers (CRCs). Loss of the adenomatous polyposis coli (APC) gene is a common initiating event in CRCs. PTEN inactivation by mutation or allelic loss also occurs in CRCs. miR‑135b was reported to be upregulated in CRCs and its overexpression was due to APC/β‑catenin and PTEN/PI3K pathway deregulation. APC was proven to be a target of miR‑135b and forms a feedback loop with miR‑135b. In the present study, we found that ubiquitin‑specific peptidase 13 (USP13) was a target of miR‑135b. miR‑135b downregulated the expression of USP13, and reduced the stability of PTEN. miR‑135b promoted cell proliferation and glycolysis that could be reversed by the overexpression of USP13 or PTEN. Moreover, knockdown of USP13 upregulated the levels of endogenous miR‑135b, but not those in CRC cells with PTEN mutation. The results showed positive feedback loops between miR‑135b and PTEN inactivation in CRCs.