An Update on the Potential Roles of E2F Family Members in Colorectal Cancer

Potential Signature Therapeutic Biomarkers TOP2A, MAD2L1, and CDK1 in Colorectal Cancer: A Systems Biomedicine-Based Approach

Colorectal cancer is the third deadliest and fourth most diagnosed cancer. It is heterogeneously driven by varied mutations and mutagens, and thus, it is challenging for targeted therapy. The rapid advancement of high-throughput technology presents considerable opportunities for discovering new colon cancer biomarkers. In the present study, we have explored and identified the biomarkers based on molecular interactions. We curated cancer datasets that were not micro-dissected and performed gene expression analysis. The protein-protein interactions were curated, and a network was constructed for the up-regulated genes. The hub genes were analyzed using 12 different topological parameters. The correlation analysis selected TOP2A, CDK1, CCNB1, AURKA, and MAD2L1 as hub genes. Further, survival analysis was performed to determine the effectiveness of the hub gene on the patient's survival rate. Our findings explore various transcription factors such as E2F4, FOXM1, E2F6, MAX, and SIN3A, along with kinases CSNK2A1, MAPK14, CDK1, CDK4, and CDK2, as potential molecular signatures and aid researchers in understanding the pathophysiological mechanisms underlying CRC development and thus providing novel therapeutic and diagnostic recourse. Furthermore, investigating miRNAs, we focused on hsa-miR-215-5p, hsa-miR-192-5p, and hsa-miR-193b-3p due to their observed impact on a diverse set of colorectal cancer genes. Thereby, the current approach brings into light CRC- related genes at the RNA and protein levels that can potentially act as novel biomarkers opening doors to diagnostic and treatment purposes.

E2F transcription factors promote tumorigenicity in pancreatic ductal adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers with limited treatment options, illustrating an urgent need to identify new drugable targets in PDACs.

OBJECTIVE

Using the similarities between tumor development and normal embryonic development, which is accompanied by rapid cell expansion, we aimed to identify and characterize embryonic signaling pathways that were reinitiated during tumor formation and expansion.

METHODS AND RESULTS

Here, we report that the transcription factors E2F1 and E2F8 are potential key regulators in PDAC. E2F1 and E2F8 RNA expression is mainly localized in proliferating cells in the developing pancreas and in malignant ductal cells in PDAC. Silencing of E2F1 and E2F8 in PANC-1 pancreatic tumor cells inhibited cell proliferation and impaired cell spreading and migration. Moreover, loss of E2F1 also affected cell viability and apoptosis with E2F expression in PDAC tissues correlating with expression of apoptosis and mitosis pathway genes, suggesting that E2F factors promote cell cycle regulation and tumorigenesis in PDAC cells.

CONCLUSION

Our findings illustrate that E2F1 and E2F8 transcription factors are expressed in pancreatic progenitor and PDAC cells, where they contribute to tumor cell expansion by regulation of cell proliferation, viability, and cell migration making these genes attractive therapeutic targets and potential prognostic markers for pancreatic cancer.

The association of E2F1 and E2F2 single nucleotide polymorphisms with laryngeal squamous cell carcinoma pathomorphological features

BACKGROUND

Laryngeal squamous cell carcinoma (LSCC) is one of the most common types of cancer in the upper respiratory tract. It is well-known that it has a high mortality rate and poor prognosis in advanced stages. There are well-known risk factors for LSCC, though new specific and prognostic blood-based markers for LSCC development and prognosis are essential. The current study aimed to evaluate the impact of four different single nucleotide polymorphisms (SNPs), E2F1 (rs3213183 and rs3213180) and E2F2 (rs2075993 and rs3820028), on LSCC development, morphological features, and patient 5-year survival rate.

METHODS

A total of 200 LSCC patients and 200 controls were included in this study; both groups were matched by age and sex. In the present study, we analyzed four single nucleotide polymorphisms (SNPs) in the genes E2F1 (rs3213183 and rs3213180) and E2F2 (rs2075993 and rs3820028) and evaluated their associations with the risk of LSCC development, its clinical and morphological manifestation, and patients 5-year survival rate. Genotyping was carried out using RT-PCR.

RESULTS

None of the analyzed SNPs showed a direct association with LSCC development. E2F2 rs2075993 G allele carriers (OR = 4.589, 95% CI 1.050-20.051, p = 0.043) and rs3820028 A allele carriers (OR = 4.750, 95% CI 1.088-20.736, p = 0.038) had a statistically significantly higher risk for poor differentiated or undifferentiated LSCC than non-carriers. E2F1 rs3213180 GC heterozygotes were found to have a 3.7-fold increased risk for lymph node involvement (OR = 3.710, 95% CI 1.452-9.479, p = 0.006). There was no statistically significant association between investigated SNPs and patient 5-year survival rate.

CONCLUSIONS

The present study indicates that E2F2 rs2075993 and rs3820028 impact LSCC differentiation, whereas E2F1 rs3213180 - on lymph node involvement.

Expression patterns of E2Fs identify tumor microenvironment features in human gastric cancer

Objective

E2F transcription factors are associated with tumor development, but their underlying mechanisms in gastric cancer (GC) remain unclear. This study explored whether E2Fs determine the prognosis or immune and therapy responses of GC patients.

Methods

E2F regulation patterns from The Cancer Genome Atlas (TCGA) were systematically investigated and E2F patterns were correlated with the characteristics of cellular infiltration in the tumor microenvironment (TME). A principal component analysis was used to construct an E2F scoring model based on prognosis-related differential genes to quantify the E2F regulation of a single tumor. This scoring model was then tested in patient cohorts to predict effects of immunotherapy.

Results

Based on the expression profiles of E2F transcription factors in GC, two different regulatory patterns of E2F were identified. TME and survival differences emerged between the two clusters. Lower survival rates in the Cluster2 group were attributed to limited immune function due to stromal activation. The E2F scoring model was then constructed based on the E2F-related prognostic genes. Evidence supported the E2F score as an independent and effective prognostic factor and predictor of immunotherapy response. A gene-set analysis correlated E2F score with the characteristics of immune cell infiltration within the TME. The immunotherapy cohort database showed that patients with a higher E2F score demonstrated better survival and immune responses.

Conclusions

This study found that differences in GC prognosis might be related to the E2F patterns in the TME. The E2F scoring system developed in this study has practical value as a predictor of survival and treatment response in GC patients.

Cell cycle protein BORA is associated with colorectal cancer progression by AURORA-PLK1 cascades: a bioinformatics analysis

Colorectal cancer (CRC) is the third most diagnosed cancer in the world. A better understanding of the molecular mechanism of CRC is essential for making novel strategies for the CRC management and its prevention. The present study aims to explore the molecular mechanism through integrated bioinformatics analysis by analyzing genes and their co-expression pattern in normal and CRC states. GSE110223, GSE110224 and GSE113513 gene expression profiles were analyzed in this study. The co-expression networks for normal and tumor samples were constructed separately and analyzed to identify the modules, sub-networks and key genes. Gene regulatory network analysis was done to understand the regulatory mechanism of selected genes. Survival analysis was performed for the identified sub-networks and key genes to understand their role in CRC progression. A total of seven modules were detected and the KEGG pathway analysis revealed these modules were mainly enriched with cell cycle, metabolism and signaling-related pathways. E2F6 and ETV4 transcription factors regulating the activity of multiple genes of identified modules were found to be up-regulated in CRC. Six Sub-networks and seven key genes, BORA, CCT7, DTL, RUVBL1, RUVBL2, THEM6 and TMEM97 associated with the CRC progression were identified. Disease-gene association analysis identified a novel association of the BORA gene with CRC that activates and regulates the AURORA-PLK1 cascades in the cell cycle. Survival analysis indicates that the overexpressed BORA is associated with unfavourable overall survival in CRC. The mechanistic role of BORA in the regulation of cell cycle progression suggests that BORA might act as a potential therapeutic target for CRC.

A novel investigation into an E2F transcription factor-related prognostic model with seven signatures for colon cancer patients

The pathogenesis of colon cancer, a common gastrointestinal tumour, involves complicated factors, especially a series of cell cycle-related genes. E2F transcription factors during the cell cycle play an essential role in the occurrence of colon cancer. It is meaningful to establish an efficient prognostic model of colon cancer targeting cellular E2F-associated genes. This has not been reported previously. The authors first aimed to explore the links of E2F genes with the clinical outcomes of colon cancer patients by integrating data from the TCGA-COAD (n = 521), GSE17536 (n = 177) and GSE39582 (n = 585) cohorts. The Cox regression and Lasso modelling approach to identify a novel colon cancer prognostic model involving several hub genes (CDKN2A, GSPT1, PNN, POLD3, PPP1R8, PTTG1 and RFC1) were utilised. Moreover, an E2F-related nomogram that efficiently predicted the survival rates of colon cancer patients was created. Additionally, the authors first identified two E2F tumour clusters, which showed distinct prognostic features. Interestingly, the potential links of E2F-based classification and 'protein secretion' issues of multiorgans and tumour infiltration of 'T-cell regulatory (Tregs)' and 'CD56dim natural killer cell' were detected. The authors' findings are of potential clinical significance for the prognosis assessment and mechanistic exploration of colon cancer.

Novel biomarkers for neoplastic progression from ulcerative colitis to colorectal cancer: a systems biology approach

In recent studies, the void of evaluation and in-depth understanding of unknown clinically relevant potential molecular biomarkers involved in colorectal cancer (CRC) from the inflammatory stage of ulcerative colitis (UC) to CRC metastasis, which can be suitable therapeutic targets, is deeply felt. The regulation and interaction among different cancer-promoting molecules, including messenger RNAs (mRNAs) and micro RNAs (miRNAs) in CRC and its progression, were the aim we pursued in this study. Using microarray data, we investigated the differential expression for five datasets, including mRNA and microRNA samples related to UC, tumor/normal. Then, using robust data analysis, separate lists of differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) were identified, which were used for robust rank aggregation (RRA) and co-expression network analysis. Then, comprehensive computational systems biology analyses, including gene ontology and Kyoto encyclopedia of genes and genomic pathway enrichment analyses, mRNA-miRNA regulatory network, and survival analysis, were employed to achieve the aim of this study. Finally, we used clinical samples to validate this potential and new target. According to this systems biology approach, a total of 98 DEGs and 8 DEmiRNAs with common differential expression were identified. By combining the distinct results of RRA and network, several potential therapeutic targets, and predictive and prognostic biomarkers for UC and CRC were identified. These targets include six common hub genes, CXCL1, CXCL8, MMP7, SLCA16A9, PLAU, and TIMP1, which are upregulated. Among these, the important and new biomarker SLC16A9 is negatively regulated by hsa-mir-194-5p, and hsa-miR-378a-5p take. The findings of the present study provide new insight into the pathogenesis of CRC in UC. Our study suggests future evaluation of the functional role of SLC16A9 and hsa-mir-194-5p and hsa-miR-378a-5p in CRC development.

Identification of functional gene modules by integrating multi-omics data and known molecular interactions

Multi-omics data integration has emerged as a promising approach to identify patient subgroups. However, in terms of grouping genes (or gene products) into co-expression modules, data integration methods suffer from two main drawbacks. First, most existing methods only consider genes or samples measured in all different datasets. Second, known molecular interactions (e.g., transcriptional regulatory interactions, protein-protein interactions and biological pathways) cannot be utilized to assist in module detection. Herein, we present a novel data integration framework, Correlation-based Local Approximation of Membership (CLAM), which provides two methodological innovations to address these limitations: 1) constructing a trans-omics neighborhood matrix by integrating multi-omics datasets and known molecular interactions, and 2) using a local approximation procedure to define gene modules from the matrix. Applying Correlation-based Local Approximation of Membership to human colorectal cancer (CRC) and mouse B-cell differentiation multi-omics data obtained from The Cancer Genome Atlas (TCGA), Clinical Proteomics Tumor Analysis Consortium (CPTAC), Gene Expression Omnibus (GEO) and ProteomeXchange database, we demonstrated its superior ability to recover biologically relevant modules and gene ontology (GO) terms. Further investigation of the colorectal cancer modules revealed numerous transcription factors and KEGG pathways that played crucial roles in colorectal cancer progression. Module-based survival analysis constructed four survival-related networks in which pairwise gene correlations were significantly correlated with colorectal cancer patient survival. Overall, the series of evaluations demonstrated the great potential of Correlation-based Local Approximation of Membership for identifying modular biomarkers for complex diseases. We implemented Correlation-based Local Approximation of Membership as a user-friendly application available at https://github.com/free1234hm/CLAM.

High Expression of E2F4 Is an Adverse Prognostic Factor and Related to Immune Infiltration in Oral Squamous Cell Carcinoma

Background

We aimed to evaluate the prognostic value of E2F4 expression in oral squamous cell carcinoma (OSCC) and clarify its influence on immune cell infiltration and biological functions.

Methods

The Cancer Genome Atlas (TCGA) database, the STRING database, and related online tools as well as single-sample gene set enrichment analysis (ssGSEA) were used for the analyses in our study.

Results

The E2F4 expression was elevated in OSCC tumor tissue compared with paracancerous tissues. The high expression of E2F4 was closely related to the poorer overall survival, disease-free survival, and progression-free interval of OSCC. In addition, pathway enrichment analyses revealed that the top 49 genes most closely related to E2F4 were strongly associated with the cell cycle. E2F4-related proteins were closely related to the following KEGG pathways: cell cycle, cellular senescence, PI3K-Akt signaling pathway, Wnt signaling pathway, and notch signaling pathway. It was also demonstrated that the E2F4 expression was negatively correlated with immune purity and strongly related to immune cell infiltration in OSCC.

Conclusions

E2F4 can be used as a novel biomarker for the diagnosis and prognosis of OSCC.

E2F1 promotes cell cycle progression by stabilizing spindle fiber in colorectal cancer cells

BACKGROUND

E2F1 is a transcription factor that regulates cell cycle progression. It is highly expressed in most cancer cells and activates transcription of cell cycle-related kinases. Stathmin1 and transforming acidic coiled-coil-containing protein 3 (TACC3) are factors that enhance the stability of spindle fiber.

METHODS

The E2F1-mediated transcription of transforming acidic coiled-coil-containing protein 3 (TACC3) and stathmin1 was examined using the Cancer Genome Atlas (TCGA) analysis, quantitative polymerase chain reaction (qPCR), immunoblotting, chromatin immunoprecipitation (ChIP), and luciferase reporter. Protein-protein interaction was studied using co-IP. The spindle structure was shown by immunofluorescence. Phenotype experiments were performed through MTS assay, flow cytometry, and tumor xenografts. Clinical colorectal cancer (CRC) specimens were analyzed based on immunohistochemistry.

RESULTS

The present study showed that E2F1 expression correlates positively with the expression levels of stathmin1 and TACC3 in colorectal cancer (CRC) tissues, and that E2F1 transactivates stathmin1 and TACC3 in CRC cells. Furthermore, protein kinase A (PKA)-mediated phosphorylation of stathmin1 at Ser16 is essential to the phosphorylation of TACC3 at Ser558, facilitating the assembly of TACC3/clathrin/α-tubulin complexes during spindle formation. Overexpression of Ser16-mutated stathmin1, as well as knockdown of stathmin1 or TACC3, lead to ectopic spindle poles including disorganized and multipolar spindles. Overexpression of wild-type but not Ser16-mutated stathmin1 promotes cell proliferation in vitro and tumor growth in vivo. Consistently, a high level of E2F1, stathmin1, or TACC3 not only associates with tumor size, lymph node metastasis, TNM stage, and distant metastasis, but predicts poor survival in CRC patients.

CONCLUSIONS

E2F1 drives the cell cycle of CRC by promoting spindle assembly, in which E2F1-induced stathmin1 and TACC3 enhance the stability of spindle fiber.

E2F3 gene expression is a potential negative prognostic marker for localised and MYCN not-amplified neuroblastoma: Results of in silico analysis of 786 samples

BACKGROUND

Neuroblastoma (NB) is an enigmatic childhood malignancy characterised by a wide range of clinical behaviour. Many potential oncogenes for NB have recently been identified. Among them, E2 transcription factor 3 (E2F3) expression was associated with a poor survival in 134 stage 4S patients, but evidence for other stage groups remains poorly investigated.

METHODS

We have analysed the expression of E2F3 gene from a database of 786 NB samples. Overall and event-free survivals (EFS) were assessed by the Kaplan-Meier method, splitting the data on the median and tertile expression values. The Cox model was applied to control for the confounding by stage, age and MYCN amplification. Validation was performed by an in silico analysis of an independent cohort of 283 NB patients. Furthermore, an immunofluorescence analysis on 48 formalin-fixed, paraffin-embedded NB specimens was also performed.

RESULTS

E2F3 overexpression was associated with a poor survival (EFS = 84%, 95% CI: 79%-95%, for low expression levels; EFS = 62%, 95% CI: 56%-68% for middle levels; EFS = 30%, 95% CI: 24%-36%, for high levels, p < .001). This association was confirmed in multivariable analysis and was more evident in patients with MYCN not-amplified and localised stages. Immunofluorescence results and the validation on an independent cohort of NB primary samples confirmed these findings.

CONCLUSIONS

E2F3 is a new potential prognostic marker in NB with favourable characteristics at diagnosis. Further studies are needed to elucidate the potential role of E2F3 in NB oncogenesis and progression, in order to identify new targets for therapeutic interventions.

E2F transcription factor 1 (E2F1) promotes the transforming growth factor TGF-β1 induced human cardiac fibroblasts differentiation through promoting the transcription of CCNE2 gene

The differentiation of cardiac fibroblast to myofibroblast is the key process of cardiac fibrosis. In the study, we aimed to determine the function of E2F Transcription Factor 1 (E2F1) in human cardiac fibroblasts (HCFs) differentiation, search for its downstream genes and elucidate the function of them in HCFs differentiation. As a result, we found that E2F1 was up-regulated in TGF-β1-induced HCFs differentiation. Silencing the expression of E2F1 by siRNA in HCFs, we found that the expression of differentiation-related genes (Collagen-1, α-Smooth muscle actin, and Fibronectin-1) was significantly suppressed, combining with proliferation and migration assay, we determined that HCFs differentiation was decreased. Luciferase report assay and immunoprecipitation proved that the oncogene CCNE2 was a direct target gene of E2F1, overexpression of CCNE2 was found in differentiated HCFs, silencing the expression of CCNE2 by siRNA decreased HCFs differentiation. Our research suggested that E2F1 and its downstream target gene CCNE2 play a vital role in TGF-β1-induced HCFs differentiation, thus E2F1 and CCNE2 may be a potential therapeutic target for cardiac fibrosis.