Aspects of the endothelin system in colorectal cancer

Mahdi, Mohamed R.; Bedeer, Raouf Fekry; Gabr, Abdel; Eltahry, Huda; Berger, Martin R.

doi:10.14748/bmr.v25.1042

Cited by 2 publications

(3 citation statements)

References 71 publications

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“…Huang, Wu (66) demonstrated that miR-485 directly suppresses EDNRA expression, thereby impeding the progression of esophageal squamous cell. In colon cancer, EDNRA was associated with advanced tumor grade and stage [67,68].Moreover, it has been that GNA14 has tumor promoting role in colon [69] and epithelial cell cancer [70]. Interesting, Oshima, Ishikawa (71) demonstrated that miR-485 inhibits GNA14 expression, attenuating the proliferation and metastasis of gastric cancer cells.…”

Section: Discussionmentioning

confidence: 99%

In silico analysis revealed the prognostic potential of a miRNA panel in lung carcinoma

Mohanad,

Fakhr Eldeen,

Shamloula

2024

Journal of Pharmaceutical Sciences and Drug Manufacturing

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Background. This research aims to identify potential prognostic biomarkers for squamous cell lung carcinoma (LUSC) by implementing bioinformatics tools to unveil the relationship between microRNAs (miRNAs) and LUSC, specifically by identifying the miRNAs and their critical target genes.Methods. We employed the Cancer Genome Atlas (TCGA)-LUSC dataset to identify differentially expressed miRNAs (DEmiRs) and genes (DEGs) utilizing R software. Subsequently, a lasso Cox regression survival model was developed to predict key prognostic DEmiRs. Their target genes were predicted using miRDB repository. Venn diagram was employed to identify the consensus genes shared between these target genes and DEGs in the TCGA-LUSC dataset. ClusetrProfiler analyzed Gene Ontology (GO) and KEGG pathways to comprehend these genes' biological functions. The STRING database and Cytoscape applications constructed the consensus gene proteinprotein interactions network.Results. Lasso model predicted 6 prognostic DEmiRs (hsa-miR1270, hsa-miR-1291, hsa-19b-2, hsa-miR-2277, hsa-miR-4791, hsa-miR-485) for LUSC with 96.67% sensitivity and 68.54% specificity. Venn diagram retrieved 906 consensus genes shared between DEGs and these 6 prognostic DEmiRs. These genes were mainly related to protein-binding, neuroactive ligand receptor interaction, retinoid metabolism, carcinogenesis, cell cycle, and system development. Network analysis in Cytoscape STRING applications identified 19 crucial genes (SDC4,

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Section: Discussionmentioning

confidence: 99%

In silico analysis revealed the prognostic potential of a miRNA panel in lung carcinoma

Mohanad,

Fakhr Eldeen,

Shamloula

2024

Journal of Pharmaceutical Sciences and Drug Manufacturing

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“…The endothelin system consists of endothelin-1 (EDN-1), endothelin-2 (EDN-2), endothelin-3 (EDN-3), the G-proteincoupled receptors, endothelin receptor type A (EDNRA) and endothelin receptor type B (EDNRB), endothelin converting enzyme 1 (ECE1), and endothelin converting enzyme 2 (ECE2) (Wang et al, 2013;Mahdi et al, 2014). Endothelin-1 has an enhancing effect on cancer cell proliferation, survival, invasion, and migration; it also has an effect on cancer stroma cells such as fibroblasts [proliferation, migration, contraction, extracellular matrix (ECM) remodeling], macrophages (chemo-attraction, ECM remodeling), and endothelial cells (proliferation, angiogenesis) (Bhalla et al, 2009).…”

Section: Discussionmentioning

confidence: 99%

“…Similarly, loss of EDN2 or EDN3 in rat colon mucosa indicates their use as early marker for colon cancer. Furthermore, increased EDNRA expression in CRC patients is correlated with increased tumor grade and reduced patient survival (Mahdi et al, 2014). Therefore, endothelin system members are considered as major regulating factors in cancer cell biology and cancer microenvironment and modulation of this gene system in cancer progression is an interesting topic of research.…”

Section: Discussionmentioning

confidence: 99%

Modulation of the Endothelin System in Colorectal Cancer Liver Metastasis: Influence of Epigenetic Mechanisms?

et al. 2020

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Targeting of endothelin system genes is a promising strategy in cancer therapy. The modulation of these genes was explored in a model of colorectal cancer (CRC) liver metastasis and in a panel of CRC tumor cell lines that were exposed to the demethylating agent decitabine. The CC531 rat model mimicking CRC liver metastasis was used for tumor cell re-isolation and analysis of the endothelin system genes and DNA methyltransferases (DNMTs) by microarray. To mimic the effects caused by methylation changes, a panel of seven CRC cell lines was treated with the demethylating agent decitabine. Three genes of the endothelin system were potently modulated at messenger RNA (mRNA) level in rat CC531 cells during liver colonization. The concomitant decrease of two DNMTs suggested an influence from altered methylation. Changes in gene expression were also accomplished by exposure of CRC cells to the demethylating agent decitabine, when using daily low concentrations for 3 days, with minimal cytotoxic effects. Sensitive human SW480 cells showed an almost 100fold upregulation of endothelin-1 mRNA compared to untreated cells. This, however, was different in LS174T cells, which showed no significant increase in gene expression although the methylation levels were significantly decreased at a variety of corresponding loci. We suggest that the mechanism induced by methylation on gene expression in metastatic CRC cells can be compromised. The results question the overall success of treating metastatic CRC by methylation inhibitors.

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Aspects of the endothelin system in colorectal cancer

Abstract: Endothelin system members including endothelin-1, endothelin-2, endothelin-3, endothelin receptors, and

Cited by 2 publications

References 71 publications

In silico analysis revealed the prognostic potential of a miRNA panel in lung carcinoma

In silico analysis revealed the prognostic potential of a miRNA panel in lung carcinoma

Modulation of the Endothelin System in Colorectal Cancer Liver Metastasis: Influence of Epigenetic Mechanisms?

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