Identification of the miRNA-mRNA regulatory pathways and a miR-21-5p based nomogram model in clear cell renal cell carcinoma

Prognostic Value of Tumor Tissue Up-regulated microRNAs in Clear Cell Renal Cell Carcinoma (ccRCC)

BACKGROUND/AIM

The management of patients with clear cell renal cell carcinoma (ccRCC) includes prognosis assessment based on TNM classification and biochemical markers. This approach stratifies patients with advanced ccRCC into groups of favorable, intermediate, and poor prognosis. The aim of the study was to improve prognosis estimation using microRNAs involved in the pathogenesis of ccRCC.

PATIENTS AND METHODS

The study was based on a histologically-verified set of matched ccRCC FFPE tissue samples (normal renal tissue, primary tumor, metastasis, n=20+20+20). The expression of 2,549 microRNAs was analyzed using the SurePrint G3 Human miRNA microarray kit (Agilent Technologies). Prognostic value of significantly deregulated microRNAs was further evaluated on microRNA expression and clinical data of 475 patients obtained from TCGA Kidney Clear Cell Carcinoma (KIRC) database.

RESULTS

There were 13 up-regulated and 6 down-regulated microRNAs in tumor tissues compared to control tissues. Among them, survival analysis revealed those with prognostic significance. Patients with high expression of miR-21, miR-27a, miR-34a, miR-106b, miR-210, and miR-342 showed significantly unfavorable outcome. The opposite was observed for miR-30e, patients with low expression had significantly shorter survival.

CONCLUSION

The inclusion of these microRNAs in a prognostic panel holds the potential to enhance stratification scoring systems, on which the treatment of ccRCC patients is based.

Hallmarks of cancer resistance

This review explores the hallmarks of cancer resistance, including drug efflux mediated by ATP-binding cassette (ABC) transporters, metabolic reprogramming characterized by the Warburg effect, and the dynamic interplay between cancer cells and mitochondria. The role of cancer stem cells (CSCs) in treatment resistance and the regulatory influence of non-coding RNAs, such as long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and circular RNAs (circRNAs), are studied. The chapter emphasizes future directions, encompassing advancements in immunotherapy, strategies to counter adaptive resistance, integration of artificial intelligence for predictive modeling, and the identification of biomarkers for personalized treatment. The comprehensive exploration of these hallmarks provides a foundation for innovative therapeutic approaches, aiming to navigate the complex landscape of cancer resistance and enhance patient outcomes.

The Versatile Role of miR-21 in Renal Homeostasis and Diseases

MicroRNAs (miRNAs) are small, non-coding RNA species that control gene expression and confer robustness to biological processes. Over the last two decades, their important roles during kidney development, homeostasis and the treatment of diseases have been established, in particular during the onset and progression of various forms of acute and chronic renal disorders. In recent years, miR-21, one of the best-characterized miRNAs to date, has received much attention in renal physiology in particular given its high degree of conservation and expression in kidneys, as well as its potent pathogenic role in various debilitating renal diseases. This review summarizes the current knowledge on miR-21’s involvement in both renal homeostasis and diseases, in particular its double-edged-sword role in acute versus chronic kidney injuries. Finally, we also discuss the potential of miR-21 as a biomarker and therapeutic target in renal diseases.

Prediction of the mechanism of miRNAs in laryngeal squamous cell carcinoma based on the miRNA-mRNA regulatory network

In this study, a bioinformatics analysis is conducted to screen differentially expressed miRNAs and mRNAs in laryngeal squamous cell carcinoma (LSCC). Based on this information, we explored the possible roles of miRNAs in the pathogenesis of LSCC. The RNA-Seq data from 79 laryngeal cancer samples in the Gene Expression Omnibus (GEO) database were sorted. Differentially expressed miRNAs and mRNAs in LSCC are screened using the PERL programming language, and it was analysed by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The miRNA-mRNA regulatory network of LSCC is constructed using Cytoscape software. Then, quantitative real-time PCR (QRT- PCR), Cell Counting Kit-8 (CCK8) and flow cytometry analysis we are used to further validate key miRNAs. We identified 99 differentially expressed miRNAs and 2,758 differentially expressed mRNAs in LSCC tissues from the GEO database. Four more important miRNAs displaying a high degree of connectivity are selected, these results suggest that they play an important role in the pathogenesis of LSCC. As shown in the present study, we identified specific miRNA-mRNA networks associated with the occurrence and development of LSCC through bioinformatics analysis. We found a miRNA molecule closely related to LSCC based on miRNA-mRNA network: miR-140-3p was down-regulated in LSCC. In addition, the potential antitumor effect of miR-140-3p in LSCC was verified in the experiment, and it was proved that overexpression of miR-140-3p could inhibit the proliferation of LSCC cells and promote cell apoptosis, suggesting that miR-140-3p may be a potential tumor marker in LSCC.