Involvement of the glutamine RF‑amide peptide and its cognate receptor GPR103 in prostate cancer

An immune infiltration-related prognostic model of kidney renal clear cell carcinoma with two valuable markers: CAPN12 and MSC

Background

Since its discovery, clear cell renal cell carcinoma (ccRCC) has been the most prevalent and lethal kidney malignancy. Our research aims to identify possible prognostic genes of ccRCC and to develop efficient prognostic models for ccRCC patients based on multi-omics investigations to shed light on the treatment and prognosis of ccRCC.

Methods

To determine a risk score for each patient, we screened out differentially expressed genes using data from tumor samples, and control samples mined from The Cancer Genome Atlas (TCGA) and GTEx datasets. Somatic mutation and copy number variation profiles were analyzed to look for specific genomic changes connected to risk scores. To investigate potential functional relationships of prognostic genes, gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were carried out. We created a prognostic model by fusing risk ratings with other clinical variables. For validation, the 786-O cell line was used to carry out the dual-gRNA approach to knock down CAPN12 and MSC. This was followed by qRT-PCR to verify the knockdown of CAPN12 and MSC.

Results

For ccRCC, seven predictive genes were discovered: PVT1, MSC, ALDH6A1, TRIB3, QRFPR, CYS1, and CAPN12. The most enriched pathways in the GSVA study and GSEA analysis promote tumorigenesis and immune system modulation. The risk score derived from prognostic genes corresponds with immune infiltration cells and helps predict how well a medicine will work. The mutation of numerous oncogenes was also linked to a high-risk score. A prognostic model with a high ROC value was created for the risk score. An in vitro study demonstrates that the suppression of CAPN12 and MSC dramatically reduced the ability of 786-O cells to proliferate in the CCK-8 proliferation assay and plate clonality assays.

Conclusions

A thorough prognostic model with good performance has been developed for ccRCC patients using seven prognostic genes that were discovered to be related to ccRCC prognosis. In ccRCC, CAPN12 and MSC were significant indicators and would make good therapeutic targets.

Identification of Key Genes Related to the Obesity Patients with Osteoarthritis Based on Weighted Gene Coexpression Network Analysis (WGCNA)

Background. Increasing evidence has suggested that obesity affects the occurrence and progression of osteoarthritis (OA). However, the underlying molecular mechanism that obesity affects the course of OA is not fully understood and remains to be studied. Methods. The gene expression profiles of the GSE117999 and GSE98460 datasets were derived from the Gene Expression Omnibus (GEO) database. Firstly, we explored the correlation between obesity and OA using chi-square test. Next, weighted gene coexpression network analysis (WGCNA) was executed to identify obesity patients with OA- (obesity OA-) related genes in the GSE117999 dataset by “WGCNA” package. Moreover, differential expression analysis was performed to select the hub genes by “limma” package. Furthermore, ingenuity pathway analysis (IPA) and functional enrichment analysis (“clusterProfiler” package) were conducted to investigate the functions of genes. Finally, the regulatory networks of hub genes and protein-protein interaction (PPI) network were created by the Cytoscape 3.5.1 software and STRING. Results. A total of 15 differentially expressed obesity OA-related genes, including 9 lncRNAs and 6 protein coding genes, were detected by overlapping 66 differentially expressed genes (DEGs) between normal BMI samples and obesity OA samples and 451 obesity OA-related genes. Moreover, CCR10, LENG8, QRFPR, UHRF1BP1, and HLA-DRB4 were identified as hub genes. IPA results indicated that the hub genes were noticeably enriched in antimicrobial response, inflammatory response, and humoral immune response. PPI network showed that CCR10 interacted more with other proteins. Gene set enrichment analysis (GSEA) indicated that the hub genes were related to protein translation, cancer, chromatin modification, antigen processing, and presentation. Conclusion. Our results further demonstrated the role of obesity in OA and might provide new targets for the treatment of obesity OA.

Targeting Multiple Signaling Pathways in Cancer: The Rutin Therapeutic Approach

Multiple dysregulated signaling pathways are implicated in the pathogenesis of cancer. The conventional therapies used in cancer prevention/treatment suffer from low efficacy, considerable toxicity, and high cost. Hence, the discovery and development of novel multi-targeted agents to attenuate the dysregulated signaling in cancer is of great importance. In recent decades, phytochemicals from dietary and medicinal plants have been successfully introduced as alternative anticancer agents due to their ability to modulate numerous oncogenic and oncosuppressive signaling pathways. Rutin (also known as rutoside, quercetin-3-O-rutinoside and sophorin) is an active plant-derived flavonoid that is widely distributed in various vegetables, fruits, and medicinal plants, including asparagus, buckwheat, apricots, apples, cherries, grapes, grapefruit, plums, oranges, and tea. Rutin has been shown to target various inflammatory, apoptotic, autophagic, and angiogenic signaling mediators, including nuclear factor-κB, tumor necrosis factor-α, interleukins, light chain 3/Beclin, B cell lymphoma 2 (Bcl-2), Bcl-2 associated X protein, caspases, and vascular endothelial growth factor. A comprehensive and critical analysis of the anticancer potential of rutin and associated molecular targets amongst various cancer types has not been performed previously. Accordingly, the purpose of this review is to present an up-to-date and critical evaluation of multiple cellular and molecular mechanisms through which the anticancer effects of rutin are known to be exerted. The current challenges and limitations as well as future directions of research are also discussed.