RASD2 promotes the development and metastasis of uveal melanoma via enhancing glycolysis

Spatio-temporal analysis of toxigenic genes expression in the growing Bufo gargarizans based on RNA sequencing data

BACKGROUND

Bufo gargarizans Cantor, a widely distributed amphibian species in Asia, produces and releases toxins through its retroauricular and granular glands. Although various tissues have been sequenced, the molecular mechanisms underlying the toxin production remain unclear. To elucidate these mechanisms, abdominal skin (non-toxic secretory glands) and retroauricular gland (toxic secreting glands) samples were collected at different time points (3, 6, 12, 24, and 36 months) for RNA sequencing (RNA-seq) and analysis.

RESULTS

In comparison to the S group during the same period, a total of 3053, 3026, 1516, 1028, and 2061 differentially expressed genes (DEGs) were identified across five developmental stages. Gene Ontology (GO) analysis revealed that DEGs were primarily enriched in biological processes including cellular processes, single-organism processes, metabolic processes, and biological regulation. In terms of cellular components, the DEGs were predominantly localized in the cell and cell parts, whereas molecular function indicated significant enrichment in binding and catalytic activity. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that the metabolism and synthesis of various substances, such as lipid metabolism, cofactor and vitamin metabolism, tryptophan metabolism, steroid biosynthesis, and primary bile acid biosynthesis, were accompanied by the development of toads. Additionally, using trend analysis, we discovered candidate genes that were upregulated in the retroauricular glands during development, and the abundance of these genes in the abdominal skin was extremely low. Finally, we identified 26 genes that are likely to be involved in toxin production and that are likely to be involved in toxin anabolism.

CONCLUSION

Overall, these results provide new insights into the genes involved in toxin production in B. gargarizans, which will improve our understanding of the molecular mechanisms underlying toxigenic gene expression.

KIF22 promotes the proliferation and glycolysis of melanoma by activating EGFR/STAT3 signaling

OBJECTIVES

Melanoma is one of the leading causes of cancer death. Kinesin Family member 22 (KIF22) is essential for the invasion of melanoma cells, but the role and mechanism of KIF22 in the proliferation and glycolysis in melanoma remains unknown.

METHODS

KIF22 expression in melanoma tissues and the relationship between KIF22 high expression and overall survival rate in patients with melanoma were analyzed using the Tnmplot database. KIF22 expression in melanoma cells was examined by western blot. Then, KIF22 was silenced and CCK-8 assay, EDU staining and flow cytometry analysis were adopted for assessing cell proliferation and apoptosis. In addition, the glycolysis metabolism of melanoma cells was reflected by detecting Extracellular Acidification Rates (ECAR) and Oxygen Consumption Rates (OCR). The expression of proteins related to apoptosis, glycolysis and EGFR/STAT3 signaling was tested by western blot. Subsequently, melanoma cells were treated with EGF or Colivelin to further elucidate the regulatory effect of KIF22 on EGFR/STAT3 signaling.

RESULTS

KIF22 expression was notably upregulated in melanoma tissues and cells, and KIF22 high expression was associated with a poor prognosis. Moreover, KIF22 insufficiency suppressed proliferation and accelerated apoptosis of melanoma cells. Additionally, glycolysis was reduced by KIF22 depletion, evidenced by the decreased ECAR and increased OCR, accompanied by the downregulated expression of HK2, PKM2 and LDHA. Importantly, the impacts of KIF22 depletion on the progression of melanoma were partially attenuated after EGF or Colivelin treatment.

CONCLUSION

Collectively, KIF22 knockdown suppressed the proliferation and glycolysis and facilitated the apoptosis of melanoma cells by inactivating EGFR/STAT3 signaling.

A novel machine learning model based on ubiquitin-related gene pairs and clinical features to predict prognosis and treatment effect in colon adenocarcinoma

BACKGROUND

Ubiquitin and ubiquitin-like (UB/UBL) conjugations are essential post-translational modifications that contribute to cancer onset and advancement. In colon adenocarcinoma (COAD), nonetheless, the biological role, as well as the clinical value of ubiquitin-related genes (URGs), is unclear. The current study sought to design and verify a ubiquitin-related gene pairs (URGPs)-related prognostic signature for predicting COAD prognoses.

METHODS

Using univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression, URGP's predictive signature was discovered. Signatures differentiated high-risk and low-risk patients. ROC and Kaplan-Meier assessed URGPs' signature. Gene set enrichment analysis (GSEA) examined biological nomogram enrichment. Chemotherapy and tumor immune microenvironment were also studied.

RESULTS

The predictive signature used six URGPs. High-risk patients had a worse prognosis than low-risk patients, according to Kaplan-Meier. After adjusting for other clinical characteristics, the URGPs signature could reliably predict COAD patients. In the low-risk group, we found higher amounts of invading CD4 memory-activated T cells, follicular helper T cells, macrophages, and resting dendritic cells. Moreover, low-risk group had higher immune checkpoint-related gene expression and chemosensitivity.

CONCLUSION

Our research developed a nomogram and a URGPs prognostic signature to predict COAD prognosis, which may aid in patient risk stratification and offer an effective evaluation method of individualized treatment in clinical settings.