DNA methylation of RNA-binding protein for multiple splicing 2 functions as diagnosis biomarker in gastric cancer pathogenesis and its potential clinical significance

Hypertrophic cardiomyopathy in MYBPC3 carriers in aging

Hypertrophic cardiomyopathy (HCM) is characterized by abnormal thickening of the myocardium, leading to arrhythmias, heart failure, and elevated risk of sudden cardiac death, particularly among the young. This inherited disease is predominantly caused by mutations in sarcomeric genes, among which those in the cardiac myosin binding protein-C3 (MYBPC3) gene are major contributors. HCM associated with MYBPC3 mutations usually presents in the elderly and ranges from asymptomatic to symptomatic forms, affecting numerous cardiac functions and presenting significant health risks with a spectrum of clinical manifestations. Regulation of MYBPC3 expression involves various transcriptional and translational mechanisms, yet the destiny of mutant MYBPC3 mRNA and protein in late-onset HCM remains unclear. Pathogenesis related to MYBPC3 mutations includes nonsense-mediated decay, alternative splicing, and ubiquitin-proteasome system events, leading to allelic imbalance and haploinsufficiency. Aging further exacerbates the severity of HCM in carriers of MYBPC3 mutations. Advancements in high-throughput omics techniques have identified crucial molecular events and regulatory disruptions in cardiomyocytes expressing MYBPC3 variants. This review assesses the pathogenic mechanisms that promote late-onset HCM through the lens of transcriptional, post-transcriptional, and post-translational modulation of MYBPC3, underscoring its significance in HCM across carriers. The review also evaluates the influence of aging on these processes and MYBPC3 levels during HCM pathogenesis in the elderly. While pinpointing targets for novel medical interventions to conserve cardiac function remains challenging, the emergence of personalized omics offers promising avenues for future HCM treatments, particularly for late-onset cases.

Construction of novel 7 integrin-related gene signatures in thyroid cancer construction of model based on integrin genes

Advanced and metastatic THCA patients usually have a poor prognosis. Thus, this study aimed to establish a risk model to discriminate the high risk population. The expression and clinical data were obtained from TCGA database. The cluster analysis, lasso, univariate and multivariate cox analyses were used to construct risk model. K-M, ROC and DCA were applied to validate the efficiency and stability of the model. GO, KEGG, and ssGSEA analysis were performed to identify the potential mechanism of signatures. The 7-gene prognosis model was constructed, including FAM27E3, FIGN, GSTM4, BEX5, RBPMS2, PHF13, and DCSTAMP. ROC and DCA results showed our model had a better prognosis prediction performance than other risk models. The high risk score was associated with the poor prognosis of THCA patients with different clinical characteristics. The risk score was closely related to cell cycle. Further, we found that the expressions of signatures were significantly dysregulated in THCA and associated with prognosis. These gene expressions were affected by some clinical characteristics, methylation and CNV. Some signatures played a role in drug sensitivity and pathway activation. We constructed a 7-gene signature model based on the integrin-related genes, which showed a great prognostic value in THCA.

Identification of alternative splicing associated with clinical features: from pan-cancers to genitourinary tumors

Background

Alternative splicing events (ASEs) are vital causes of tumor heterogeneity in genitourinary tumors and many other cancers. However, the clinicopathological relevance of ASEs in cancers has not yet been comprehensively characterized.

Methods

By analyzing splicing data from the TCGA SpliceSeq database and phenotype data for all TCGA samples from the UCSC Xena database, we identified differential clinical feature-related ASEs in 33 tumors. CIBERSORT immune cell infiltration data from the TIMER2.0 database were used for differential clinical feature-related immune cell infiltration analysis. Gene function enrichment analysis was used to analyze the gene function of ASEs related to different clinical features in tumors. To reveal the regulatory mechanisms of ASEs, we integrated race-related ASEs and splicing quantitative trait loci (sQTLs) data in kidney renal clear cell carcinoma (KIRC) to comprehensively assess the impact of SNPs on ASEs. In addition, we predicted regulatory RNA binding proteins in bladder urothelial carcinoma (BLCA) based on the enrichment of motifs around alternative exons for ASEs.

Results

Alternative splicing differences were systematically analyzed between different groups of 58 clinical features in 33 cancers, and 30 clinical features in 24 cancer types were identified to be associated with more than 50 ASEs individually. The types of immune cell infiltration were found to be significantly different between subgroups of primary diagnosis and disease type. After integrating ASEs with sQTLs data, we found that 63 (58.9%) of the race-related ASEs were significantly SNP-correlated ASEs in KIRC. Gene function enrichment analyses showed that metastasis-related ASEs in KIRC mainly enriched Rho GTPase signaling pathways. Among those ASEs associated with metastasis, alternative splicing of GIT2 and TUBB3 might play key roles in tumor metastasis in KIRC patients. Finally, we identified several RNA binding proteins such as PCBP2, SNRNP70, and HuR, which might contribute to splicing differences between different groups of neoplasm grade in BLCA.

Conclusion

We demonstrated the significant clinical relevance of ASEs in multiple cancer types. Furthermore, we identified and validated alternative splicing of TUBB3 and RNA binding proteins such as PCBP2 as critical regulators in the progression of urogenital cancers.

Development of cancer-associated fibroblasts subtype and prognostic model in gastric cancer and the landscape of tumor microenvironment

As the components of the tumor microenvironment (TME), cancer-associated fibroblasts (CAFs) are inextricably linked to cancer development. However, the potential impact of CAFs on gastric cancer (GC) remains unclear, as does the relationship between clinical prognosis and immunotherapy. We identified the expression of genes associated with CAFs in 1050 gastric cancer samples from three independent datasets and assessed the correlation between CAFs and clinical characteristics, prognosis, and TME. The CRG-Score was developed and validated for predicting overall survival (OS) in gastric cancer patients and its applicability in immunotherapy. We explored the changes of CAFs-related genes (CRGs) in gastric cancer tissues and evaluated their expression patterns. Two molecular subtypes were identified, and the expression of CRGs was assessed among different subtypes in correlation with prognosis and TME characteristics. The CRG-Score was constructed using differentially expressed genes between the subtypes, and its predictive power was evaluated in gastric cancer patients. Additionally, we developed an accurate nomogram to increase the clinical practicality of CRG-Score. Furthermore, CRG-Score was significantly correlated with tumor mutation burden, microsatellite instability, cancer stem cells, and chemotherapeutic drug sensitivity. CRGs have the potential to influence prognosis, TME, and the clinical features of gastric cancer. This provided new possibilities for improving our understanding of gastric cancer, assessing prognosis, and more effective immunotherapeutic strategies.