Unravelling driver genes as potential therapeutic targets in ovarian cancer via integrated bioinformatics approach

Target-driven cancer therapy is a notable advancement in precision oncology that has been accompanied by substantial medical accomplishments. Ovarian cancer is a highly frequent neoplasm in women and exhibits significant genomic and clinical heterogeneity. In a previous publication, we presented an extensive bioinformatics study aimed at identifying specific biomarkers associated with ovarian cancer. The findings of the network analysis indicate the presence of a cluster of nine dysregulated hub genes that exhibited significance in the underlying biological processes and contributed to the initiation of ovarian cancer. Here in this research article, we are proceeding our previous research by taking all hub genes into consideration for further analysis. GEPIA2 was used to identify patterns in the expression of critical genes. The KM plotter analysis indicated that the out of all genes 5 genes are statistically significant. The cBioPortal platform was further used to investigate the frequency of genetic mutations across the board and how they affected the survival of the patients. Maximum mutation was reported by ELAVL2. In order to discover viable therapeutic candidates after competitive inhibition of ELAVL2 with small molecular drug complex, high throughput screening and docking studies were used. Five compounds were identified. Overall, our results suggest that the ELAV-like protein 2-ZINC03830554 complex was relatively stable during the molecular dynamic simulation. The five compounds that have been found can also be further examined as potential therapeutic possibilities. The combined findings suggest that ELAVL2, together with their genetic changes, can be investigated in therapeutic interventions for precision oncology, leveraging early diagnostics and target-driven therapy.

Individual frailty phenotype components and mortality in adults with type 2 diabetes: A UK Biobank study

AIMS

This study aimed to explore associations between frailty components and mortality and rank prognostic relevance of each frailty component in predicting mortality in adults with and without type 2 diabetes (T2D).

METHODS

We used data from the UK Biobank. Associations and prognostic discrimination of individual Fried's frailty components and the overall frailty status with all-cause and cardiovascular (CVD) mortality were investigated using Cox proportional-hazard models and C-index in adults with and without T2D.

RESULTS

In both populations the strongest association with all-cause mortality across all frailty components and overall frailty status was observed for slow walking pace (without T2D Hazard Ratio [HR] 2.25, 95 %CI: 2.12-2.38 and with T2D HR 1.95, 95 %CI: 1.67-2.28). Similarly, slow walking pace was associated with a greater risk of CVD mortality. The combination of T2D and slow walking pace had the strongest association with all-cause and CVD mortality, compared to the combination of T2D and other frailty components or overall frailty status. Slow walking pace also provided the greatest prognostic discrimination.

CONCLUSION

Slow walking pace has a stronger predictive factor for all-cause and CVD mortality compared to other frailty components and overall frailty status, especially when simultaneously present with T2D.

ErbB receptors as prognostic and therapeutic drug targets in bone and soft tissue sarcomas

ErbB receptors have been intensely studied to understand their importance in cancer biology and as therapeutic targets, and many ErbB inhibitors are now used in the clinical setting. A large number of studies have been conducted to examine the expression of ErbB family members in bone and soft tissue sarcomas, including osteosarcomas, synovial sarcomas, Ewing sarcomas, rhabdomyosarcomas, and so on. Nevertheless, the clinical implications of ErbB receptors remain elusive. To illustrate the potential of ErbB family members as prognostic and therapeutic drug targets in bone and soft tissue sarcomas, we summarized the molecular evidence and observations from clinical and basic trials.