Exploring novel biomarkers and immunotherapeutic targets for biofeedback therapies to reveal the tumor-associated immune microenvironment through a multimetric analysis of kidney renal clear cell carcinoma.

BACKGROUND

Kidney renal clear cell carcinoma (KIRC) constitutes the primary subtype of renal cell carcinoma, representing 75% to 80% of cases and carrying a substantial cancer-specific mortality rate of up to 24%. Despite advancements in treatment options, KIRC displays notable resistance to conventional therapies, emphasizing the need for innovative targeted immunotherapeutic strategies. Chromatin regulators (CRs), pivotal proteins controlling gene expression and critical biological processes, play a crucial role in the initiation and progression of KIRC. This study employed a multi-omics approach to evaluate the impact of CR-associated genes on KIRC prognosis.

METHODS

The study utilized the TCGA-KIRC dataset and employed LASSO Cox regression to construct and validate a prognostic model that focuses on genes influencing KIRC prognosis. The research investigated interactions among gene characteristics, clinical parameters, the tumor microenvironment, targeted immunotherapy, and drug responsiveness. Experimental validation, encompassing various techniques such as cell culture, transient transfection, qPCR, Transwell assays, confirmed the robust predictive capability of the BRD9 gene.

RESULTS

The analysis identified the risk score of CRs as an independent factor determining KIRC prognosis. Furthermore, the study introduced a predictive Nomogram model that integrates clinical attributes and risk assessment. Significantly, BRD9 exhibited substantially elevated expression within KIRC cells, underscoring its role in driving cancer cell proliferation, invasion, and migration. These findings suggest the potential for tailored immunotherapy targeting BRD9 in the treatment of KIRC.

CONCLUSION

This study presents an innovative prognostic framework for KIRC based on multi-omics approaches, seamlessly incorporating CRs. This model holds promise for improving the accuracy of prognosis prediction for KIRC patients, laying a robust foundation for the development of targeted immunotherapies.