TP53/BRAF mutation as an aid in predicting response to immune-checkpoint inhibitor across multiple cancer types

Abstract

Immunotherapy with checkpoint inhibitors, such as PD-1/PD-L1 blockage, is becoming standard of practice for an increasing number of cancer types. However, the response rate is only 10%-40%. Thus, identifying biomarkers that could accurately predict the ICI-therapy response is critically important. We downloaded somatic mutation data for 46,697 patients and tumor-infiltrating immune cells levels data for 11070 patients, then combined TP53 and BRAF mutation status into a biomarker model and found that the predict ability of TP53/BRAF mutation model is more powerful than some past models. Commonly, patients with high-TMB status have better response to ICI therapy than patients with low-TMB status. However, the genotype of TP53^MUTBRAF^WT in high-TMB status cohort have poorer response to ICI therapy than the genotype of BRAF^MUTTP53^WT in low-TMB status (Median, 18 months vs 47 month). Thus, TP53/BRAF mutation model can add predictive value to TMB in identifying patients who benefited from ICI treatment, which can enable more informed treatment decisions.

Keywords: BRAF; TP53; immune-checkpoint inhibitor therapies; precision medicine; prognosis.