CD24, NFIL3, FN1, and KLRK1 signature predicts melanoma immunotherapy response and survival.

Abstract

Melanoma poses a significant health concern due to its propensity to metastasize and its high mortality rate. Immunotherapy has emerged as a promising treatment strategy for harnessing the patient's immune system to fight tumor cells. However, not all patients respond equally to immunotherapy, highlighting the need for predictive biomarkers to identify potential responders and optimize treatment strategies. Using data from 579 immunology-related genes evaluated by the NanoString nCounter Human Immunology v2 Panel, we integrated transcriptomic data with the clinical characteristics of 35 individuals to develop a predictive signature for immunotherapy response in melanoma patients. Through comprehensive analysis, we identified 18 genes upregulated in non-responder patients and three upregulated in responder patients. In multivariate analysis, CD24, NFIL3, FN1, and KLRK1 were identified as key predictors with significant potential for forecasting treatment outcomes. We then calculated a score incorporating the expression levels of these genes. The score achieved high accuracy in discriminating responders from non-responders, with an area under the curve of 0.935 (p < 0.001). The signature was also significantly associated with progression-free survival, overall survival, and survival following immunotherapy (p < 0.001). The validation of the signature in two independent cohorts confirmed its robustness and applicability, with areas under the curve of 0.758 (p = 0.036) and 0.833 (p = 0.004), respectively. This study represents a significant advance in precision medicine for melanoma. By identifying patients unlikely to benefit from immunotherapy, our approach could help optimize treatment allocation and improve patient outcomes. KEY MESSAGES: Novel 4-gene signature predicts immunotherapy failure in melanoma. High accuracy for personalized treatment decisions. Signature associated with decreased survival for non-responders. Signature validated in independent cohorts, enhancing generalizability. Potential to tailor treatment strategies and avoid unnecessary burden to patients.