Predicting immune checkpoint therapy response in three independent metastatic melanoma cohorts.

While Immune checkpoint inhibition (ICI) therapy shows significant efficacy in metastatic melanoma, only about 50% respond, lacking reliable predictive methods. We introduce a panel of six proteins aimed at predicting response to ICI therapy. Evaluating previously reported proteins in two untreated melanoma cohorts, we used a published predictive model (EaSIeR score) to identify potential proteins distinguishing responders and non-responders. Six proteins initially identified in the ICI cohort correlated with predicted response in the untreated cohort. Additionally, three proteins correlated with patient survival, both at the protein, and at the transcript levels, in an independent immunotherapy treated cohort. Our study identifies predictive biomarkers across three melanoma cohorts, suggesting their use in therapeutic decision-making.

Informations de copyright

Copyright © 2024 Szadai, Bartha, Parada, Lakatos, Pál, Lengyel, de Almeida, Jánosi, Nogueira, Szeitz, Doma, Woldmar, Guedes, Ujfaludi, Pahi, Pankotai, Kim, Győrffy, Baldetorp, Welinder, Szasz, Betancourt, Gil, Appelqvist, Kwon, Kárpáti, Kuras, Murillo, Németh, Malm, Fenyö, Pawłowski, Horvatovich, Wieslander, Kemény, Domont, Marko-Varga and Sanchez.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.