AUTHOR=Szadai Leticia , Bartha Aron , Parada Indira Pla , Lakatos Alexandra I.T. , Pál Dorottya M.P. , Lengyel Anna Sára , de Almeida Natália Pinto , Jánosi Ágnes Judit , Nogueira Fábio , Szeitz Beata , Doma Viktória , Woldmar Nicole , Guedes Jéssica , Ujfaludi Zsuzsanna , Pahi Zoltán Gábor , Pankotai Tibor , Kim Yonghyo , Győrffy Balázs , Baldetorp Bo , Welinder Charlotte , Szasz A. Marcell , Betancourt Lazaro , Gil Jeovanis , Appelqvist Roger , Kwon Ho Jeong , Kárpáti Sarolta , Kuras Magdalena , Murillo Jimmy Rodriguez , Németh István Balázs , Malm Johan , Fenyö David , Pawłowski Krzysztof , Horvatovich Peter , Wieslander Elisabet , Kemény Lajos V. , Domont Gilberto , Marko-Varga György , Sanchez Aniel 

TITLE=Predicting immune checkpoint therapy response in three independent metastatic melanoma cohorts

JOURNAL=Frontiers in Oncology

VOLUME=14

YEAR=2024

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2024.1428182

DOI=10.3389/fonc.2024.1428182

ISSN=2234-943X

ABSTRACT=<sec><title>Introduction</title><p>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.</p></sec><sec><title>Methods</title><p>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.</p></sec><sec><title>Results</title><p>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.</p></sec><sec><title>Discussion</title><p>Our study identifies predictive biomarkers across three melanoma cohorts, suggesting their use in therapeutic decision-making.</p></sec>