1. Predicting immune checkpoint therapy response in three independent metastatic melanoma cohorts
- Author
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Leticia Szadai, Aron Bartha, Indira Pla Parada, Alexandra I.T. Lakatos, Dorottya M.P. Pál, Anna Sára Lengyel, Natália Pinto de Almeida, Ágnes Judit Jánosi, Fábio Nogueira, Beata Szeitz, Viktória Doma, Nicole Woldmar, Jéssica Guedes, Zsuzsanna Ujfaludi, Zoltán Gábor Pahi, Tibor Pankotai, Yonghyo Kim, Balázs Győrffy, Bo Baldetorp, Charlotte Welinder, A. Marcell Szasz, Lazaro Betancourt, Jeovanis Gil, Roger Appelqvist, Ho Jeong Kwon, Sarolta Kárpáti, Magdalena Kuras, Jimmy Rodriguez Murillo, István Balázs Németh, Johan Malm, David Fenyö, Krzysztof Pawłowski, Peter Horvatovich, Elisabet Wieslander, Lajos V. Kemény, Gilberto Domont, György Marko-Varga, and Aniel Sanchez
- Subjects
metastatic melanoma ,immunotherapy ,immunotherapy response ,responders ,non-responders ,proteomics ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
IntroductionWhile 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.MethodsEvaluating 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.ResultsSix 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.DiscussionOur study identifies predictive biomarkers across three melanoma cohorts, suggesting their use in therapeutic decision-making.
- Published
- 2024
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