TY - JOUR
T1 - Predicting immune checkpoint therapy response in three independent metastatic melanoma cohorts
AU - Szadai, Leticia
AU - Bartha, Aron
AU - Parada, Indira Pla
AU - Lakatos, Alexandra I T
AU - Pál, Dorottya M P
AU - Lengyel, Anna Sára
AU - de Almeida, Natália Pinto
AU - Jánosi, Ágnes Judit
AU - Nogueira, Fábio
AU - Szeitz, Beata
AU - Doma, Viktória
AU - Woldmar, Nicole
AU - Guedes, Jéssica
AU - Ujfaludi, Zsuzsanna
AU - Pahi, Zoltán Gábor
AU - Pankotai, Tibor
AU - Kim, Yonghyo
AU - Győrffy, Balázs
AU - Baldetorp, Bo
AU - Welinder, Charlotte
AU - Szasz, A Marcell
AU - Betancourt, Lazaro
AU - Gil, Jeovanis
AU - Appelqvist, Roger
AU - Kwon, Ho Jeong
AU - Kárpáti, Sarolta
AU - Kuras, Magdalena
AU - Murillo, Jimmy Rodriguez
AU - Németh, István Balázs
AU - Malm, Johan
AU - Fenyö, David
AU - Pawłowski, Krzysztof
AU - Horvatovich, Peter
AU - Wieslander, Elisabet
AU - Kemény, Lajos V
AU - Domont, Gilberto
AU - Marko-Varga, György
AU - Sanchez, Aniel
N1 - 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.
PY - 2024/7/2
Y1 - 2024/7/2
N2 - INTRODUCTION: 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.METHODS: 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.RESULTS: 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.DISCUSSION: Our study identifies predictive biomarkers across three melanoma cohorts, suggesting their use in therapeutic decision-making.
AB - INTRODUCTION: 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.METHODS: 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.RESULTS: 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.DISCUSSION: Our study identifies predictive biomarkers across three melanoma cohorts, suggesting their use in therapeutic decision-making.
U2 - 10.3389/fonc.2024.1428182
DO - 10.3389/fonc.2024.1428182
M3 - Article
C2 - 39015503
SN - 2234-943X
VL - 14
JO - Frontiers in Oncology
JF - Frontiers in Oncology
M1 - 1428182
ER -