Predicting immune checkpoint therapy response in three independent metastatic melanoma cohorts

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; Aniel Sanchez

doi:10.3389/fonc.2024.1428182

Predicting immune checkpoint therapy response in three independent metastatic melanoma cohorts

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 WelinderA 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, Aniel Sanchez

^*Corresponding author for this work

Analytical Biochemistry

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Abstract

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.

Original language	English
Article number	1428182
Number of pages	16
Journal	Frontiers in Oncology
Volume	14
DOIs	https://doi.org/10.3389/fonc.2024.1428182
Publication status	Published - 2-Jul-2024

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Predicting immune checkpoint therapy response in three independent metastatic melanoma cohortsFinal publisher's version, 2.86 MBLicence: CC BY

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Szadai, L., Bartha, A., Parada, I. P., Lakatos, A. I. T., Pál, D. M. P., Lengyel, A. S., de Almeida, N. P., Jánosi, Á. J., Nogueira, F., Szeitz, B., Doma, V., Woldmar, N., Guedes, J., Ujfaludi, Z., Pahi, Z. G., Pankotai, T., Kim, Y., Győrffy, B., Baldetorp, B., ... Sanchez, A. (2024). Predicting immune checkpoint therapy response in three independent metastatic melanoma cohorts. Frontiers in Oncology, 14, Article 1428182. https://doi.org/10.3389/fonc.2024.1428182

@article{78e79ee7086a453ca28f2e593cc56e75,

title = "Predicting immune checkpoint therapy response in three independent metastatic melanoma cohorts",

abstract = "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.",

author = "Leticia Szadai and Aron Bartha and Parada, {Indira Pla} and Lakatos, {Alexandra I T} and P{\'a}l, {Dorottya M P} and Lengyel, {Anna S{\'a}ra} and {de Almeida}, {Nat{\'a}lia Pinto} and J{\'a}nosi, {{\'A}gnes Judit} and F{\'a}bio Nogueira and Beata Szeitz and Vikt{\'o}ria Doma and Nicole Woldmar and J{\'e}ssica Guedes and Zsuzsanna Ujfaludi and Pahi, {Zolt{\'a}n G{\'a}bor} and Tibor Pankotai and Yonghyo Kim and Bal{\'a}zs Gy{\H o}rffy and Bo Baldetorp and Charlotte Welinder and Szasz, {A Marcell} and Lazaro Betancourt and Jeovanis Gil and Roger Appelqvist and Kwon, {Ho Jeong} and Sarolta K{\'a}rp{\'a}ti and Magdalena Kuras and Murillo, {Jimmy Rodriguez} and N{\'e}meth, {Istv{\'a}n Bal{\'a}zs} and Johan Malm and David Feny{\"o} and Krzysztof Paw{\l}owski and Peter Horvatovich and Elisabet Wieslander and Kem{\'e}ny, {Lajos V} and Gilberto Domont and Gy{\"o}rgy Marko-Varga and Aniel Sanchez",

note = "Copyright {\textcopyright} 2024 Szadai, Bartha, Parada, Lakatos, P{\'a}l, Lengyel, de Almeida, J{\'a}nosi, Nogueira, Szeitz, Doma, Woldmar, Guedes, Ujfaludi, Pahi, Pankotai, Kim, Gy{\H o}rffy, Baldetorp, Welinder, Szasz, Betancourt, Gil, Appelqvist, Kwon, K{\'a}rp{\'a}ti, Kuras, Murillo, N{\'e}meth, Malm, Feny{\"o}, Paw{\l}owski, Horvatovich, Wieslander, Kem{\'e}ny, Domont, Marko-Varga and Sanchez.",

year = "2024",

month = jul,

day = "2",

doi = "10.3389/fonc.2024.1428182",

language = "English",

volume = "14",

journal = "Frontiers in Oncology",

issn = "2234-943X",

publisher = "Frontiers Media SA",

}

Szadai, L, Bartha, A, Parada, IP, Lakatos, AIT, Pál, DMP, Lengyel, AS, de Almeida, NP, Jánosi, ÁJ, Nogueira, F, Szeitz, B, Doma, V, Woldmar, N, Guedes, J, Ujfaludi, Z, Pahi, ZG, Pankotai, T, Kim, Y, Győrffy, B, Baldetorp, B, Welinder, C, Szasz, AM, Betancourt, L, Gil, J, Appelqvist, R, Kwon, HJ, Kárpáti, S, Kuras, M, Murillo, JR, Németh, IB, Malm, J, Fenyö, D, Pawłowski, K, Horvatovich, P, Wieslander, E, Kemény, LV, Domont, G, Marko-Varga, G & Sanchez, A 2024, 'Predicting immune checkpoint therapy response in three independent metastatic melanoma cohorts', Frontiers in Oncology, vol. 14, 1428182. https://doi.org/10.3389/fonc.2024.1428182

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 -

Predicting immune checkpoint therapy response in three independent metastatic melanoma cohorts

Abstract

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