预测三个独立转移性黑色素瘤队列中免疫检查点治疗的反应
Predicting immune checkpoint therapy response in three independent metastatic melanoma cohorts.
作者信息
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
机构信息
Department of Dermatology and Allergology, University of Szeged, Szeged, Hungary.
Department of Bioinformatics, Semmelweis University, Budapest, Hungary.
出版信息
Front Oncol. 2024 Jul 2;14:1428182. doi: 10.3389/fonc.2024.1428182. eCollection 2024.
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.
引言
虽然免疫检查点抑制（ICI）疗法在转移性黑色素瘤中显示出显著疗效，但只有约50%的患者有反应，缺乏可靠的预测方法。我们引入了一组六种蛋白质，旨在预测对ICI疗法的反应。
方法
在两个未经治疗的黑色素瘤队列中评估先前报道的蛋白质，我们使用已发表的预测模型（EaSIeR评分）来识别区分反应者和无反应者的潜在蛋白质。
结果
最初在ICI队列中鉴定出的六种蛋白质与未经治疗队列中的预测反应相关。此外，在一个独立的免疫治疗队列中，三种蛋白质在蛋白质水平和转录水平上均与患者生存相关。
讨论
我们的研究在三个黑色素瘤队列中鉴定出预测性生物标志物，表明它们可用于治疗决策。
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