Frontiers in Immunology (Feb 2024)

Biological insights from plasma proteomics of non-small cell lung cancer patients treated with immunotherapy

  • Jair Bar,
  • Jair Bar,
  • Raya Leibowitz,
  • Raya Leibowitz,
  • Niels Reinmuth,
  • Niels Reinmuth,
  • Astrid Ammendola,
  • Eyal Jacob,
  • Mor Moskovitz,
  • Adva Levy-Barda,
  • Michal Lotem,
  • Rivka Katsenelson,
  • Abed Agbarya,
  • Mahmoud Abu-Amna,
  • Maya Gottfried,
  • Tatiana Harkovsky,
  • Ido Wolf,
  • Ella Tepper,
  • Gil Loewenthal,
  • Ben Yellin,
  • Yehuda Brody,
  • Nili Dahan,
  • Maya Yanko,
  • Coren Lahav,
  • Michal Harel,
  • Shani Raveh Shoval,
  • Yehonatan Elon,
  • Itamar Sela,
  • Adam P. Dicker,
  • Yuval Shaked

DOI
https://doi.org/10.3389/fimmu.2024.1364473
Journal volume & issue
Vol. 15

Abstract

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IntroductionImmune checkpoint inhibitors have made a paradigm shift in the treatment of non-small cell lung cancer (NSCLC). However, clinical response varies widely and robust predictive biomarkers for patient stratification are lacking. Here, we characterize early on-treatment proteomic changes in blood plasma to gain a better understanding of treatment response and resistance.MethodsPre-treatment (T0) and on-treatment (T1) plasma samples were collected from 225 NSCLC patients receiving PD-1/PD-L1 inhibitor-based regimens. Plasma was profiled using aptamer-based technology to quantify approximately 7000 plasma proteins per sample. Proteins displaying significant fold changes (T1:T0) were analyzed further to identify associations with clinical outcomes using clinical benefit and overall survival as endpoints. Bioinformatic analyses of upregulated proteins were performed to determine potential cell origins and enriched biological processes.ResultsThe levels of 142 proteins were significantly increased in the plasma of NSCLC patients following ICI-based treatments. Soluble PD-1 exhibited the highest increase, with a positive correlation to tumor PD-L1 status, and, in the ICI monotherapy dataset, an association with improved overall survival. Bioinformatic analysis of the ICI monotherapy dataset revealed a set of 30 upregulated proteins that formed a single, highly interconnected network, including CD8A connected to ten other proteins, suggestive of T cell activation during ICI treatment. Notably, the T cell-related network was detected regardless of clinical benefit. Lastly, circulating proteins of alveolar origin were identified as potential biomarkers of limited clinical benefit, possibly due to a link with cellular stress and lung damage.ConclusionsOur study provides insights into the biological processes activated during ICI-based therapy, highlighting the potential of plasma proteomics to identify mechanisms of therapy resistance and biomarkers for outcome.

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