Abstract 2058: Clinical and biological implications of plasma proteomic patterns in NSCLC patients treated with immune checkpoint inhibitors

Abstract Introduction: Immune checkpoint inhibitors (ICIs) offer significant benefits for patients with advanced non-small cell lung cancer (NSCLC). However, resistance to ICIs poses a major clinical hurdle. Recently, we described PROphet, a treatment guidance tool that predicts clinical benefit from ICI-based treatment using baseline plasma proteins termed ‘resistance-associated proteins’ (RAPs). Here, we conducted an in-depth bioinformatic analysis of RAPs to uncover the biological mechanisms underlying ICI resistance and their clinical relevance. Methods: 388 RAPs were analyzed using multiple bioinformatic and statistical tools. Putative tissue origins of the RAPs were explored using publicly available datasets. Enrichment analyses were performed to investigate RAP-related biological processes. Plasma proteomic data from healthy subjects (n=50) and NSCLC patients displaying clinical benefit (CB; n=76) or no CB (NCB; n=196) were compared to identify differential expression patterns between the three subpopulations. Results: RAPs were found to originate from both host and tumor tissues, with significant enrichment of lung cancer- and liver-associated proteins. A comparison of RAP expression levels in healthy, CB and NCB populations revealed five distinct expression patterns that provide mechanistic insights into treatment resistance. One such pattern characterized by higher RAP expression levels in healthy subjects compared to NSCLC patients included proteins associated with antitumor activities. Another pattern characterized by elevated RAP expression levels in the NCB population included multiple proteins associated with treatment resistance mechanisms such as angiogenesis, cell proliferation, immune modulation, and chemoresistance. Patient-specific scores based on these four resistance mechanisms revealed inter-patient diversity, highlighting the potential of RAP profiles for guiding personalized combination therapies. A protein-drug database screen showed that 17.5% of the RAPs could be targeted therapeutically, demonstrating that the RAP set is a rich source of additional potential therapeutic targets. Conclusions: The study provides insights into the biological processes associated with ICI resistance in patients with NSCLC and highlights the potential clinical value of RAP profiles for developing personalized therapies addressing resistance. Citation Format: Michal Harel,Nili Dahan,Coren Lahav,Eyal Jacob,Yehonatan Elon,Igor Puzanov,Ronan J. Kelly,Yuval Shaked,Raya Leibowitz,David P. Carbone,David R. Gandara,Adam P. Dicker. Clinical and biological implications of plasma proteomic patterns in NSCLC patients treated with immune checkpoint inhibitors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2058.

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Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-2058
Primary Topic
Cancer Immunotherapy and Biomarkers
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article
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article

Abstract 2058: Clinical and biological implications of plasma proteomic patterns in NSCLC patients treated with immune checkpoint inhibitors

Michal Harel, Coren Lahav, Yehonatan Elon, Nili Dahan et al.
Cancer Research
Cancer Immunotherapy and Biomarkers
article

Abstract 2058: Clinical and biological implications of plasma proteomic patterns in NSCLC patients treated with immune checkpoint inhibitors

Michal Harel, Coren Lahav, Yehonatan Elon, Nili Dahan, David R. Gandara, Raya Leibowitz‐Amit, Adam P. Dicker, Igor Puzanov, David P. Carbone, Ronan J. Kelly, Yuval Shaked, Eyal Jacob
article en

Abstract

Abstract Introduction: Immune checkpoint inhibitors (ICIs) offer significant benefits for patients with advanced non-small cell lung cancer (NSCLC). However, resistance to ICIs poses a major clinical hurdle. Recently, we described PROphet, a treatment guidance tool that predicts clinical benefit from ICI-based treatment using baseline plasma proteins termed ‘resistance-associated proteins’ (RAPs). Here, we conducted an in-depth bioinformatic analysis of RAPs to uncover the biological mechanisms underlying ICI resistance and their clinical relevance. Methods: 388 RAPs were analyzed using multiple bioinformatic and statistical tools. Putative tissue origins of the RAPs were explored using publicly available datasets. Enrichment analyses were performed to investigate RAP-related biological processes. Plasma proteomic data from healthy subjects (n=50) and NSCLC patients displaying clinical benefit (CB; n=76) or no CB (NCB; n=196) were compared to identify differential expression patterns between the three subpopulations. Results: RAPs were found to originate from both host and tumor tissues, with significant enrichment of lung cancer- and liver-associated proteins. A comparison of RAP expression levels in healthy, CB and NCB populations revealed five distinct expression patterns that provide mechanistic insights into treatment resistance. One such pattern characterized by higher RAP expression levels in healthy subjects compared to NSCLC patients included proteins associated with antitumor activities. Another pattern characterized by elevated RAP expression levels in the NCB population included multiple proteins associated with treatment resistance mechanisms such as angiogenesis, cell proliferation, immune modulation, and chemoresistance. Patient-specific scores based on these four resistance mechanisms revealed inter-patient diversity, highlighting the potential of RAP profiles for guiding personalized combination therapies. A protein-drug database screen showed that 17.5% of the RAPs could be targeted therapeutically, demonstrating that the RAP set is a rich source of additional potential therapeutic targets. Conclusions: The study provides insights into the biological processes associated with ICI resistance in patients with NSCLC and highlights the potential clinical value of RAP profiles for developing personalized therapies addressing resistance. Citation Format: Michal Harel,Nili Dahan,Coren Lahav,Eyal Jacob,Yehonatan Elon,Igor Puzanov,Ronan J. Kelly,Yuval Shaked,Raya Leibowitz,David P. Carbone,David R. Gandara,Adam P. Dicker. Clinical and biological implications of plasma proteomic patterns in NSCLC patients treated with immune checkpoint inhibitors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2058.

Cancer ResearchVol. 85(8_Supplement_1)
Roswell Park Comprehensive Cancer Center (US), Technion – Israel Institute of Technology (IL), Baylor University Medical Center (US), Assaf Harofeh Medical Center (IL), UC Davis Comprehensive Cancer Center, The Ohio State University (US), University of California, Davis (US)
Openalex Percentile: Top 88%
Cancer Immunotherapy and Biomarkers
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