Abstract 4617: Blood-based biomarkers for predicting treatment response to immune checkpoint inhibitors after EGFR-TKI resistance
Jun Hyeok Lim, Min Seok Park, Nuri Park, Yejin Cho, Sehan Kwak, Beom Seok Han, Minseo Lee, Donghyun Seo, Woo Kyung Ryu, Jeong‐Seon Ryu, Soon‐Sun Hong, Kyung Hee Jung
Abstract Background: Immune checkpoint inhibitors (ICIs) improve survival in advanced non-small cell lung cancer (NSCLC), but their benefits are limited in EGFR-mutant NSCLC. ICIs are often used after resistance to EGFR tyrosine kinase inhibitors (EGFR-TKIs). Since EGFR-TKI treatment alters the tumor microenvironment, predictive biomarkers for ICI response should ideally be identified post-EGFR-TKI resistance. However, obtaining re-biopsy samples is challenging. This study explores predictive biomarkers for ICI response using plasma samples collected before and after EGFR-TKI therapy. Methods: We retrospectively analyzed 28 EGFR-mutant NSCLC patients treated with ICIs at Inha University Hospital (2016-2023). All patients received first-line EGFR-TKI therapy and transitioned to ICIs after resistance. Plasma samples were collected before EGFR-TKI initiation and post-resistance. Ninety-six plasma proteins were quantified using the Olink Immuno-Oncology panel. PD-L1 expression in tumor tissues was assessed at diagnosis with SP263 or 22C3 assays. Progression-free survival (PFS) was defined as time from ICI initiation to progression. Responders were defined as PFS ≥6 months, and non-responders as PFS <6 months. Results: Among 28 patients, 25 had adenocarcinoma, 1 squamous cell carcinoma, 1 adenosquamous carcinoma, and 1 poorly differentiated NSCLC. EGFR mutations included exon 19 deletion (n=14), L858R (n=10), and uncommon mutations (n=4). First-line EGFR-TKIs included erlotinib (n=15), afatinib (n=9), and gefitinib (n=4). T790M mutations were identified in 11 patients, of whom 10 received osimertinib and 1 received lazertinib. ICIs included atezolizumab (n=15), pembrolizumab (n=5), and nivolumab (n=8). PD-L1 expression was evaluated in 23 patients using SP263 (5 negative, 15 with 1-49%, 3 with ≥50%) and in 22 patients using 22C3 (7 negative, 11 with 1-49%, 4 with ≥50%). Median PFS for ICIs was 2.7 months (95% CI: 1.7-3.7), with 6 responders and 22 non-responders. Plasma levels of IL-4, IL-6, GZMH, and Gal-9 differed significantly between responders and non-responders post-EGFR-TKI resistance. These findings were validated using tissue samples obtained post-resistance. Progression-free survival (PFS) showed significant differences according to plasma biomarker expression. Conclusions: Plasma samples collected after EGFR-TKI resistance can predict ICI responses in EGFR-mutant NSCLC. Post-resistance plasma biomarker levels may serve as a minimally invasive approach to guide therapeutic decisions in this challenging patient population. Citation Format: Jun Hyeok Lim, Min Seok Park, Nuri Park, Yejin Cho, Sehan Kwak, Beom Seok Han, Minseo Lee, Donghyun Seo, Woo Kyung Ryu, Jeong-Seon Ryu, Soon-sun Hong, Kyung Hee Jung. Blood-based biomarkers for predicting treatment response to immune checkpoint inhibitors after EGFR-TKI resistance [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 4617.
https://doi.org/10.1158/1538-7445.am2025-4617
Medicine
Oncology
Internal medicine
Immune checkpoint
Immune system
Immunology
Cancer
Immunotherapy
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