ImmunoDriver-1: Driver alterations (dAlts) and their immunological implications in early and metastatic non-small cell lung cancer (NSCLC).

8060 Background: NSCLC treatments and clinical trials include targeted agents and immunotherapy (IO) across stages, yet dAlts and how they relate to the tumor immune microenvironment (TIME) are incompletely characterized in early NSCLC (eNSCLC; stage I-III) and metastatic NSCLC (mNSCLC; stage IV). Here, we evaluated the NSCLC TIME by dAlt status to inform IO biomarker strategies. Methods: From the Tempus Database, we selected de-identified lung adenocarcinoma samples sequenced by xT DNA assay (eNSCLC n=5,535; mNSCLC n=10,299), a subset with whole transcriptome analysis. Targetable dAlts were defined as classic (c) (L858R and exon 19 del) or non-classic (nc) EGFR , KRAS G12C, other non-G12C variants, other guideline defined dAlts (ALK, ROS1, RET, NTRK1-3 fusions, ERBB2 alt, METex14), or no dAlt. Immune cell proportions were estimated by quanTIseq. Additional markers, PD-L1 TPS (IHC) and TMB (mt/mB; DNAseq) were analyzed. Significance (p&lt;0.05) was assessed using χ 2 or Wilcoxon/Kruskal-Wallis rank sum tests. Results: The dAlt prevalence was similar (|Δ| &lt; 2%) across early and late stage (Overall %: cEGFR=13, ncEGFR=2.9, KRAS G12C=15 and KRASother=22). The prevalence of other dAlt were less than 4% across stages. The CD8 proportion was higher in eNSCLC than mNSCLC (p&lt;0.001). Across stages, CD4 Treg and CD8 proportions in the KRAS G12C cohort were nearly identical to the non-dAlt cohort, while c/nc EGFR tumors exhibited the lowest percentage of CD8 cells and higher Tregs cells compared to non-dAlt tumors (Table). PD-L1 and TMB were similar between KRAS G12C and non-dAlt tumors and lowest among c/nc EGFR (Table). Conclusions: This real-world analysis demonstrated similar dAlt prevalence across eNSCLC and mNSCLC, while the TIME was distinct across stage and dAlts. The TIME of KRAS G12C tumors was similar to non-dAlt tumors, and was least immunogenic in the c/nc EGFR cohort. These findings highlight immunological differences across stages and dAlts that should be considered when developing IO strategies. Group IO marker Overall No dAlt cEGFR ncEGFR KRAS G12C KRAS other Other dAlt eNSCLC % CD8 cells 1 * 1.3 (0.5, 2.4) 1.4 (0.6, 2.8) 0.9 (0.4, 1.7) 1.0 (0.5, 1.9) 1.4 (0.6, 2.6) 1.3 (0.5, 2.4) 1.1 (0.5, 2.1) % Tregs 1 * 6.9 (4.8, 9.2) 6.3 (4.2, 8.8) 7.4 (5.6, 9.4) 8.2 (5.8, 10.3) 7.0 (5.1, 9.3) 7.1 (5.2, 9.3) 6.7 (4.6, 8.6) % PDL1 2 * 22 20 9.3 7.9 31 25 24 TMB* 5.8 (3.2, 9.5) 7.9 (3.7, 13.2) 3.2 (2.1, 4.7 4.2 (2.3, 6.3) 6.8 (4.2, 10.0) 5.8 (3.7, 8.9) 3.2 (1.6, 5.3) mNSCLC % CD8 cells 1 * 0.6 (0.04, 1.6) 0.8 (0.1, 1.9) 0.4 (0.0, 1.3) 0.5 (0.0, 1.5) 0.7 (0.1, 1.7) 0.5 (0.01, 1.5) 0.5 (0.0, 1.4) %Tregs 1 * 4.0 (2.6, 5.9) 3.8 (2.4, 5.6) 4.2 (2.9, 6.1) 4.7 (3.0, 6.8) 4.2 (2.7, 6.0) 4.0 (2.6, 6.0) 3.9 (2.6, 5.6) % PDL1 2 * 28 24 15 17 37 34 34 TMB* 5.8 (3.2, 10.0) 7.9 (4.2, 13.1) <jats:td colspan="1" rowspan=

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Journal
Journal of Clinical Oncology
Published
2025-05-28
DOI
https://doi.org/10.1200/jco.2025.43.16_suppl.8060
Primary Topic
Immunotherapy and Immune Responses
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article
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article

ImmunoDriver-1: Driver alterations (dAlts) and their immunological implications in early and metastatic non-small cell lung cancer (NSCLC).

Arjan Gower, Jay M. Lee, Paul C. Boutros, Jacob Mercer et al.
Journal of Clinical Oncology
Immunotherapy and Immune Responses
article

ImmunoDriver-1: Driver alterations (dAlts) and their immunological implications in early and metastatic non-small cell lung cancer (NSCLC).

Arjan Gower, Jay M. Lee, Paul C. Boutros, Jacob Mercer, Stamatina Fragkogianni, Amy L. Cummings, Brooke Rhead, Michael A. Thompson, Jonathan Wade Goldman, Maria A. Velez, Edward B. Garon, Carlo Enrico Traverso, Aaron Elliott Lisberg, Steven M. Dubinett, E. S. Williams
article en

Abstract

8060 Background: NSCLC treatments and clinical trials include targeted agents and immunotherapy (IO) across stages, yet dAlts and how they relate to the tumor immune microenvironment (TIME) are incompletely characterized in early NSCLC (eNSCLC; stage I-III) and metastatic NSCLC (mNSCLC; stage IV). Here, we evaluated the NSCLC TIME by dAlt status to inform IO biomarker strategies. Methods: From the Tempus Database, we selected de-identified lung adenocarcinoma samples sequenced by xT DNA assay (eNSCLC n=5,535; mNSCLC n=10,299), a subset with whole transcriptome analysis. Targetable dAlts were defined as classic (c) (L858R and exon 19 del) or non-classic (nc) EGFR , KRAS G12C, other non-G12C variants, other guideline defined dAlts (ALK, ROS1, RET, NTRK1-3 fusions, ERBB2 alt, METex14), or no dAlt. Immune cell proportions were estimated by quanTIseq. Additional markers, PD-L1 TPS (IHC) and TMB (mt/mB; DNAseq) were analyzed. Significance (p&lt;0.05) was assessed using χ 2 or Wilcoxon/Kruskal-Wallis rank sum tests. Results: The dAlt prevalence was similar (|Δ| &lt; 2%) across early and late stage (Overall %: cEGFR=13, ncEGFR=2.9, KRAS G12C=15 and KRASother=22). The prevalence of other dAlt were less than 4% across stages. The CD8 proportion was higher in eNSCLC than mNSCLC (p&lt;0.001). Across stages, CD4 Treg and CD8 proportions in the KRAS G12C cohort were nearly identical to the non-dAlt cohort, while c/nc EGFR tumors exhibited the lowest percentage of CD8 cells and higher Tregs cells compared to non-dAlt tumors (Table). PD-L1 and TMB were similar between KRAS G12C and non-dAlt tumors and lowest among c/nc EGFR (Table). Conclusions: This real-world analysis demonstrated similar dAlt prevalence across eNSCLC and mNSCLC, while the TIME was distinct across stage and dAlts. The TIME of KRAS G12C tumors was similar to non-dAlt tumors, and was least immunogenic in the c/nc EGFR cohort. These findings highlight immunological differences across stages and dAlts that should be considered when developing IO strategies. Group IO marker Overall No dAlt cEGFR ncEGFR KRAS G12C KRAS other Other dAlt eNSCLC % CD8 cells 1 * 1.3 (0.5, 2.4) 1.4 (0.6, 2.8) 0.9 (0.4, 1.7) 1.0 (0.5, 1.9) 1.4 (0.6, 2.6) 1.3 (0.5, 2.4) 1.1 (0.5, 2.1) % Tregs 1 * 6.9 (4.8, 9.2) 6.3 (4.2, 8.8) 7.4 (5.6, 9.4) 8.2 (5.8, 10.3) 7.0 (5.1, 9.3) 7.1 (5.2, 9.3) 6.7 (4.6, 8.6) % PDL1 2 * 22 20 9.3 7.9 31 25 24 TMB* 5.8 (3.2, 9.5) 7.9 (3.7, 13.2) 3.2 (2.1, 4.7 4.2 (2.3, 6.3) 6.8 (4.2, 10.0) 5.8 (3.7, 8.9) 3.2 (1.6, 5.3) mNSCLC % CD8 cells 1 * 0.6 (0.04, 1.6) 0.8 (0.1, 1.9) 0.4 (0.0, 1.3) 0.5 (0.0, 1.5) 0.7 (0.1, 1.7) 0.5 (0.01, 1.5) 0.5 (0.0, 1.4) %Tregs 1 * 4.0 (2.6, 5.9) 3.8 (2.4, 5.6) 4.2 (2.9, 6.1) 4.7 (3.0, 6.8) 4.2 (2.7, 6.0) 4.0 (2.6, 6.0) 3.9 (2.6, 5.6) % PDL1 2 * 28 24 15 17 37 34 34 TMB* 5.8 (3.2, 10.0) 7.9 (4.2, 13.1) <jats:td colspan="1" rowspan=

Journal of Clinical OncologyVol. 43(16_suppl)
University of California, Los Angeles (US), Tempus Labs (United States) (US), UCLA Jonsson Comprehensive Cancer Center
Openalex Percentile: Top 87%
Immunotherapy and Immune Responses
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