Impact of genomic HLA class I allelic imbalance on enduring immunotherapy response in advanced non–small cell lung cancer.

Abstract

8582 Background: Human leukocyte antigen class I (HLA-I) molecules are essential for neoantigen presentation and T cell recognition, yet the clinical significance of allelic imbalance within HLA-I genes (HLA-AI) in immune checkpoint inhibitors (ICIs) therapy remains undefined. Methods: Here, we established haplotype-specific, coverage-based (cHLA-AI) compatible with routine biopsy-derived sequencing, based on 292 fully heterozygous non–small cell lung cancer (NSCLC) patients with paired tumor samples from the phase III CHOICE-01 trial and confirmed in RATIONALE-304 and real-world NCC cohorts, covering both first- and later-line immunochemotherapy as well as ICI monotherapy, and complemented by analyses in surgical, pan-cancer, and longitudinal datasets to assess immune correlates and evolutionary dynamics. Results: Patients with tumor mutational burden (TMB)–low and cHLA-AI derived no benefit from first-line immunochemotherapy, whereas all other patients achieved significant survival gains (TMB-low and cHLA-AI vs. others: immunochemotherapy arm: mOS 16.53 vs. 29.57 months, HR = 2.29, 95% CI 1.59–3.30, p < 0.001,interaction P = 0.019; mPFS 5.59 vs. 9.92 months, HR = 2.02, 95% CI 1.43–2.90, p < 0.001, interaction P = 0.016). These findings were validated in the RATIONALE-304 and RATIONALE-307 trials and independent real-world cohorts. Incorporating cHLA-AI with pathology, PD-L1 and TMB significantly improved 2-year OS prediction (DeLong’s P = 0.003). Multi-omic profiling linked cHLA-AI to active DNA damage response signalings, high TMB -intratumor heterogeneity (ITH) -chromosomal instability (CIN) phenotype, immune-cold microenvironments, and failure of on-treatment TCR clone expansion, while longitudinal sampling revealed its late, branching emergence under immune pressure. Pan-cancer profiling (N = 5,989) demonstrated consistent associations with high TMB-ITH-CIN phenotype and proliferative activity (Ki-67 index). Conclusions: Collectively, these results establish cHLA-AI as a pivotal biomarker bridging genomic instability, immune evasion, and therapeutic outcomes, providing a framework for stratified immunotherapy response in non–small cell lung cancer and beyond.