DYNC2H1 Mutation as an indicator stratified patients benefit from Immune Checkpoint Inhibitors in NSCLC.

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e21052 Background: Immune checkpoint inhibitors (ICIs), targeting the programmed cell death 1 (PD-1), programmed cell death ligand 1 (PD-L1) or cytotoxic T lymphocyte-associated protein 4 (CTLA-4) have demonstrated impressive anti-tumor efficacy in multiple tumors, particularly non-small cell lung cancer (NSCLC). However, only a minority of patients could clinically benefit from the ICIs. Therefore, it is of vital clinical significance to explore underlying predictive biomarkers to identify to identify these most potentially ICIs-benefitable patients. Dynein cytoplasmic 2 heavy chain 1 (DYNC2H1) encodes a large cytoplasmic dynein protein that involved in intraflagellar transport. However, its role in lung cancer immunotherapy remains unknown. Here we aimed to explore the association between DYNC2H1 and ICIs. Methods: 165 NSCLC patients from three public immunotherapy cohorts (Hellmann 2018, Miao 2018, and Rizvi 2015 cohort) were included to analyze the association between DYNC2H1 gene mutation and efficacy of ICI therapy. Genomic, survival and mRNA data of NSCLC patients from the Cancer Genome Atlas (TCGA) database was used to explore the potential mechanisms of anti-tumor immunity. Results: NSCLC patients with DYNC2H1 mutation were significantly associated with better PFS (HR = 0.3; 95% CI, 0.14-0.64; P= 0.001), objective response rate (ORR, 65.0% vs 27.6%; P = 0.003) and durable clinical benefit (DCB, 75.0% vs 43.4%; P = 0.031) after ICIs therapy, compared with those with wide-type DYNC2H1. DYNC2H1 mutation were associated with increased TMB ( P < 0.001). In the multivariable Cox proportional hazards regression model adjusted by smoking status, PD-L1 expression and TMB, the association between DYNC2H1 mutation and PFS remained significant (HR = 0.32; 95% CI, 0.14-0.73; P = 0.007). In contrast, no association between DYNC2H1 mutation and OS (LUAD: P = 0.97 ; LUSC: P = 0.34) or PFS (LUAD: P = 0.54; LUSC: P = 0.39) was observed in TCGA datasets, suggesting that DYNC2H1 mutation may be a predictive but not a prognostic factor in ICI treatment for NSCLC patients. Based on CIBERSORT-inferred tumor infiltrating lymphocytes from TCGA, DYNC2H1 mutation was significantly associated with higher CD8+ T cell. Moreover, DYNC2H1 mutation was associated with increased TMB ( P < 0.001) and neoantigen load ( P < 0.001) in TCGA. Conclusions: Our results demonstrated that DYNC2H1 mutation is an underlying classifier that could stratify patients with NSCLC for ICIs. The role of DYNC2H1 in immunotherapy is needed to be further studied.