Shiyue Zhang, Youming Lei, Juan Zhao, Songhui Zhao, Wen-Jing Wang, Ming Yao, Xiaowei Dong, Kai Wang, Li Liu, Qing Zhou, and Yunfei Shi
Objectives This study aimed to explore the novel biomarkers for immune checkpoint inhibitor (ICI) responses in non‐small cell lung cancer (NSCLC) by integrating genomic profiling, tumor mutational burden (TMB), and expression of programmed death receptor 1 ligand (PD‐L1). Materials and Methods Tumor and blood samples from 637 Chinese patients with NSCLC were collected for targeted panel sequencing. Genomic alterations, including single nucleotide variations, insertions/deletions, copy number variations, and gene rearrangements, were assessed and TMB was computed. TMB‐high (TMB‐H) was defined as ≥10 mutations/Mb. PD‐L1 positivity was defined as ≥1% tumor cells with membranous staining. Genomic data and ICI outcomes of 240 patients with NSCLC were derived from cBioPortal. Results EGFR‐sensitizing mutations, ALK, RET, and ROS1 rearrangements were associated with lower TMB and PD‐L1+/TMB‐H proportions, whereas KRAS, ALK, RET, and ROS1 substitutions/indels correlated with higher TMB and PD‐L1+/TMB‐H proportions than wild‐type genotypes. Histone‐lysine N‐methyltransferase 2 (KMT2) family members (KMT2A, KMT2C, and KMT2D) were frequently mutated in NSCLC tumors, and these mutations were associated with higher TMB and PD‐L1 expression, as well as higher PD‐L1+/TMB‐H proportions. Specifically, patients with KMT2C mutations had higher TMB and PD‐L1+/TMB‐H proportions than wild‐type patients. The median progression‐free survival (PFS) was 5.47 months (95% CI 2.5–NA) in patients with KMT2C mutations versus 3.17 months (95% CI 2.6–4.27) in wild‐type patients (p = 0.058). Furthermore, in patients with NSCLC who underwent ICI treatment, patients with TP53/KMT2C co‐mutations had significantly longer PFS and greater durable clinical benefit (HR: 0.48, 95% CI: 0.24–0.94, p = 0.033). TP53 mutation combined with KMT2C or KRAS mutation was a better biomarker with expanded population benefit from ICIs therapy and increased the predictive power (HR: 0.46, 95% CI: 0.26–0.81, p = 0.007). Conclusion We found that tumors with different alterations in actionable target genes had variable expression of PD‐L1 and TMB in NSCLC. TP53/KMT2C co‐mutation might serve as a predictive biomarker for ICI responses in NSCLC. Implications for Practice Cancer immunotherapies, especially immune checkpoint inhibitors (ICIs), have revolutionized the treatment of non‐small cell lung cancer (NSCLC); however, only a proportion of patients derive durable responses to this treatment. Biomarkers with greater accuracy are highly needed. In total, 637 Chinese patients with NSCLC were analyzed using next‐generation sequencing and IHC to characterize the unique features of genomic alterations and TMB and PD‐L1 expression. Our study demonstrated that KMT2C/TP53 co‐mutation might be an accurate, cost‐effective, and reliable biomarker to predict responses to PD‐1 blockade therapy in NSCLC patients and that adding KRAS to the biomarker combination creates a more robust parameter to identify the best responders to ICI therapy., Cancer immunotherapy, especially immune checkpoint inhibitors (ICIs), is epoch‐making in non‐small cell lung cancer (NSCLC), but only a proportion of patients can derive durable benefits from it, more accurate biomarkers are thus highly needed. Samples of 637 Chinese patients with NSCLC were analyzed through next‐generation sequencing and IHC to characterize the unique features of genomic alterations, TMB, and PD‐L1 expression. The results showed that the alteration subtypes of common driver genes including EGFR G719X, KRAS G12C, MET amplification, and SNVs/INDELs of ALK, RET, and ROS1 in NSCLC are associated with higher PD‐L1 expression or higher TMB value. Furthermore, our study first demonstrated that KMT2C/TP53 co‐mutation might be an accurate, cost‐effective, and reliable biomarker to predict the responses to PD‐1 blockade therapy in NSCLC patients, and that adding KRAS to the biomarker combination creates a more robust parameter to identify the best responders to ICI therapy.