Mutations Associated with No Durable Clinical Benefit to Immune Checkpoint Blockade in Non-S-Cell Lung Cancer
Guangsheng Zhu1,2, Dian Ren1,2, Xi Lei1,2
1Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin 300050, China.
Abstract:
(1) Background: The immune checkpoint blockade (ICB) has shown promising efficacy in non-small-cell lung cancer (NSCLC) patients with significant clinical benefits and durable responses, but the overall response rate to ICBs is only 20%. The lack of responsiveness to ICBs is currently a central problem in cancer immunotherapy. (2) Methods: Four public cohorts comprising 2986 patients with NSCLC were included in the study. We screened 158 patients with NSCLC with no durable clinical benefit (NDB) to ICBs in the Rizvi cohort and identified NDB-related gene mutations in these patients using univariate and multivariate Cox regression analyses. Programmed death-ligand 1 (PD-L1) expression, tumor mutation burden (TMB), neoantigen load, tumor-infiltrating lymphocytes, and immune-related gene expression were analyzed for identifying gene mutations. A comprehensive predictive classifier model was also built to evaluate the efficacy of ICB therapy. (3) Results: Mutations in FAT1 and KEAP1 were found to correlate with NDB in patients with NSCLC to ICBs; however, the analysis suggested that only mutation in FAT1 was valuable in predicting the efficacy of ICB therapy, and that mutation in KEAP1 acted as a prognostic but not a predictive biomarker for NSCLC. Mutations in FAT1 were associated with a higher TMB and lower multiple lymphocyte infiltration, including CD8 (T-Cell Surface Glycoprotein CD8)+ T cells. We established a prognostic model according to PD-L1 expression, TMB, smoking status, treatment regimen, treatment type, and FAT1 mutation, which indicated good accuracy by receiver operating characteristic (ROC) analysis (area under the curve (AUC) for 6-months survival: 0.763; AUC for 12-months survival: 0.871). (4) Conclusions: Mutation in FAT1 may be a predictive biomarker in patients with NSCLC who exhibit NDB to ICBs. We proposed an FAT1 mutation-based model for screening more suitable NSCLC patients to receive ICBs that may contribute to individualized immunotherapy.
Insights
FAT1 gene mutations may predict non-small-cell lung cancer (NSCLC) response to immune checkpoint blockade (ICB) therapy. This finding could help identify patients who will not benefit from ICB, enabling personalized immunotherapy strategies.
Area of Science:
- Oncology
- Immunotherapy
- Genetics
Background:
- Immune checkpoint blockade (ICB) shows promise in non-small-cell lung cancer (NSCLC), but only 20% of patients respond.
- Lack of responsiveness to ICB is a significant challenge in cancer immunotherapy.
Purpose of the Study:
- To identify gene mutations associated with no durable clinical benefit (NDB) to ICBs in NSCLC patients.
- To evaluate the predictive value of identified mutations for ICB therapy efficacy.
Main Methods:
- Analysis of four public NSCLC cohorts (2986 patients).
- Screening 158 NSCLC patients with NDB to ICBs for gene mutations using Cox regression.
- Assessment of PD-L1 expression, tumor mutation burden (TMB), neoantigen load, and immune cell infiltration.
Main Results:
- FAT1 and KEAP1 mutations correlated with NDB in NSCLC patients.
- FAT1 mutation was identified as a predictive biomarker for ICB efficacy, while KEAP1 served as a prognostic biomarker.
- FAT1 mutations were linked to higher TMB and reduced CD8+ T-cell infiltration.
- A prognostic model incorporating PD-L1, TMB, smoking status, treatment, and FAT1 mutation showed high accuracy (AUCs 0.763-0.871).
Conclusions:
- FAT1 mutation may serve as a predictive biomarker for NSCLC patients unresponsive to ICBs.
- An FAT1 mutation-based model can help screen suitable NSCLC patients for ICB, advancing individualized immunotherapy.
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