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|Ref Type||Journal Article|
|Authors||Fang W, Ma Y, Yin JC, Hong S, Zhou H, Wang A, Wang F, Bao H, Wu X, Yang Y, Huang Y, Zhao H, Shao YW, Zhang L|
|Title||Comprehensive Genomic Profiling Identifies Novel Genetic Predictors of Response to Anti-PD-(L)1 Therapies in Non-Small Cell Lung Cancer.|
|Journal||Clinical cancer research : an official journal of the American Association for Cancer Research|
|Date||2019 Aug 15|
|Abstract Text||Immune checkpoint inhibitors (ICI) have revolutionized cancer management. However, molecular determinants of response to ICIs remain incompletely understood.We performed genomic profiling of 78 patients with non-small cell lung cancer (NSCLC) who underwent anti-PD-(L)1 therapies by both whole-exome and targeted next-generation sequencing (a 422-cancer-gene panel) to explore the predictive biomarkers of ICI response. Tumor mutation burden (TMB), and specific somatic mutations and copy-number alterations (CNA) were evaluated for their associations with immunotherapy response.We confirmed that high TMB was associated with improved clinical outcomes, and TMB quantified by gene panel strongly correlated with WES results (Spearman's ρ = 0.81). Compared with wild-type, patients with FAT1 mutations had higher durable clinical benefit (DCB, 71.4% vs. 22.7%, P = 0.01) and objective response rates (ORR, 57.1% vs. 15.2%, P = 0.02). On the other hand, patients with activating mutations in EGFR/ERBB2 had reduced median progression-free survival (mPFS) compared with others [51.0 vs. 70.5 days, P = 0.0037, HR, 2.47; 95% confidence interval (CI), 1.32-4.62]. In addition, copy-number loss in specific chromosome 3p segments containing the tumor-suppressor ITGA9 and several chemokine receptor pathway genes, were highly predictive of poor clinical outcome (survival rates at 6 months, 0% vs. 31%, P = 0.012, HR, 2.08; 95% CI, 1.09-4.00). Our findings were further validated in two independently published datasets comprising multiple cancer types.We identified novel genomic biomarkers that were predictive of response to anti-PD-(L)1 therapies. Our findings suggest that comprehensive profiling of TMB and the aforementioned molecular markers could result in greater predictive power of response to ICI therapies in NSCLC.|
|Molecular Profile||Treatment Approach|
|Gene Name||Source||Synonyms||Protein Domains||Gene Description||Gene Role|
|Therapy Name||Drugs||Efficacy Evidence||Clinical Trials|
|Drug Name||Trade Name||Synonyms||Drug Classes||Drug Description|
|Gene||Variant||Impact||Protein Effect||Variant Description||Associated with drug Resistance|
|Molecular Profile||Indication/Tumor Type||Response Type||Therapy Name||Approval Status||Evidence Type||Efficacy Evidence||References|