Journal
CLINICAL CANCER RESEARCH
Volume 25, Issue 16, Pages 5015-5026Publisher
AMER ASSOC CANCER RESEARCH
DOI: 10.1158/1078-0432.CCR-19-0585
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Funding
- National Key R&D Program of China [2016YFC0905500, 2016YFC0905503]
- Science and Technology Program of Guangdong [2017B020227001]
- Chinese National Natural Science Foundation [81772476, 81602005, 81872499]
- Outstanding Young Talents Program of Sun Yat-sen University Cancer Center [16zxyc04]
- Central Basic Scientific Research Fund for Colleges-Young Teacher Training Program of Sun Yat-sen University [17ykpy81]
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Purpose: Immune checkpoint inhibitors (ICI) have revolutionized cancer management. However, molecular determinants of response to ICIs remain incompletely understood. Experimental Design: 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. Results: We confirmed that high TMB was associated with improved clinical outcomes, and TMB quantified by gene panel strongly correlated with WES results (Spearman's r = 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. Conclusions: 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.
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