Dataset Information

The immune response-related mutational signatures and driver genes in non-small-cell lung cancer.

ABSTRACT: Immune checkpoint blockade (ICB) therapy has achieved remarkable clinical benefit in non-small-cell lung cancer (NSCLC), but our understanding of biomarkers that predict the response to ICB remain obscure. Here we integrated somatic mutational profile and clinicopathologic information from 113 NSCLC patients treated by ICB (CTLA-4/PD-1). High tumor mutation burden (TMB) and neoantigen burden were identified significantly associated with improved efficacy in NSCLC immunotherapy. Furthermore, we identified apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like (APOBEC) mutational signature was markedly associated with responding of ICB therapy (log-rank test, P = .001; odds ratio (OR), 0.18 [95% CI, 0.06-0.50], P < .001). The association with progression-free survival remained statistically significant after controlling for age, sex, histological type, smoking, PD-L1 expression, hypermutation, smoking signature and mismatch repair (MMR) (HR, 0.30 [95% CI, 0.12-0.75], P = .010). Combined high TMB with APOBEC signature preferably predict immunotherapy responders in NSCLC cohort. The CIBERSORT algorithm revealed that high APOBEC mutational activity samples were associated with increased infiltration of CD4 memory activated T cells, CD8+ T cells and natural killer (NK) cells, but reduced infiltration of regulatory T cells. Besides, individual genes mutation of IFNGR1 or VTCN1 were only found in responders; however, the PTEN mutation was only found in non-responders (Fisher's exact test, all P < .05). These findings may be applicable for guiding immunotherapy for patients with NSCLC.

SUBMITTER: Chen H

PROVIDER: S-EPMC6676111 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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The immune response-related mutational signatures and driver genes in non-small-cell lung cancer.

Chen Hao H Chong Wei W Teng Changcai C Yao Yueliang Y Wang Xin X Li Xue X

Cancer science 20190723 8

Immune checkpoint blockade (ICB) therapy has achieved remarkable clinical benefit in non-small-cell lung cancer (NSCLC), but our understanding of biomarkers that predict the response to ICB remain obscure. Here we integrated somatic mutational profile and clinicopathologic information from 113 NSCLC patients treated by ICB (CTLA-4/PD-1). High tumor mutation burden (TMB) and neoantigen burden were identified significantly associated with improved efficacy in NSCLC immunotherapy. Furthermore, we i ...[more]

PMID: 31222843

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Project description:BackgroundHomologous recombination deficiency (HRD) is a well-known biomarker which could predict poly-ADP ribose polymerase 1 (PARP) inhibitor and platinum drug response. As an aggressive cancer, small-cell lung cancer (SCLC) is sensitive to platinum drugs, but relapse occurs rapidly. Herein, we aim to illustrate the genomic alteration patterns of homologous recombination repair (HRR)-related genes in a Chinese SCLC cohort and further analyze the relationship among HRR gene mutations and known biomarkers of immune checkpoint inhibitor (ICI) response, including tumor mutation burden (TMB) and programmed cell death-ligand 1 (PD-L1) expression.MethodsNext-generation sequencing (NGS)-based target capture sequencing of 543 cancer-related genes was performed to analyze the genomic profiles of 133 Chinese SCLC patients, and TMB was calculated. PD-L1 expression was evaluated in 90 out of 133 patients using the SP142 PD-L1 immunohistochemistry assay.ResultsAmong the 133 patients with SCLC, 47 (35.3%) had HRR gene mutations. ATM (8.3%) was the most frequently mutated HRR gene in the cohort, followed by NBN (4.5%). Pathogenic somatic and germline mutations of HRR genes were identified in 11 (23.4%) and 4 (8.5%) patients, respectively. HRR gene mutations cooccurred with KMT2D gene mutations. There were several differences in genomic alterations between patients with HRR gene mutations (HRR-Mut) and without HRR mutations (HRR-WT). The results revealed that TP53 and RB1 were commonly mutated genes in both groups. Mutations in the KMT2D gene and genes in the RTK-RAS pathway occurred more frequently in the HRR-Mut group. Furthermore, we found that mutations in HRR genes were associated with high TMB (Wilcoxon, p = 0.048), but there was no correlation of HRR gene mutation status with PD-L1 expression.ConclusionsWe exhaustively describe the genomic alteration profile of Chinese SCLC patients and provide further evidence that HRR gene mutations are prevalent in SCLC patients.

Project description:Purpose:Heterogeneity in tumor mutational burden (TMB) quantification across sequencing platforms limits the application and further study of this potential biomarker of response to immune checkpoint inhibitors (ICI). We hypothesized that harmonization of TMB across platforms would enable integration of distinct clinical datasets to better characterize the association between TMB and ICI response. Methods:Cohorts of NSCLC patients sequenced by one of three targeted panels or by whole exome sequencing (WES) were compared (total n=7297). TMB was calculated uniformly and compared across cohorts. TMB distributions were harmonized by applying a normal transformation followed by standardization to z-scores. In sub-cohorts of patients treated with ICIs (DFCI n=272; MSKCC n=227), the association between TMB and outcome was assessed. Durable clinical benefit (DCB) was defined as responsive/stable disease lasting ≥6 months. Results:TMB values were higher in the panel cohorts than the WES cohort. Average mutation rates per gene were highly concordant across cohorts (Pearson coefficient 0.842-0.866). Subsetting the WES cohort by gene panels only partially reproduced the observed differences in TMB. Standardization of TMB into z-scores harmonized TMB distributions and enabled integration of the ICI-treated sub-cohorts. Simulations indicated that cohorts >900 are necessary for this approach. TMB did not associate with response in never smokers or patients harboring targetable driver alterations, although these analyses were under-powered. Increasing TMB thresholds increased DCB rate, but DCB rates within deciles varied. Receiver operator curves yielded an area under the curve of 0.614 with no natural inflection point. Conclusion:Z-score conversion harmonizes TMB values and enables integration of datasets derived from different sequencing panels. Clinical and biologic features may provide context to the clinical application of TMB, and warrant further study.

Dataset Information

The immune response-related mutational signatures and driver genes in non-small-cell lung cancer.

Publications

The immune response-related mutational signatures and driver genes in non-small-cell lung cancer.

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