Abstract
BackgroundTumor mutational burden (TMB) has both prognostic value in resected non-small cell lung cancer (NSCLC) patients and predictive value for immunotherapy response. However, TMB evaluation by whole-exome sequencing (WES) is expensive and time-consuming, hampering its application in clinical practice. In our study, we aimed to construct a mutational burden estimation model, with a small set of genes, that could precisely estimate WES-TMB and, at the same time, has prognostic and predictive value for NSCLC patients.MethodsTMB estimation model was trained based on genomic data from 1056 NSCLC samples from The Cancer Genome Atlas (TCGA). Validation was performed using three independent cohorts, including Rizvi cohort and our own Asian cohorts, including 89 early-stage and n late-stage Asian NSCLC patients, respectively. TCGA data were obtained on September 3, 2018. The two Asian cohort studies were performed from September 1, 2018, to March 5, 2019. Pearson’s correlation coefficient was used to assess the performance of estimated TMB with WES-TMB. The Kaplan-Meier survival analysis was applied to evaluate the association of estimated TMB with disease-free survival (DFS), overall survival (OS), and response to anti-programmed death-1 (PD-1) and anti-programmed death-ligand 1 (PD-L1) therapy.ResultsThe estimation model, consisted of only 23 genes, correlated well with WES-TMB both in the training set of TCGA cohort and validation set of Rizvi cohort and our own Asian cohort. Estimated TMB by the 23-gene panel was significantly associated with DFS and OS in patients with early-stage NSCLC and could serve as a predictive biomarker for anti-PD-1 and anti-PD-L1 treatment response.ConclusionsThe 23-gene panel, instead of WES or the currently used panel-based methods, could be used to assess the WES-TMB with a high relevance. This customized targeted sequencing panel could be easily applied into clinical practice to predict the immunotherapy response and prognosis of NSCLC.
Highlights
Tumor mutational burden (TMB) has both prognostic value in resected non-small cell lung cancer (NSCLC) patients and predictive value for immunotherapy response
The 23-gene panel, instead of whole-exome sequencing (WES) or the currently used panel-based methods, could be used to assess the WES-TMB with a high relevance. This customized targeted sequencing panel could be applied into clinical practice to predict the immunotherapy response and prognosis of NSCLC
DNA damage repair (DDR) genes, negatively predictive genes (STK11 and KEAP1), and TMB-associated genes such as MUC16, POLE, POLD1, and TTN have been included in the next generation sequencing (NGS) panels for TMB evaluation [10,11,12,13,14], with the burgeoning developments in immunotherapy, there is a need for more specific panels that focus on TMB estimation for NSCLC
Summary
Tumor mutational burden (TMB) has both prognostic value in resected non-small cell lung cancer (NSCLC) patients and predictive value for immunotherapy response. Tumor mutational burden (TMB), commonly defined as the number of nonsynonymous mutations, has been proposed as a promising predictive biomarker for the response to immune checkpoint inhibitors (ICIs) This metric tightly correlates with overall survival (OS) in resected non-small cell lung cancer (NSCLC) patients [1]. Many new NGS panels consisting of different numbers of genes have been developed and validated, most of which were designed initially for guiding the use of target therapies These panels mainly include cancer-related oncogenes and tumor suppressor genes, many of which do not contribute to or even negatively correlate with TMB, are not accurate for TMB evaluation. DNA damage repair (DDR) genes, negatively predictive genes (STK11 and KEAP1), and TMB-associated genes such as MUC16, POLE, POLD1, and TTN have been included in the NGS panels for TMB evaluation [10,11,12,13,14], with the burgeoning developments in immunotherapy, there is a need for more specific panels that focus on TMB estimation for NSCLC
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