Tumor mutational burden assessed by targeted NGS predicts clinical benefit from immune checkpoint inhibitors in non-small cell lung cancer.

In non-small cell lung cancer (NSCLC), immune checkpoint inhibitors (ICIs) significantly improve overall survival (OS). Tumor mutational burden (TMB) has emerged as a predictive biomarker for patients treated with ICIs. Here, we evaluated the predictive power of TMB measured by the Oncomine™ Tumor Mutational Load targeted sequencing assay in 76 NSCLC patients treated with ICIs. TMB was assessed retrospectively in 76 NSCLC patients receiving ICI therapy. Clinical data (RECIST 1.1) were collected and patients were classified as having either durable clinical benefit (DCB) or no durable benefit (NDB). Additionally, genetic alterations and PD-L1 expression were assessed and compared with TMB and response rate. TMB was significantly higher in patients with DCB than in patients with NDB (median TMB = 8.5 versus 6.0 mutations/Mb, Mann-Whitney p = 0.0244). 64% of patients with high TMB (cut-off = third tertile, TMB ≥ 9) were responders (DCB) compared to 33% and 29% of patients with intermediate and low TMB, respectively (cut-off = second and first tertile, TMB = 5-9 and TMB ≤ 4, respectively). TMB-high patients showed significantly longer progression-free survival (PFS) and OS (log-rank test p = 0.0014 for PFS and 0.0197 for OS). While identifying different subgroups of patients, combining PD-L1 expression and TMB increased the predictive power (from AUC 0.63 to AUC 0.65). Our results show that the TML panel is an effective tool to stratify patients for ICI treatment. A combination of biomarkers might maximize the predictive precision for patient stratification. Our study supports TMB evaluation through targeted NGS in NSCLC patient samples as a tool to predict response to ICI therapy. We offer recommendations for a reliable and cost-effective assessment of TMB in a routine diagnostic setting. © 2019 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Robust assessment of tumor mutational burden in cytological specimens from lung cancer patients.

OBJECTIVES: Tumor mutational burden (TMB) has emerged as a promising predictive biomarker for immune checkpoint inhibitor therapy. While the feasibility of TMB analysis on formalin-fixed paraffin-embedded (FFPE) samples has been thoroughly evaluated, only limited analyses have been performed on cytological samples, and no dedicated study has investigated concordance of TMB between different sample types. Here, we assessed TMB on matched histological and cytological samples from lung cancer patients and evaluated the accuracy of TMB estimation in these sample types. MATERIALS AND METHODS: We analyzed mutations and resulting TMB in FFPE samples and matched ethanol-fixed cytological smears (n = 12 matched pairs) by using a targeted next-generation sequencing assay (Oncomine™ Tumor Mutational Load). Two different variant allele frequency (VAF) thresholds were used to estimate TMB (VAF = 5% or 10%). RESULTS: At 5% VAF threshold, 73% (107/147) of mutations were concordantly detected in matched histological and cytological samples. Discordant variants were mainly unique to FFPE samples (34/40 discordant variants) and mostly C:G > T:A transitions with low allelic frequency, likely indicating formalin fixation artifacts. Increasing the VAF threshold to 10% clearly increased the number of concordantly detected mutations in matched histological and cytological samples to 96% (100/106 mutations), and drastically reduced the number of FFPE-only mutations (from 34 to 4 mutations). In contrast, cytological samples showed consistent mutation count and TMB values at both VAF thresholds. Using FFPE samples, 2 out of 12 patients were classified as TMB-high at VAF cutoff of 5% but TMB-low at 10%, whereas cytological specimens allowed consistent patient classification independently from VAF cutoff. CONCLUSION: Our results show that cytological smears provide more consistent TMB values due to high DNA quality and lack of formalin-fixation induced artifacts. Therefore, cytological samples should be the preferred sample type for robust TMB estimation.