Abstract

Abstract Checkpoint inhibitors have been approved for the treatment of solid tumor and hematological malignancies. While significant responses have been observed in a subset of patients, outcomes are variable and there is a need to identify additional predictive biomarkers beyond PD-L1 levels as measured by IHC. Tumor mutation burden (TMB) has been correlated with response to checkpoint inhibitors and is emerging as a key biomarker for predicting checkpoint inhibitor response. So far, the methods used to assess tumor mutation burden have included exome sequencing and multiple laboratory-developed targeted NGS panels (e.g., FoundationOne and MSK-IMPACT). In order to fully determine the value of TMB as a predictive biomarker for immunotherapy, a standardized panel, workflow and data analysis pipeline for TMB assessment are needed. In this study we evaluated the performance of a commercially available targeted NGS panel and workflow for TMB analysis. A set of 30 FFPE tumor samples including colon, renal, gastric, endometrial, and lung tissues was analyzed. DNA and RNA were extracted using the RecoverAll Total Nucleic Acid Isolation Kit. DNA quantity and quality were assessed using Qubit and qPCR, respectively. Samples were analyzed with the ThermoFisher Oncomine™ Mutation Load Research Assay (TML), which evaluates tumor mutation load (mutations/Mb) by interrogating 409 cancer-related genes, spanning ~1.7 megabases of the genome. TMB was measured by counting somatic single-base substitutions per Mb at ≥10% allele frequency in single, non-matched, tumor DNA samples. The impact of DNA quality on the TMB score was evaluated. Deamination errors (i.e. G>A and C>T) in poor quality FFPE samples was found to cause the overestimation of TMB. Therefore, a delta Ct cutoff was established to qualify DNA samples for TMB analysis. 12 of the 30 samples were also analyzed using a comparator NGS panel covering ~1.25 megabases. The correlation of TMB results between the two panels was 0.87. Overall, TMB was lowest in RCC (9-17/Mb) compared to NSCLC and CRC (16-37/Mb). MSI status was determined using the Promega MSI Analysis System v1.2. A correlation was observed between TMB and MSI status in a subset of samples. Reproducibility of the assay was also evaluated. To identify clinically relevant mutations and genetic alteration associated with high mutation burden, the Oncomine Comprehensive assay v3 (OCAv3) was also used to analyze the sample set. Mutations in genes involved in several DNA repair pathways were found to correlate with TMB. This study demonstrated the feasibility of utilizing a commercial targeted NGS panel and data analysis pipeline for TMB evaluation in clinical FFPE tumor samples. Standardization of TMB analysis will enable the clinical validation of TMB as a predictive biomarker for therapy selection. Citation Format: Peng Fang, Zhenyu Yan, Quyen Vu, David Smith, Chad Galderisi, Cynthia S. Spittle, Jin Li. Evaluation of a commercial targeted NGS panel for tumor mutation burden assessment in FFPE tissue [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3614.

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