Abstract

Abstract Immunotherapies are an emerging approach for cancer treatment that leverage the power of the immune system to attack cancer cells. By targeting immune check-point pathways such as PD-1, these treatments have been highly effective for some patients diagnosed with skin, bladder, lung, or kidney cancer. However, response rates for these treatments vary, making it beneficial to identify patients who are likely to respond to the treatment. Qualitative methods for predicting immunotherapy response are available but are technically challenging and subjective. An emerging quantitative predictor of immunotherapy response, tumor mutational burden (TMB), measures the number of somatic mutations per Mb of the genome. TMB calculations using whole exome data have been shown to correlate with patient response to immunotherapies. However, derivation of this score is not well characterized, nor is the score universally performed across laboratories. Here we describe the results from calculating TMB scores varying cancer panel size and amount of sequencing generated. First, variants are called in matched tumor and normal samples within Exomes. Then low coverage variants are removed along with variants outside the targeted, high-confidence regions in each panel. The remaining variants in the normal samples constitute the germline variants and are subtracted from the number of variants identified in tumor samples to yield the TMB score. We then repeated this across multiple indications across TCGA to review robustness of score in indications across the spectra of burden. TMB scores from the our comprehensive cancer closely resembles scores calculated using whole exome data across indications. We propose rules for gene content and sequencing depth for providing a range of burden scores that could be used for determining thresholds needed for determining therapeutic implications. We suggest that only a small subset of genes are required for accurate TMB estimation, thus reducing costs associated with predicting patient response to immunotherapy. Citation Format: Scott Yourstone, Natalie Mola, Victor J. Weigman. Effects of sequencing parameters and panel size on mutational burden calculations [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 LB-381.

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