Benchmarking bioinformatics approaches for tumour mutational burden evaluation from a large cancer panel against whole-exome sequencing

Autor: Jiuhong Pang, Hongai Xia, Shijun Mi, Wen Zhang, Danielle Pendrick, Christopher Freeman, Helen Fernandes, Mahesh Mansukhani, Susan J Hsiao
Rok vydání: 2022
Předmět:
Zdroj: Journal of Clinical Pathology. 76:276-280
ISSN: 1472-4146
0021-9746
DOI: 10.1136/jcp-2022-208385
Popis: Tumour mutational burden (TMB) is used to predict response to immunotherapies. Although several groups have proposed calculation methods for TMB, a clear consensus has not yet emerged. In this study, we explored TMB calculation approaches with a 586-gene cancer panel (1.75 Mb) benchmarked to TMB measured by whole-exome sequencing (WES), using 30 samples across a range of tumour types. We explored variant allelic fraction (VAF) cut-offs of 5% and 10%, population database filtering at 0.001, 0.0001 and 0.000025, as well as different combinations of synonymous, insertion/deletion and intronic (splice site) variants, as well as exclusion of hotspot mutations, and examined the effect on TMB correlation. Good correlation (Spearman, range 0.66–0.78) between WES and panel TMB was seen across all methods evaluated. Each method of TMB calculation evaluated showed good positive per cent agreement and negative per cent agreement using 10 mutations/Mb as a cut-off, suggesting that multiple TMB calculation approaches may yield comparable results.
Databáze: OpenAIRE