Abstract

Outcome of immune checkpoint inhibition in cancer can be predicted by measuring PDL1 expression of tumor cells. Search for additional biomarkers led to tumor mutational burden (TMB) as surrogate marker for neoantigens presented. While TMB was previously determined via whole exome sequencing (WES), there have been approaches with comprehensive gene panels as well. We sequenced samples derived from formalin-fixed tumors, a POLE mutated cell line and standard DNA by WES and five different panels. If available, normal tissue was also exome sequenced. Sequencing data was analyzed by commercial software solutions and an in-house pipeline. A robust Pearson correlation (R = 0.9801 ± 0.0167; mean ± sd; N = 7) was determined for the different panels in a tumor paired normal setting for WES. Expanded analysis on tumor only exome sequenced samples yielded similar correlation (R = 0.9439 ± 0.0632; mean ± sd; N = 14). Remaining germline variants increased TMB in WES by 5.761 ± 1.953 (mean ± sd.; N = 7) variants per megabase (v/mb) for samples including synonymous variants and 3.883 ± 1.38 v/mb for samples without synonymous variants compared to tumor-normal paired calling results. Due to limited sample numbers in this study, additional replication is suggested for a clinical setting. Remaining germline variants in a tumor-only setting and artifacts caused by different library chemistries construction might affect the results.

Details

Title
Analysis of tumor mutational burden: correlation of five large gene panels with whole exome sequencing
Author
Heydt Carina 1 ; Rehker Jan 1 ; Pappesch Roberto 1 ; Buhl, Theresa 1 ; Ball, Markus 1 ; Siebolts Udo 2 ; Haak Anja 2 ; Lohneis Philipp 1 ; Büttner Reinhard 1 ; Hillmer, Axel M 1 ; Merkelbach-Bruse Sabine 1 

 University of Cologne, Institute of Pathology, Faculty of Medicine, Cologne, Germany (GRID:grid.6190.e) (ISNI:0000 0000 8580 3777) 
 University Hospital Halle (Saale), Institute of Pathology, Halle, Germany (GRID:grid.461820.9) (ISNI:0000 0004 0390 1701) 
Publication year
2020
Publication date
2020
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2421631761
Copyright
© The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.