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Pan-cancer Analysis of Tumor Mutational Burden and Homologous Recombination DNA Damage Repair Using Targeted Next-Generation Sequencing

Authors :
Yan-Fen Feng
Ling Deng
Hai-Yun Wang
Ying-Qing Li
Tao Tang
Fang Wang
Ya-Kang Long
Xin-Hua Yang
Xiao Zhang
Yuan He
Xu Zhang
Source :
Cancer Research and Treatment : Official Journal of Korean Cancer Association
Publication Year :
2021
Publisher :
Korean Cancer Association, 2021.

Abstract

Purpose Current variability in methods for tumor mutational burden (TMB) estimation and reporting demonstrates the urgent need for a homogeneous TMB assessment approach. Here, we compared TMB distributions in different cancer types using two customized targeted panels commonly used in clinical practice. Materials and Methods TMB spectra of 295- and 1021-gene panels in multiple cancer types were compared using targeted next-generation sequencing (NGS). The TMB distributions across a diverse cohort of 2,332 cancer cases were then investigated for their associations with clinical features. Treatment response data were collected for 222 patients who received immune-checkpoint inhibitors (ICIs) and their homologous recombination DNA damage repair (HR-DDR) and programmed death-ligand 1 (PD-L1) expression were additionally assessed and compared with the TMB and response rate. Results The median TMB between gene panels was similar despite a wide range in TMB values. The highest TMB was 8 and 10 in patients with squamous cell carcinoma and esophageal carcinoma according to the classification of histopathology and cancer types, respectively. Twenty-three out of 103 patients (22.3%) were HR-DDR‒positive and could benefit from ICI therapy; out of those 23 patients, seven patients had high TMB (p=0.004). Additionally, PD-L1 expression was not associated with TMB or treatment response among patients receiving ICIs. Conclusion Targeted NGS assays demonstrated the ability to evaluate TMB in pan-cancer samples as a tool to predict response to ICIs. In addition, TMB integrated with HR-DDR‒positive status could be a significant biomarker for predicting ICI response in patients.

Details

ISSN :
20059256 and 15982998
Volume :
53
Database :
OpenAIRE
Journal :
Cancer Research and Treatment
Accession number :
edsair.doi.dedup.....ed983c75ccc0553931ad0b42543800fc
Full Text :
https://doi.org/10.4143/crt.2020.798