Tumor mutation burden in Chinese cancer patients and the underlying driving pathways of high tumor mutation burden across different cancer types.
Ann Transl Med
; 8(14): 860, 2020 Jul.
Article
de En
| MEDLINE
| ID: mdl-32793704
ABSTRACT
BACKGROUND:
Tumor mutation burden (TMB) has an important association with immunotherapy responses. TMB in the Chinese population has not been well established. Finding differences between the Chinese and Caucasian populations and elucidating the underlying biological mechanisms of high TMB might help develop more precise and effective means for TMB and immunotherapy response prediction.METHODS:
Chinese cancer patients fresh tissue (n=2,177), formalin-fixed, paraffin-embed (FFPE) specimens (n=3,294), and pleural fluid (n=189) were profiled using a 295- or 520-gene next-generation sequencing (NGS) panel. The association of the TMB status with a series of molecular features and biological pathways was determined using bootstrapping.RESULTS:
TMB, measured by 295- or 520-cancer-related gene panels, was correlated with whole-exome sequencing (WES) TMB based on the in silico simulation in The Cancer Genome Atlas cohort. The median TMB of our data was slightly higher than that from the Foundation Medicine Inc. (FMI) dataset. TMB was also slightly different within the same cancer type between the Chinese and Caucasian population. We discovered that the underlying pathways of TMB status varied greatly and sometimes had an opposite association with TMB across different cancer types. Moreover, we developed a 23-gene and a 16-gene signature to predict TMB prediction for lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), respectively, indicating a histology-specific mechanism for driving high-TMB in lung cancer.CONCLUSIONS:
TMB varies among different ethnic populations. Our findings extend the knowledge of the underlying biological mechanisms for high TMB and might be helpful for developing more precise and accessible TMB assessment panels and algorithms in more cancer types.
Texte intégral:
1
Collection:
01-internacional
Base de données:
MEDLINE
Type d'étude:
Prognostic_studies
Langue:
En
Journal:
Ann Transl Med
Année:
2020
Type de document:
Article
Pays d'affiliation:
Chine