ecTMB: a robust method to estimate and classify tumor mutational burden
被引:0
|
作者:
Lijing Yao
论文数: 0引用数: 0
h-index: 0
机构:Roche Sequencing Solutions,
Lijing Yao
Yao Fu
论文数: 0引用数: 0
h-index: 0
机构:Roche Sequencing Solutions,
Yao Fu
Marghoob Mohiyuddin
论文数: 0引用数: 0
h-index: 0
机构:Roche Sequencing Solutions,
Marghoob Mohiyuddin
Hugo Y. K. Lam
论文数: 0引用数: 0
h-index: 0
机构:Roche Sequencing Solutions,
Hugo Y. K. Lam
机构:
[1] Roche Sequencing Solutions,
来源:
Scientific Reports
|
/
10卷
关键词:
D O I:
暂无
中图分类号:
学科分类号:
摘要:
Tumor Mutational Burden (TMB) is a measure of the abundance of somatic mutations in a tumor, which has been shown to be an emerging biomarker for both anti-PD-(L)1 treatment and prognosis; however, multiple challenges still hinder the adoption of TMB as a biomarker. The key challenges are the inconsistency of tumor mutational burden measurement among assays and the lack of a meaningful threshold for TMB classification. Here we describe a new method, ecTMB (Estimation and Classification of TMB), which uses an explicit background mutation model to predict TMB robustly and to classify samples into biologically meaningful subtypes defined by tumor mutational burden.
机构:
Weill Cornell Med, Meyer Canc Ctr, Englander Inst Precis Med, New York, NY 10021 USAWeill Cornell Med, Meyer Canc Ctr, Englander Inst Precis Med, New York, NY 10021 USA