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ecTMB:一种稳健的估计和分类肿瘤突变负担的方法。

ecTMB: a robust method to estimate and classify tumor mutational burden.

机构信息

Roche Sequencing Solutions, Santa Clara, CA, 95050, USA.

出版信息

Sci Rep. 2020 Mar 18;10(1):4983. doi: 10.1038/s41598-020-61575-1.

Abstract

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.

摘要

肿瘤突变负荷(TMB)是衡量肿瘤中体细胞突变丰度的指标,已被证明是抗 PD-(L)1 治疗和预后的新兴生物标志物;然而,多个挑战仍然阻碍了 TMB 作为生物标志物的采用。关键的挑战是在检测中肿瘤突变负荷测量的不一致性,以及缺乏有意义的 TMB 分类阈值。在这里,我们描述了一种新的方法,ecTMB(TMB 的估计和分类),它使用一个显式的背景突变模型来稳健地预测 TMB,并将样本分类为由肿瘤突变负荷定义的具有生物学意义的亚型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/add5/7080796/52958fc0cab9/41598_2020_61575_Fig1_HTML.jpg

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