Guo Wenbing, Fu Yelin, Jin Liangliang, Song Kai, Yu Ruihan, Li Tianhao, Qi Lishuang, Gu Yunyan, Zhao Wenyuan, Guo Zheng
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China;
Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350122, China.
J Cancer. 2020 Jan 1;11(4):883-892. doi: 10.7150/jca.34363. eCollection 2020.
The clinical applicability of the whole-exome sequencing (WES) in estimating tumor mutational burden (TMB) is currently limited by high cost, time-consuming and tissue availability. And given to the differences in the mutational landscapes among different types of cancer, we aimed to develop a cancer-specific signature to estimate TMB for right-sided colon cancer patients (RCC). Using WES data of 315 RCC patients, we identified the exons in which the number of mutational sites of the coding DNA sequences associated with TMB through linear regression analysis. Then, among these exons, we extracted a signature composed by 102 exons (0.13 Mbp) through a heuristic selection procedure. The TMB estimated by the signature was highly correlated with those calculated by WES in the discovery dataset (R=0.9869) and three independent validation datasets (R=0.9351, R=0.8063 and R=0.9527, respectively). And the performance of the signature was superior to a colorectal-specific TMB estimation model contained 22 genes (0.24 Mbp). Moreover, between TMB-high and TMB-low RCC patients, there were significantly differences in the frequencies of microsatellite instability status, CpG island methylator phenotype, , and / mutation status (<0.01). However, the performances of the signature in other types of cancer were dramatically degraded (left-sided colon cancer, R=0.7849 and 0.9407, respectively; rectum, R=0.5955 and R=0.965, respectively; breast cancer, R=0.8444; lung cancer, R=0.5963), suggesting that it was necessary to develop cancer-specific TMB estimated signatures to estimate precisely the TMB in different types of cancer. In summary, we developed an exon signature that can accurately estimate TMB in RCC patients, and the cost and time required for the assessment of TMB can be considerably decreased, making it more suitable for blood and/or biopsy samples.
全外显子组测序(WES)在评估肿瘤突变负荷(TMB)方面的临床适用性目前受到高成本、耗时和组织可用性的限制。鉴于不同类型癌症的突变图谱存在差异,我们旨在开发一种针对特定癌症的特征来估计右侧结肠癌患者(RCC)的TMB。利用315例RCC患者的WES数据,我们通过线性回归分析确定了与TMB相关的编码DNA序列突变位点数量的外显子。然后,在这些外显子中,我们通过启发式选择程序提取了一个由102个外显子(约0.13 Mbp)组成的特征。在发现数据集中,该特征估计的TMB与WES计算的TMB高度相关(R = 0.9869),在三个独立验证数据集中也高度相关(分别为R = 0.9351、R = 0.8063和R = 0.9527)。并且该特征的性能优于一个包含22个基因(约0.24 Mbp)的结直肠癌特异性TMB估计模型。此外,在TMB高和TMB低的RCC患者之间,微卫星不稳定性状态、CpG岛甲基化表型以及 和 / 突变状态的频率存在显著差异(<0.01)。然而,该特征在其他类型癌症中的性能显著下降(左侧结肠癌,分别为R = 0.7849和0.9407;直肠癌,分别为R = 0.5955和0.965;乳腺癌,R = 0.8444;肺癌,R = 0.5963),这表明有必要开发针对特定癌症的TMB估计特征以精确估计不同类型癌症中的TMB。总之,我们开发了一种外显子特征,可准确估计RCC患者的TMB,并且评估TMB所需的成本和时间可大幅降低,使其更适合血液和/或活检样本。