Chen Xueshu, Chen Haixing, Liu Mi, Li Mi, Zhang Fujuan, Ouyang Weiwei, Li Xiaoxu, Yang Yong, Long Niya
Department of Molecular Pathology Laboratory, The Affiliated Cancer Hospital of Guizhou Medical University, Guiyang, Guizhou, 550000, China.
Department of Thoracic Oncology, The Affiliated Cancer Hospital of Guizhou Medical University, Guiyang, Guizhou, 550000, China.
BMC Cancer. 2025 Mar 10;25(1):427. doi: 10.1186/s12885-025-13719-7.
Tumor mutation burden (TMB) is a predictive biomarker for assessing the response of various tumor types to immune checkpoint inhibitors (ICI). TMB is quantified based on somatic mutations identified by next-generation sequencing (NGS) using targeted panel data. This study aimed to investigate whether different NGS methods will affect the results of TMB detection in solid tumors.
In this study, a hybrid capture NGS method was performed to identify Tumor-only (TO) tissue and tumor tissue and white blood cells Tumor Control (TC). The accuracy and specificity of the two employed methods were evaluated by the identification and analysis of standard reference data. Based on the quality control of FFPE samples, 24 pathological and imaging confirmed solid tumor samples were compared to assess the differences between the two methods in identifying and incorporating the mutation sites and the effect on TMB detection.
The data identified 298 common genes in the detection range of TO and TC methods. The detection range of these genes primarily comprised exons and some introns. The coefficient of variation (CV%) between the detected variant and true mutation frequencies was < 10%, confirming their accuracy and specificity. Both methods detected increased mutations of TP53, CDKN2 A, KRAS, PTEN, EGFR, PIK3 CA, BRAF, BRCA2, FGFR2, and NRAS. The consistency rate of TMB was observed as 92% (22/24). The chi-square test indicated a significant difference in TMB results between TO and TC (χ = 16.667, p = 0.000, p < 0.001). Furthermore, Cohen's kappa analysis showed consistency in the TMB values detected by TO and TC methods, which were good and had high repeatability (kappa = 0.833, p = 0.000, p < 0.001). The Venn analysis revealed that the two methods identified and included different TMB sites, which in turn affected the TMB calculation results.
This study revealed that different algorithms and design panels for mutation filtering affect the TMB test results. When the TMB result is near the 10 mut/Mb threshold, different methods may yield different results. Moreover, a single test result can affect clinical treatment decisions. Therefore, it is recommended to use TO or TC combined with other tests for evaluating somatic mutations.
肿瘤突变负荷(TMB)是评估各种肿瘤类型对免疫检查点抑制剂(ICI)反应的预测生物标志物。TMB基于使用靶向测序数据通过下一代测序(NGS)鉴定的体细胞突变进行量化。本研究旨在调查不同的NGS方法是否会影响实体瘤中TMB检测的结果。
在本研究中,采用杂交捕获NGS方法鉴定仅肿瘤(TO)组织以及肿瘤组织与白细胞的肿瘤对照(TC)。通过对标准参考数据的鉴定和分析评估所采用的两种方法的准确性和特异性。基于福尔马林固定石蜡包埋(FFPE)样本的质量控制,比较24例经病理和影像学证实的实体瘤样本,以评估两种方法在鉴定和纳入突变位点方面的差异以及对TMB检测的影响。
数据在TO和TC方法的检测范围内鉴定出298个常见基因。这些基因的检测范围主要包括外显子和一些内含子。检测到的变异频率与真实突变频率之间的变异系数(CV%)<10%,证实了它们的准确性和特异性。两种方法均检测到TP53、CDKN2 A、KRAS、PTEN、EGFR、PIK3 CA、BRAF、BRCA2、FGFR2和NRAS的突变增加。观察到TMB的一致性率为92%(22/24)。卡方检验表明TO和TC之间的TMB结果存在显著差异(χ=16.667,p=0.000,p<0.001)。此外,科恩kappa分析显示TO和TC方法检测到的TMB值具有一致性,一致性良好且重复性高(kappa=0.833,p=0.000,p<0.001)。维恩分析显示两种方法鉴定并纳入了不同的TMB位点,进而影响了TMB计算结果。
本研究表明,用于突变筛选的不同算法和设计面板会影响TMB检测结果。当TMB结果接近10个突变/Mb阈值时,不同方法可能产生不同结果。此外,单一检测结果可能影响临床治疗决策。因此,建议使用TO或TC并结合其他检测来评估体细胞突变。