Microsatellite instability (MSI) is an effective biomarker for diagnosing Lynch syndrome (LS) and predicting the responsiveness of cancer therapy. MSI testing is conventionally performed by capillary electrophoresis, and MSI status is judged by visual assessment of allele size change. Here, we attempted to develop a quantitative evaluation model of MSI using next-generation sequencing (NGS). Microsatellite markers were analyzed in tumor and non-tumor tissues of colorectal cancer patients by NGS after a single multiplex polymerase chain reaction amplification. The read counts corresponding to microsatellite loci lengths were calculated independently of mapping against a reference genome, and their distribution was digitized by weighted mean. Weighted mean differences between tumor and non-tumor samples with different MSI status were assessed, and cut-off values for each marker in the discovery cohort were determined. Each microsatellite maker was defined as unstable if the weighted mean difference was greater than the cut-off value. In the discovery cohort, the evaluation model demonstrated sensitivity and specificity of 100% for all markers. In the validation cohort, MSI status determined by the new model was consistent with the outcome of the conventional method in 29/30 cases (97%). The single inconsistent case was classified as low-frequency MSI by the conventional method but considered MSI-high by NGS. Genetic testing for mismatch repair genes revealed a pathogenic variant in MSH6 in the discordant case. We successfully developed a quantitative evaluation method for determining MSI status using NGS. This is a robust and sensitive method and could improve LS diagnosis.

微卫星不稳定性 (MSI) 是诊断林奇综合征 (LS) 和预测癌症治疗反应的有效生物标志物。MSI 测试通常通过毛细管电泳进行，MSI 状态通过等位基因大小变化的视觉评估来判断。在这里，我们尝试使用下一代测序 (NGS) 开发 MSI 的定量评估模型。单次多重聚合酶链反应扩增后，通过NGS在结直肠癌患者的肿瘤和非肿瘤组织中分析微卫星标记物。与微卫星基因座长度相对应的读数计数独立于参考基因组的映射计算，并且它们的分布通过加权平均值数字化。评估了具有不同 MSI 状态的肿瘤和非肿瘤样本之间的加权平均差异，并确定了发现队列中每个标记的截止值。如果加权平均差大于临界值，则每个微卫星制造商被定义为不稳定。在发现队列中，评估模型对所有标志物均表现出 100% 的敏感性和特异性。在验证队列中，新模型确定的 MSI 状态与传统方法在 29/30 例 (97%) 中的结果一致。单个不一致的情况被常规方法归类为低频 MSI，但被 NGS 认为是 MSI 高。错配修复基因的基因检测揭示了一个致病性变异 在发现队列中，评估模型对所有标志物均表现出 100% 的敏感性和特异性。在验证队列中，新模型确定的 MSI 状态与传统方法在 29/30 例 (97%) 中的结果一致。单个不一致的情况被常规方法归类为低频 MSI，但被 NGS 认为是 MSI 高。错配修复基因的基因检测揭示了一个致病性变异 在发现队列中，评估模型对所有标志物均表现出 100% 的敏感性和特异性。在验证队列中，新模型确定的 MSI 状态与传统方法在 29/30 例 (97%) 中的结果一致。单个不一致的情况被常规方法归类为低频 MSI，但被 NGS 认为是 MSI 高。错配修复基因的基因检测揭示了一个致病性变异MSH6在不一致的情况下。我们成功开发了一种使用 NGS 确定 MSI 状态的定量评估方法。这是一种稳健且灵敏的方法，可以改善 LS 诊断。