Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, 300121, China.
Beijing USCI Medical Laboratory, Beijing, 100195, China.
J Transl Med. 2020 May 28;18(1):215. doi: 10.1186/s12967-020-02373-1.
With the recent emergence of immune checkpoint inhibitors, microsatellite instability (MSI) status has become an important biomarker for immune checkpoint blockade therapy. There are growing technical demands for the integration of different genomic alterations profiling including MSI analysis in a single assay for full use of the limited tissues.
Tumor and paired control samples from 64 patients with primary colorectal cancer were enrolled in this study, including 14 MSI-high (MSI-H) cases and 50 microsatellite stable (MSS) cases determined by MSI-PCR. All the samples were sequenced by a customized NGS panel covering 2.2 MB. A training dataset of 28 samples was used for selection of microsatellite loci and a novel NGS-based MSI status classifier, USCI-msi, was developed. NGS-based MSI status, single nucleotide variant (SNV) and tumor mutation burden (TMB) were detected for all patients. Most of the patients were also independently detected by immunohistochemistry (IHC) staining.
A 9-loci model for detecting microsatellite instability was able to correctly predict MSI status with 100% sensitivity and specificity compared with MSI-PCR, and 84.3% overall concordance with IHC staining. Mutations in cancer driver genes (APC, TP53, and KRAS) were dispersed in MSI-H and MSS cases, while BRAF p.V600E and frameshifts in TCF7L2 gene occurred only in MSI-H cases. Mismatch repair (MMR)-related genes are highly mutated in MSI-H samples.
We established a new NGS-based MSI classifier, USCI-msi, with as few as 9 microsatellite loci for detecting MSI status in CRC cases. This approach possesses 100% sensitivity and specificity, and performed robustly in samples with low tumor purity.
随着免疫检查点抑制剂的出现，微卫星不稳定性（MSI）状态已成为免疫检查点阻断治疗的重要生物标志物。为了充分利用有限的组织，越来越需要将不同的基因组改变分析（包括 MSI 分析）整合到单个检测中，这对技术提出了更高的要求。
本研究纳入了 64 例原发性结直肠癌患者的肿瘤和配对对照样本，包括 14 例 MSI-高（MSI-H）病例和 50 例微卫星稳定（MSS）病例，这些病例通过 MSI-PCR 确定。所有样本均通过覆盖 2.2MB 的定制 NGS 面板进行测序。我们使用 28 个样本的训练数据集来选择微卫星位点，并开发了一种新的基于 NGS 的 MSI 状态分类器 USCI-msi。对所有患者进行 NGS 检测 MSI 状态、单核苷酸变异（SNV）和肿瘤突变负担（TMB）。大多数患者还通过免疫组织化学（IHC）染色进行了独立检测。
与 MSI-PCR 相比，用于检测微卫星不稳定性的 9 个微卫星模型能够以 100%的灵敏度和特异性正确预测 MSI 状态，与 IHC 染色的总体一致性为 84.3%。癌症驱动基因（APC、TP53 和 KRAS）的突变在 MSI-H 和 MSS 病例中分散存在，而 BRAF p.V600E 和 TCF7L2 基因的移码突变仅发生在 MSI-H 病例中。MSI-H 样本中错配修复（MMR）相关基因高度突变。
我们建立了一种新的基于 NGS 的 MSI 分类器 USCI-msi，仅使用 9 个微卫星来检测 CRC 病例中的 MSI 状态。该方法具有 100%的灵敏度和特异性，在肿瘤纯度低的样本中表现稳健。
