Analysis of the molecular nature associated with microsatellite status in colon cancer identifies clinical implications for immunotherapy.
Analysis of the molecular nature associated with microsatellite status in colon cancer identifies clinical implications for immunotherapy.
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与结肠癌微卫星状态相关的分子性质分析确定了免疫治疗的临床意义
DOI：
10.1136/jitc-2020-001437
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发表时间：
2020-10
影响因子：
10.9
通讯作者：
Liu F
中科院分区：
文献类型：
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作者：
Bao X;Zhang H;Wu W;Cheng S;Dai X;Zhu X;Fu Q;Tong Z;Liu L;Zheng Y;Zhao P;Fang W;Liu F
背景结肠癌中的微卫星不稳定性意味着检查点阻断免疫治疗后有良好的治疗结果。然而，微卫星不稳定性的分子性质尚未得到很好的阐明。方法我们通过评估大量转录组和单细胞转录组来检查结肠癌的免疫微环境，重点关注公共数据库中结直肠癌中微卫星稳定性（MSS）和微卫星不稳定性（MSI）的分子性质。通过癌症基因组图谱 (TCGA) 中的随机森林算法分析突变模式与微卫星状态的关联，并通过我们的内部数据集（39 个肿瘤突变负荷 (TMB)-低 MSS 结肠癌、10 个 TMB-高 MSS 结肠癌、15 个 MSI 结肠癌）进行验证。构建了一个预后模型来预测生存潜力并通过神经网络对微卫星状态进行分层。结果 尽管 MSI 结肠癌中存在敌对的 CD8+ 细胞毒性 T 淋巴细胞 (CTL)/Th1 微环境，但在 MSI 结肠癌中在单细胞水平上发现了高比例的耗竭 CD8+ T 细胞和免疫检查点表达上调，表明耗竭 T 细胞状态对细胞毒性 T 细胞活性的潜在中和作用。在来自 MSI 结肠癌的 CD8+ T 细胞中观察到 PD1 更加均一的高表达模式；然而，在 MSS 患者中发现了一小群高表达检查点分子的 CD8+ T 细胞。随机森林算法预测了 TCGA 结肠癌队列中与 MSI 状态相关的重要突变，我们的内部队列验证了 MSI 结肠癌中 BRAF、ARID1A、RNF43 和 KM2B 突变的较高频率。建立了强大的微卫星状态相关基因特征来预测预后并区分 MSI 和 MSS 肿瘤。构建了使用微卫星状态相关基因特征表达谱的神经网络。采用受试者工作特征曲线来评价神经网络的准确率，达到100%。结论 我们的分析揭示了 MSI 和 MSS 结肠癌分子性质和基因组变异的差异。微卫星状态相关基因特征可以更好地预测结肠癌患者的预后以及对基于免疫检查点抑制剂的免疫治疗和抗 VEGF 治疗联合治疗的反应。
Background Microsatellite instability in colon cancer implies favorable therapeutic outcomes after checkpoint blockade immunotherapy. However, the molecular nature of microsatellite instability is not well elucidated. Methods We examined the immune microenvironment of colon cancer using assessments of the bulk transcriptome and the single-cell transcriptome focusing on molecular nature of microsatellite stability (MSS) and microsatellite instability (MSI) in colorectal cancer from a public database. The association of the mutation pattern and microsatellite status was analyzed by a random forest algorithm in The Cancer Genome Atlas (TCGA) and validated by our in-house dataset (39 tumor mutational burden (TMB)-low MSS colon cancer, 10 TMB-high MSS colon cancer, 15 MSI colon cancer). A prognostic model was constructed to predict the survival potential and stratify microsatellite status by a neural network. Results Despite the hostile CD8+ cytotoxic T lymphocyte (CTL)/Th1 microenvironment in MSI colon cancer, a high percentage of exhausted CD8+ T cells and upregulated expression of immune checkpoints were identified in MSI colon cancer at the single-cell level, indicating the potential neutralizing effect of cytotoxic T-cell activity by exhausted T-cell status. A more homogeneous highly expressed pattern of PD1 was observed in CD8+ T cells from MSI colon cancer; however, a small subgroup of CD8+ T cells with high expression of checkpoint molecules was identified in MSS patients. A random forest algorithm predicted important mutations that were associated with MSI status in the TCGA colon cancer cohort, and our in-house cohort validated higher frequencies of BRAF, ARID1A, RNF43, and KM2B mutations in MSI colon cancer. A robust microsatellite status–related gene signature was built to predict the prognosis and differentiate between MSI and MSS tumors. A neural network using the expression profile of the microsatellite status–related gene signature was constructed. A receiver operating characteristic curve was used to evaluate the accuracy rate of neural network, reaching 100%. Conclusion Our analysis unraveled the difference in the molecular nature and genomic variance in MSI and MSS colon cancer. The microsatellite status–related gene signature is better at predicting the prognosis of patients with colon cancer and response to the combination of immune checkpoint inhibitor–based immunotherapy and anti-VEGF therapy.
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影响因子：
3
作者：
Amarasinghe KC;Li J;Halgamuge SK
通讯作者：
Halgamuge SK
WGCNA：用于加权相关网络分析的 R 包。
影响因子：
3
作者：
Langfelder P;Horvath S
通讯作者：
Horvath S
影响因子：
4.7
作者：
Bao, Xuanwen;Shi, Run;Wang, Yanfang
通讯作者：
Wang, Yanfang
影响因子：
64.8
作者：
Koo, Bon-Kyoung;Spit, Maureen;Clevers, Hans
通讯作者：
Clevers, Hans
使用下一代 DNA 测序数据进行变异发现和基因分型的框架。
影响因子：
30.8
作者：
通讯作者：
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