Department of Medical Oncology, Zhongshan Hospital of Fudan University, Xuhui District, Shanghai, People's Republic of China.
Cancer Center, Zhongshan Hospital of Fudan University, Xuhui District, Shanghai, People's Republic of China.
J Physiol Pharmacol. 2022 Apr;73(2). doi: 10.26402/jpp.2022.2.04. Epub 2022 Aug 18.
Whether tumor mutational burden (TMB), which refers to the total number of somatic or acquired mutations per million bases in a particular region of the tumor genome, can serve as a predictive biomarker of immune checkpoint inhibitor (ICI) therapy for colon cancer remains unclear. Hereby, we retrospectively investigated the differentially expressed genes (DEGs) based on the level of TMB and tried to established a risk score model as a novel biomarker. The DNA mutation data were retrieved from the Masked Somatic Mutation in Genomic Data Commons data portal of the Cancer Genome Atlas, where the RNA sequencing data, clinical information, and survival outcomes of patients were downloaded. Patients with incomplete clinical information were excluded. The immune score and stromal score were calculated to investigate immune infiltration. The patients were grouped into TMB-high group and the TMB-low group based on the median value of TMB. An immune relevant gene set was obtained from the Immunology Database and Analysis Portal to identify immune-related DEGs. The Cox proportional hazard model and nomogram were applied to establish the risk model. In results: the TMB value was associated with age (p≤0.001), clinical stage (p≤0.001), N stage (p≤0.001), M stage (p=0.003), and immune score (p≤0.001). Twenty-nine immune-related DEGs were identified as enriched in immune response-related function or pathway and tumorigenesis signaling. Nine of 29 were determined to establish a riskScore model. The riskScore suggested a positive relationship with the TMB value (p=0.033), immune score (p≤0.001), and tumor immune dysfunction and exclusion (TIDE) (p=0.002) and presented an independent prognostic factor (p≤0.001, HR=1.04), which predicted the overall survival with good specificity. We concluded that the combination of TMB with transcriptome expression has a predictive and prognostic value for patients treated with ICIs.
肿瘤突变负荷（TMB）是指肿瘤基因组特定区域每百万碱基中体细胞或获得性突变的总数，它是否可以作为结直肠癌免疫检查点抑制剂（ICI）治疗的预测生物标志物仍不清楚。在此，我们根据 TMB 水平回顾性研究差异表达基因（DEGs），并尝试建立风险评分模型作为一种新的生物标志物。DNA 突变数据从癌症基因组图谱的 Masked Somatic Mutation in Genomic Data Commons 数据门户中检索，其中下载了 RNA 测序数据、患者的临床信息和生存结果。排除临床信息不完整的患者。计算免疫评分和基质评分以研究免疫浸润。根据 TMB 的中位数将患者分为 TMB 高组和 TMB 低组。从免疫数据库和分析门户获得免疫相关基因集，以识别免疫相关 DEGs。应用 Cox 比例风险模型和列线图建立风险模型。结果：TMB 值与年龄（p≤0.001）、临床分期（p≤0.001）、N 分期（p≤0.001）、M 分期（p=0.003）和免疫评分（p≤0.001）相关。鉴定出 29 个与免疫反应相关功能或途径和肿瘤发生信号相关的免疫相关 DEGs。29 个中有 9 个确定用于建立风险评分模型。风险评分与 TMB 值呈正相关（p=0.033）、免疫评分（p≤0.001）和肿瘤免疫功能障碍和排除（TIDE）（p=0.002），并呈现独立的预后因素（p≤0.001，HR=1.04），可特异性预测总生存期。我们得出结论，TMB 与转录组表达的结合对接受 ICI 治疗的患者具有预测和预后价值。
