Department of Gastroenterology, The People's Hospital of Guangxi Zhuang Autonomous Region, No.6 Tao-Yuan Road, Nanning, 530021, Guangxi, China.
Department of Gastroenterology, First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi, China.
BMC Cancer. 2023 Aug 18;23(1):773. doi: 10.1186/s12885-023-11277-4.
The tumor microenvironment (TME) plays a crucial role in tumorigenesis, progression, and therapeutic response in many cancers. This study aimed to comprehensively investigate the role of TME in colorectal cancer (CRC) by generating a TMEscore based on gene expression.
The TME patterns of CRC datasets were investigated, and the TMEscores were calculated. An unsupervised clustering method was used to divide samples into clusters. The associations between TMEscores and clinical features, prognosis, immune score, gene mutations, and immune checkpoint inhibitors were analyzed. A TME signature was constructed using the TMEscore-related genes. The results were validated using external and clinical cohorts.
The TME pattern landscape was for CRC was examined using 960 samples, and then the TMEscore pattern of CRC datasets was evaluated. Two TMEscore clusters were identified, and the high TMEscore cluster was associated with early-stage CRC and better prognosis in patients with CRC when compared with the low TMEscore clusters. The high TMEscore cluster indicated elevated tumor cell scores and tumor gene mutation burden, and decreased tumor purity, when compared with the low TMEscore cluster. Patients with high TMEscore were more likely to respond to immune checkpoint therapy than those with low TMEscore. A TME signature was constructed using the TMEscore-related genes superimposing the results of two machine learning methods (LASSO and XGBoost algorithms), and a TMEscore-related four-gene signature was established, which had a high predictive value for discriminating patients from different TMEscore clusters. The prognostic value of the TMEscore was validated in two independent cohorts, and the expression of TME signature genes was verified in four external cohorts and clinical samples.
Our study provides a comprehensive description of TME characteristics in CRC and demonstrates that the TMEscore is a reliable prognostic biomarker and predictive indicator for patients with CRC undergoing immunotherapy.
肿瘤微环境(TME)在许多癌症的肿瘤发生、进展和治疗反应中起着至关重要的作用。本研究旨在通过基于基因表达生成 TMEscore 来全面研究 TME 在结直肠癌(CRC)中的作用。
研究了 CRC 数据集的 TME 模式,并计算了 TMEscore。使用无监督聚类方法将样本分为聚类。分析了 TMEscore 与临床特征、预后、免疫评分、基因突变和免疫检查点抑制剂之间的关联。使用 TMEscore 相关基因构建了 TME 特征。使用外部和临床队列验证了结果。
使用 960 个样本检查了 CRC 的 TME 模式景观,然后评估了 CRC 数据集的 TMEscore 模式。确定了两个 TMEscore 聚类,与低 TMEscore 聚类相比,高 TMEscore 聚类与 CRC 的早期阶段和 CRC 患者的更好预后相关。高 TMEscore 聚类表明肿瘤细胞评分和肿瘤基因突变负担升高,而肿瘤纯度降低。与低 TMEscore 聚类相比,高 TMEscore 的患者更有可能对免疫检查点治疗有反应。使用 TMEscore 相关基因构建了 TME 特征,叠加了两种机器学习方法(LASSO 和 XGBoost 算法)的结果,并建立了 TMEscore 相关的四个基因特征,该特征对区分不同 TMEscore 聚类的患者具有很高的预测价值。在两个独立的队列中验证了 TMEscore 的预后价值,并在四个外部队列和临床样本中验证了 TME 特征基因的表达。
本研究全面描述了 CRC 中 TME 的特征,并表明 TMEscore 是 CRC 患者免疫治疗的可靠预后生物标志物和预测指标。