Mao Rui, Yang Fan, Wang Zheng, Xu Chenxin, Liu Qian, Liu Yanjun, Zhang Tongtong
The Center of Gastrointestinal and Minimally Invasive Surgery, Affiliated Hospital of Southwest Jiaotong University, Chengdu, China.
Emergency Department, Peking University Third Hospital, School of Medicine, Peking University, Beijing, China.
Front Cell Dev Biol. 2021 Feb 25;9:625212. doi: 10.3389/fcell.2021.625212. eCollection 2021.
Some colorectal adenocarcinoma (CRC) patients are susceptible to recurrence, and they rapidly progress to advanced cancer stages and have a poor prognosis. There is an urgent need for efficient screening criteria to identify patients who tend to relapse in order to treat them earlier and more systematically.
We identified two groups of patients with significantly different outcomes by unsupervised cluster analysis of GSE39582 based on 101 significantly differentially expressed immune genes. To develop an accurate and specific signature based on immune-related genes to predict the recurrence of CRC, a multivariate Cox risk regression model was constructed with a training cohort composed of 519 CRC samples. The model was then validated using 129, 292, and 446 samples in the real-time quantitative reverse transcription PCR (qRT-PCR), test, and validation cohorts, respectively.
This classification system can also be used to predict the prognosis in clinical subgroups and patients with different mutation states. Four independent datasets, including qRT-PCR and The Cancer Genome Atlas (TCGA), demonstrated that they can also be used to accurately predict the overall survival of CRC patients. Further analysis suggested that high-risk patients were characterized by worse effects of chemotherapy and immunotherapy, as well as lower immune scores. Ultimately, the signature was identified as an independent prognostic factor.
The signature can accurately predict recurrence and overall survival in patients with CRC and may serve as a powerful prognostic tool to further optimize cancer immunotherapy.
一些结直肠癌（CRC）患者易复发，他们会迅速进展至癌症晚期且预后较差。迫切需要有效的筛查标准来识别易复发的患者，以便更早、更系统地对其进行治疗。
我们基于101个显著差异表达的免疫基因，通过对GSE39582进行无监督聚类分析，确定了两组预后显著不同的患者。为了开发基于免疫相关基因的准确且特异的标志物来预测CRC的复发，我们构建了一个多变量Cox风险回归模型，其训练队列由519个CRC样本组成。然后分别使用实时定量逆转录PCR（qRT-PCR）、测试和验证队列中的129、292和446个样本对该模型进行验证。
该分类系统还可用于预测临床亚组和不同突变状态患者的预后。四个独立数据集，包括qRT-PCR和癌症基因组图谱（TCGA），表明它们也可用于准确预测CRC患者的总生存期。进一步分析表明，高危患者的特征是化疗和免疫治疗效果较差以及免疫评分较低。最终，该标志物被确定为独立的预后因素。
该标志物可准确预测CRC患者的复发和总生存期，并可能作为一种强大的预后工具，以进一步优化癌症免疫治疗。
