Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Aahui, China.
World J Surg Oncol. 2020 Jun 29;18(1):146. doi: 10.1186/s12957-020-01921-9.
Colon adenocarcinoma (COAD) is a gastrointestinal tumor with a high degree of malignancy. Its deterioration process is closely related to the tumor microenvironment, and transcription factors (TF) play a regulatory role in this process. Currently, there is a lack of exploration between the genes related to the COAD tumor microenvironment and the survival prognosis of patients. Models composed of multiple genes usually predict the survival prognosis of patients more accurately than single genes. We can analyze the multigene models that can predict the prognosis of COAD from the current database.
The limma package of the R programming language is used for gene differential expression analysis. Kaplan-Meier curve is used to analyze the relationship between the patient risk score model and survival data. The hazard model is used to analyze the relationship between the risk score and the clinical data of COAD patients. The information of immune genes and immune cells is obtained from IMMPORT database and TIMER database. Receiver operating characteristic (ROC) curve is used to judge the stability of the model.
We found 7 immune genes, which can built a risk score model to predict the survival prognosis of COAD. According to univariate and multivariate analysis, the risk score can be used as an independent predictor. The content of some immune microenvironment cells will also increase as the risk score increases.
We found 7 immune genes, such as SLC10A2 (solute carrier family 10 member 2), CXCL3 (C-X-C motif chemokine ligand 3), IGHV5-51 (immunoglobulin heavy variable 5-51), INHBA (inhibin subunit beta A), STC1 (stanniocalcin 1), UCN (urocortin), and OXTR (oxytocin receptor), can constitute a model for predicting the prognosis of COAD. They may provide potential therapeutic targets for clinical treatment of COAD.
结肠腺癌（COAD）是一种高度恶性的胃肠道肿瘤。其恶化过程与肿瘤微环境密切相关，转录因子（TF）在这一过程中发挥调节作用。目前，COAD 肿瘤微环境相关基因与患者生存预后之间的关系仍缺乏探索。由多个基因组成的模型通常比单个基因更能准确预测患者的生存预后。我们可以从当前的数据库中分析能够预测 COAD 预后的多基因模型。
使用 R 编程语言的 limma 包进行基因差异表达分析。Kaplan-Meier 曲线用于分析患者风险评分模型与生存数据之间的关系。风险模型用于分析风险评分与 COAD 患者临床数据之间的关系。免疫基因和免疫细胞的信息从 IMMPORT 数据库和 TIMER 数据库中获得。接收者操作特征（ROC）曲线用于判断模型的稳定性。
我们发现了 7 个免疫基因，可以构建一个风险评分模型来预测 COAD 的生存预后。根据单变量和多变量分析，风险评分可以作为独立的预测因子。随着风险评分的增加，某些免疫微环境细胞的含量也会增加。
我们发现了 7 个免疫基因，如 SLC10A2（溶质载体家族 10 成员 2）、CXCL3（C-X-C 基序趋化因子配体 3）、IGHV5-51（免疫球蛋白重链可变区 5-51）、INHBA（抑制素亚基β A）、STC1（斯钙素 1）、UCN（尿皮质素）和 OXTR（催产素受体），可以构成一个预测 COAD 预后的模型。它们可能为 COAD 的临床治疗提供潜在的治疗靶点。
