一种与血管生成和中性粒细胞胞外诱捕网相关基因调控结肠癌肿瘤微环境的预后模型
A Prognostic Model of Angiogenesis and Neutrophil Extracellular Traps Related Genes Manipulating Tumor Microenvironment in Colon Cancer.
作者信息
Zhang Dongsheng, Zhao Yan, Wang Shirui, Wang Xiaowei, Sun Yueming
机构信息
Department of Colorectal Surgery, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Colorectal Institute of Nanjing Medical University, Nanjing, China.
出版信息
J Cancer. 2023 Jul 9;14(11):2109-2127. doi: 10.7150/jca.85778. eCollection 2023.
Colon adenocarcinoma (COAD) is one of the most common carcinomas worldwide. The main causes of cancer-related mortality of COAD are metastases. The fundamental processes for how angiogenesis and neutrophil extracellular traps (NETs) contributing to tumor progression and metastasis are still uncertain. In our study, The Cancer Genome Atlas (TCGA)-COAD dataset (train set) and GSE17536 (test set) were analyzed. Angiogenesis potential index (API) and NETs potential index (NPI) based on angiogenesis and NETs-related genes were respectively built using bioinformatic methods and machine learning algorithms. Subjects were split into groups with low API/NPI or high API/NPI. Survival analysis showed the high API and high NPI patients with the worst survival compared with the others. Between the high API/NPI group and the other groups, differentially expressed genes (DEGs) were found. A four-gene signature (TIMP1, FSL3, CALB2, and FABP4) was included in a risk model based on least absolute shrinkage and selection operator (LASSO) analysis. Additionally, the model displayed a significant association with many immune microenvironment characteristics. Finally, we verified the clinical significance of CALB2 expression and its role to promote the invasion and migration of colon cancer cells in vitro.
结肠腺癌(COAD)是全球最常见的癌症之一。COAD与癌症相关的死亡主要原因是转移。血管生成和中性粒细胞胞外陷阱(NETs)如何促进肿瘤进展和转移的基本过程仍不明确。在我们的研究中,分析了癌症基因组图谱(TCGA)-COAD数据集(训练集)和GSE17536(测试集)。基于血管生成和NETs相关基因,分别使用生物信息学方法和机器学习算法构建了血管生成潜力指数(API)和NETs潜力指数(NPI)。将受试者分为低API/NPI组或高API/NPI组。生存分析显示,与其他患者相比,高API和高NPI患者的生存率最差。在高API/NPI组和其他组之间,发现了差异表达基因(DEGs)。基于最小绝对收缩和选择算子(LASSO)分析,一个四基因特征(TIMP1、FSL3、CALB2和FABP4)被纳入风险模型。此外,该模型与许多免疫微环境特征显示出显著关联。最后,我们验证了CALB2表达的临床意义及其在体外促进结肠癌细胞侵袭和迁移的作用。
相似文献
引用本文的文献
World J Gastrointest Oncol. 2025-8-15
Endocr Metab Immune Disord Drug Targets. 2024
本文引用的文献
Exp Hematol Oncol. 2022-11-16
J Exp Clin Cancer Res. 2022-10-11
Front Cell Dev Biol. 2022-8-19
Front Pharmacol. 2022-7-11
J Immunother Cancer. 2022-6
Front Cell Dev Biol. 2021-12-13