血管生成在结直肠癌（CRC）中发挥着关键作用，但其潜在机制仍需进一步探索。本研究旨在通过综合多组学分析阐明血管生成相关基因（ARG）在结直肠癌中的重要性。根据ARGs表达对结直肠癌患者进行分类，形成血管生成相关基因簇（ARC）。我们研究了 ARC 与患者生存、临床特征、共有分子亚型 (CMS)、癌症干细胞 (CSC) 指数、肿瘤微环境 (TME)、基因突变和免疫治疗反应之间的相关性。利用三种机器学习算法（LASSO、Xgboost 和决策树），我们筛选与 ARC 相关的关键 ARG，并在独立队列中进一步验证。在 scRNA-seq 水平上开发并分析了基于关键 ARG 的预后特征。通过 RT-PCR 测定对外部队列、临床组织和血液样本中的基因表达进行验证。确定了两种不同的 ARC 亚型，它们与患者生存、临床特征、CMS、CSC 指数和 TME 显着相关，但与患者生存率、临床特征、CMS、CSC 指数和 TME 无关。基因突变。四个基因（S100A4、COL3A1、TIMP1 和 APP）被确定为关键 ARC，能够区分 ARC 亚型。基于这些基因的预后特征有效地将患者分为高风险或低风险类别。 scRNA-seq 分析表明这些基因主要在免疫细胞而不是癌细胞中表达。在两个外部队列中的验证以及通过临床样本证实了 CRC 和对照之间的显着表达差异。这项研究确定了 CRC 中的两种 ARG 亚型，并强调了与这些亚型相关的四个关键基因，为个性化 CRC 治疗策略提供了新的见解。版权所有 © 2024 Wei，谢、刘、邓、陈、吕、唐、胡。

Angiogenesis plays a pivotal role in colorectal cancer (CRC), yet its underlying mechanisms demand further exploration. This study aimed to elucidate the significance of angiogenesis-related genes (ARGs) in CRC through comprehensive multi-omics analysis.CRC patients were categorized according to ARGs expression to form angiogenesis-related clusters (ARCs). We investigated the correlation between ARCs and patient survival, clinical features, consensus molecular subtypes (CMS), cancer stem cell (CSC) index, tumor microenvironment (TME), gene mutations, and response to immunotherapy. Utilizing three machine learning algorithms (LASSO, Xgboost, and Decision Tree), we screen key ARGs associated with ARCs, further validated in independent cohorts. A prognostic signature based on key ARGs was developed and analyzed at the scRNA-seq level. Validation of gene expression in external cohorts, clinical tissues, and blood samples was conducted via RT-PCR assay.Two distinct ARC subtypes were identified and were significantly associated with patient survival, clinical features, CMS, CSC index, and TME, but not with gene mutations. Four genes (S100A4, COL3A1, TIMP1, and APP) were identified as key ARCs, capable of distinguishing ARC subtypes. The prognostic signature based on these genes effectively stratified patients into high- or low-risk categories. scRNA-seq analysis showed that these genes were predominantly expressed in immune cells rather than in cancer cells. Validation in two external cohorts and through clinical samples confirmed significant expression differences between CRC and controls.This study identified two ARG subtypes in CRC and highlighted four key genes associated with these subtypes, offering new insights into personalized CRC treatment strategies.Copyright © 2024 Wei, Xie, Liu, Deng, Chen, Lv, Tang and Hu.