结直肠腺癌（COAD）是一个严重的公共卫生问题，在世界上是第三常见的癌症和第二致命的癌症。2020年与COAD相关的癌症死亡中约有9.4％是由COAD引起的。缺陷离层死亡是一种特殊形式的程序性细胞死亡，它在肿瘤侵袭和转移中起着重要作用。反离层死因子的存在与肿瘤侵袭能力和药物抵抗力有关。本研究使用了差异表达分析、功能注释分析和机器学习等多种生物信息学方法。我们从基因表达全球数据库（GEO）和癌症基因组图谱数据库（TCGA）中获取了COAD患者的RNA测序和临床数据。采用多因素分析和Lasso-Cox回归构建预测总体生存（OS）的预测模型。免疫组化（IHC）是验证与COAD中离层死相关的七个基因表达的方法。我们确定了七个与COAD生存和预后相关的离层死相关基因，并通过KM生存曲线和ROC曲线验证了它们在预测结直肠腺癌预后方面的准确性。由NAT1、CDC25C、ATP2A3、MMP3、EEF1A2、PBK和TIMP1组成的七基因风险评分显示出较强的预测价值。同时，我们制作了一个预测COAD患者生存率的预测模型。免疫浸润分析显示T细胞、CD4记忆性细胞和巨噬细胞M0在COAD中比例较高，并且与肿瘤免疫相关的11个基因扮演重要角色。基于GDSC2的药物敏感性分析显示在COAD中有6种药物具有显著意义。离层死相关基因在预测COAD预后方面具有潜在价值，并为COAD的新治疗策略开发提供线索。免疫浸润和药物敏感性结果为寻找COAD的新个体化治疗选择提供重要线索。这些发现还暗示了可能影响预后的机制。这些结果是制定个体化治疗和管理患者预后的起点。© 2023年 Springer Nature Limited.

Colon adenocarcinoma (COAD) is a serious public health problem, the third most common cancer and the second most deadly cancer in the world. About 9.4% of cancer-related deaths in 2020 were due to COAD. Anoikis is a specialized form of programmed cell death that plays an important role in tumor invasion and metastasis. The presence of anti-anoikis factors is associated with tumor aggressiveness and drug resistance. Various bioinformatic methods, such as differential expression analysis, and functional annotation analysis, machine learning, were used in this study. RNA-sequencing and clinical data from COAD patients were obtained from the Gene expression omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Construction of a prognostic nomogram for predicting overall survival (OS) using multivariate analysis and Lasso-Cox regression. Immunohistochemistry (IHC) was our method of validating the expression of seven genes that are linked to anoikis in COAD. We identified seven anoikis-related genes as predictors of COAD survival and prognosis, and confirmed their accuracy in predicting colon adenocarcinoma prognosis by KM survival curves and ROC curves. A seven-gene risk score consisting of NAT1, CDC25C, ATP2A3, MMP3, EEF1A2, PBK, and TIMP1 showed strong prognostic value. Meanwhile, we made a nomogram to predict the survival rate of COAD patients. The immune infiltration assay showed T cells. CD4 memory. Rest and macrophages. M0 has a higher proportion in COAD, and 11 genes related to tumor immunity are important. GDSC2-based drug susceptibility analysis showed that 6 out of 198 drugs were significant in COAD. Anoikis-related genes have potential value in predicting the prognosis of COAD and provide clues for developing new therapeutic strategies for COAD. Immune infiltration and drug susceptibility results provide important clues for finding new personalized treatment options for COAD. These findings also suggest possible mechanisms that may affect prognosis. These results are the starting point for planning individualized treatment and managing patient outcomes.© 2023. Springer Nature Limited.