结直肠癌(CRC)是全球胃肠道中第三最常见的恶性肿瘤。5-甲基胞嘧啶(m5C)和长链非编码RNA(lncRNA)在预测CRC患者的预后和免疫反应方面发挥着重要作用。因此，我们建立了一个m5C相关的lncRNA(m5CRlncRNA)模型来研究CRC患者的预后和治疗方法。首先，我们从癌症基因组图谱(TCGA)中获取了CRC的转录组和临床数据。然后，利用共表达分析识别m5CRlncRNA。接着，利用单因素Cox、最小绝对收缩和选择算子(LASSO)和多因素Cox回归分析建立m5C相关的预后特征。此外，进行了Kaplan-Meier分析、ROC、PCA、C指数、富集分析和诊断模型来研究模型。另外，探究了CRC患者的免疫治疗反应和抗肿瘤药物。总共采用了8个m5C相关的lncRNA(AC093157.1、LINC00513、AC025171.4、AC090948.2、ZEB1-AS1、AC109449.1、AC009041.3和LINC02516)构建了一个风险模型，以研究CRC患者的生存和预后。CRC样本分为低风险组和高风险组，后者预后更差。m5C相关的lncRNA模型有助于我们更好地区分不同组CRC患者的免疫治疗反应和抗肿瘤药物的IC50。该研究可能为个体化治疗方法和预测CRC患者预后的新理论提供新的视角。版权所有©2023张鹏等人。

Colorectal cancer (CRC) has been the 3rd most commonly malignant tumor of the gastrointestinal tract in the world. 5-Methylcytosine (m5C) and long noncoding RNAs (lncRNAs) have an essential role in predicting the prognosis and immune response for CRC patients. Therefore, we built a m5C-related lncRNA (m5CRlncRNA) model to investigate the prognosis and treatment methods for CRC patients.Firstly, we secured the transcriptome and clinical data for CRC from The Cancer Genome Atlas (TCGA). Then, m5CRlncRNAs were recognized by coexpression analysis. Then, univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were utilized to build m5C-related prognostic characteristics. Besides, Kaplan-Meier analysis, ROC, PCA, C-index, enrichment analysis, and nomogram were performed to investigate the model. Additionally, immunotherapy responses and antitumor medicines were explored for CRC patients.A total of 8 m5C-related lncRNAs (AC093157.1, LINC00513, AC025171.4, AC090948.2, ZEB1-AS1, AC109449.1, AC009041.3, and LINC02516) were adopted to construct a risk model to investigate survival and prognosis for CRC patients. CRC samples were separated into low- and high-risk groups, with the latter having a worse prognosis. The m5C-related lncRNA model helps us to better distinguish immunotherapy responses and IC50 of antitumor medicines in different groups of CRC patients.The research may give new perspectives on tailored therapy approaches as well as novel theories for forecasting the prognosis of CRC patients.Copyright © 2023 Peng Zhang et al.