累计的证据突出展示了多样的蛋白质翻译后修饰（PTM）在结直肠癌（CRC）的发生和进展中的生物学意义。本研究分析了十种 PTM 模式（泛素化、甲基化、磷酸化、糖基化、乙酰化、SUMO化、柠檬酰化、尼酰化、美拉酰化和ADP核糖基化）以用于模型构建。建立了一个具有14个基因签名的翻译后修饰指数（PTMI）。在九个独立数据集的验证后发现，高 PTMI 的 CRC 患者预后较差。通过将 PTMI 与临床特征结合，构建了一个预测性能优异的格点图。通过无监督聚类，识别出两个 CRC 分子亚型，其存活时间有明显差异。此外，PTMI 与已知的免疫调节因子和肿瘤微环境成分相关。与高 PTMI 患者相比，低 PTMI 患者对氟尿嘧啶类化疗和免疫检查点阻断疗法的反应更好，这一点在多个独立数据集中得到验证。然而，高 PTMI 患者可能对贝伐单抗更敏感。总之，我们通过全面分析多样的蛋白质翻译后修饰模式建立了一种新的 PTMI 模型，可以准确预测 CRC 患者的临床预后和治疗反应。©2023. 作者或许可的排他许可给 Springer Science+Business Media, LLC，属于 Springer Nature 的一部分。

Accumulated evidence highlights the biological significance of diverse protein post-translational modifications (PTMs) in tumorigenicity and progression of colorectal cancer (CRC). In this study, ten PTM patterns (ubiquitination, methylation, phosphorylation, glycosylation, acetylation, SUMOylation, citrullination, neddylation, palmitoylation, and ADP-ribosylation) were analyzed for model construction. A post-translational modification index (PTMI) with a 14-gene signature was established. CRC patients with high PTMI had a worse prognosis after validating in nine independent datasets. By incorporating PTMI with clinical features, a nomogram with excellent predictive performance was constructed. Two molecular subtypes of CRC with obvious difference in survival time were identified by unsupervised clustering. Furthermore, PTMI was related to known immunoregulators and key tumor microenvironment components. Low-PTMI patients responded better to fluorouracil-based chemotherapy and immune checkpoint blockade therapy compared to high-PTMI patients, which was validated in multiple independent datasets. However, patients with high PTMI might be sensitive to bevacizumab. In short, we established a novel PTMI model by comprehensively analyzing diverse post-translational modification patterns, which can accurately predict clinical prognosis and treatment response of CRC patients.© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.