二硫化合物病是一种新识别的非程序性细胞死亡模式，与葡萄糖代谢密切相关。升高的糖酵解是肿瘤细胞的一个重要代谢特征，满足了其快速生长和进展的能量需求。我们的研究旨在开发一种与二硫化合物病和糖酵解相关的基因（DGRG）风险评分签名，以预测CRC患者的预后和ICI治疗反应能力。首先，我们从TCGA和GEO数据库中获取了CRC患者的基因表达和临床资料。利用加权基因共表达网络分析，我们确定了与二硫化合物病和糖酵解活性之间最强相关性的核心基因。接下来，通过单变量和最小绝对收缩和选择操作方法的Cox回归方法，成功开发了DGRG风险评分签名。基于DGRG风险评分的示意图进一步提高了预测性能。此外，进行了一系列系统分析，以揭示DGRG风险评分与肿瘤微环境的相关性。结果显示，DGRG风险水平低的CRC患者具有上调的免疫细胞浸润、增强的代谢活性和增高的基因突变频率，而高风险患者则相反。此外，我们的研究确定了低风险CRC患者作为免疫检查点抑制剂（ICI）治疗的潜在受益者。我们的研究重点强调了DGRG风险评分签名在预后预测和ICI反应性确定方面的潜在应用价值，展示了有希望的临床应用价值。© 2023. Springer Nature Limited.

Disulfidptosis is a newly-identified non-programmed cell death mode with tight associations with glucose metabolism. Elevated glycolysis is an important metabolic feature of tumor cells, which fulfills the energy requirement for their rapid growth and progression. Our present study determined to develop a disulfidptosis and glycolysis related gene (DGRG) risk score signature to predict the prognosis and ICI therapeutic responsiveness for CRC patients. First, the gene expression and clinical profiles for CRC patients were obtained from TCGA and GEO database. Using weighted gene co-expression network analysis, we identified hub genes showing the strongest correlations with both disulfidptosis and glycolysis activities. Next, a DGRG risk score signature was successfully developed through univariate and least absolute shrinkage and selection operator method Cox regression method. A DGRG risk score-based nomogram could further enhance the predictive performance. In addition, an array of systemic analysis was performed to unravel the correlation of DGRG risk score with tumor microenvironment. The results showed that CRC patients with low DGRG risk level had up-regulated immune cell infiltrations, enhanced metabolic activities and heightened gene mutation frequencies, while high risk patients was the opposite. Moreover, our present study identified low risk CRC patients as potential beneficiaries from immune checkpoint inhibitor (ICI) therapies. Our present work highlighted the potential utility of DGRG risk score signature in prognosis prediction and ICI responsiveness determination for CRC patients, which demonstrated promising clinical application value.© 2023. Springer Nature Limited.