尽管新辅助治疗给患者带来了诸多益处，但并不是所有患者都能从中受益。趋化因子在肿瘤微环境中发挥着至关重要的作用，与结直肠癌的预后和治疗密切相关。因此，构建基于趋化因子的预后模型将有助于风险分层，为个体化治疗提供参考。利用LASSO-Cox预测模型，利用TCGA和GEO数据库的数据，建立了基于趋化因子的预后模型。然后，我们的探索重点是趋化因子特征与免疫景观、体细胞突变、拷贝数变异和药物敏感性等元素之间的相关性。通过 scRNA-seq 鉴定CXCL10 M1 巨噬细胞。 Monocle2 显示细胞伪时间轨迹，CellChat 表征细胞间通讯。 CytoTRACE 分析了新辅助治疗的干性，SCENIC 检测了细胞类型特异性调节。最后通过多重免疫荧光实验进行验证。构建并验证了基于15种趋化因子的模型。高风险评分与较差的预后以及晚期 TNM 和临床分期相关。风险评分较高的个体表现出化疗耐药性增加的倾向。随后的 scRNA-seq 数据分析表明，肿瘤组织中存在较高 CXCL10 M1 巨噬细胞的患者更有可能从新辅助治疗中受益。我们通过整合单细胞和批量 RNA-seq 数据开发了基于趋化因子的预后模型。此外，我们揭示了新辅助治疗结果中的上皮细胞异质性，并将 CXCL10 M1 巨噬细胞确定为潜在的治疗反应预测因子。这些发现可以极大地促进风险分层，并为个性化治疗方法的发展提供关键指导。版权所有 © 2024 Tuersun、Huo、Lv、Zhang、Chen、Zhao、Feng、Xu、Mao、Xue 和 Lu。

Although neoadjuvant therapy has brought numerous benefits to patients, not all patients can benefit from it. Chemokines play a crucial role in the tumor microenvironment and are closely associated with the prognosis and treatment of colorectal cancer. Therefore, constructing a prognostic model based on chemokines will help risk stratification and providing a reference for the personalized treatment.Employing LASSO-Cox predictive modeling, a chemokine-based prognostic model was formulated, harnessing the data from TCGA and GEO databases. Then, our exploration focused on the correlation between the chemokine signature and elements such as the immune landscape, somatic mutations, copy number variations, and drug sensitivity. CXCL10+M1 macrophages identified via scRNA-seq. Monocle2 showed cell pseudotime trajectories, CellChat characterized intercellular communication. CytoTRACE analyzed neoadjuvant therapy stemness, SCENIC detected cell type-specific regulation. Lastly, validation was performed through multiplex immunofluorescence experiments.A model based on 15 chemokines was constructed and validated. High-risk scores correlated with poorer prognosis and advanced TNM and clinical stages. Individuals presenting elevated risk scores demonstrated an increased propensity towards the development of chemotherapy resistance. Subsequent scRNA-seq data analysis indicated that patients with higher presence of CXCL10+ M1 macrophages in tumor tissues are more likely to benefit from neoadjuvant therapy.We developed a chemokine-based prognostic model by integrating both single-cell and bulk RNA-seq data. Furthermore, we revealed epithelial cell heterogeneity in neoadjuvant outcomes and identified CXCL10+ M1 macrophages as potential therapy response predictors. These findings could significantly contribute to risk stratification and serve as a key guide for the advancement of personalized therapeutic approaches.Copyright © 2024 Tuersun, Huo, Lv, Zhang, Chen, Zhao, Feng, Xu, Mao, Xue and Lu.