标题： 基于免疫浸润的风险评分系统在结直肠腺癌中的预后分层应用 显示英文标题

标题： An Immune Infiltration-Based Risk Scoring System for Prognostic Stratification in Colorectal Adenocarcinoma

摘要： 背景：结直肠腺癌（CRC）仍然是全球癌症相关死亡的主要原因，尽管治疗取得了进展，但患者的预后仍然存在差异。基于临床病理变量的传统预后方法无法完全捕捉疾病的生物学复杂性。本研究旨在开发一种基于肿瘤浸润免疫细胞（TIIC相关基因）的基因风险评分系统，以改善CRC的预后评估。方法：分析了TCGA-CRC的RNA-seq基因表达和临床病理数据（647个肿瘤样本，51个正常组织），通过与CIBERSORTx数据库比较来识别差异表达的TIIC相关基因。进行了单变量和多变量Cox分析以筛选预后标志物。应用高斯混合模型对预后模型进行聚类，并选择具有最稳健基因组合的模型。生成的风险评分系统在外部队列（GSE39582）中进行了验证，并与临床病理变量结合以开发预后列线图。结果：从128个TIIC相关基因中，确定了一个由CCL8和TYR组成的最佳预后模型。风险评分计算为0.152*Exp(CCL8) - 0.516*Exp(TYR)。Kaplan-Meier分析证实了TCGA-CRC（p < 0.05）和GSE39582（p < 0.05）中高风险组和低风险组之间显著的生存差异。时间依赖性ROC分析显示，在TCGA-CRC和GSE39582中，1年、3年和5年生存率的AUC值范围为0.605至0.696。多变量Cox分析将TNM_T、TNM_N和风险评分识别为独立的预后因素。结论：我们基于CCL8和TYR的风险评分系统能够有效地将CRC患者分为不同的预后群体，并可能指导治疗决策，特别是在与TNM分期结合在列线图中时尤其如此。 显示英文摘要

摘要： Background: Colorectal adenocarcinoma (CRC) remains a leading cause of cancer-related mortality worldwide, with variable patient outcomes despite treatment advances. Traditional prognostic methods based on clinicopathological variables alone do not fully capture the biological complexity of the disease. This study aims to develop a risk scoring system based on genes associated with tumor-infiltrating immune cells (TIIC-associated genes) to improve prognostic assessment in CRC. Methods: RNA-seq gene expression and clinicopathological data from TCGA-CRC (647 tumor samples, 51 normal tissues) were analyzed to identify differentially expressed TIIC-associated genes through comparison with the CIBERSORTx database. Univariate and multivariate Cox analyses were performed to screen for prognostic markers. A Gaussian mixture model was applied to cluster prognostic models and select the model with the most robust gene combination. The resulting risk scoring system was validated in an external cohort (GSE39582) and integrated with clinicopathological variables to develop a prognostic nomogram. Results: From 128 TIIC-associated genes, an optimal prognostic model comprising CCL8 and TYR was identified. The risk score was calculated as 0.152*Exp(CCL8) - 0.516*Exp(TYR). Kaplan-Meier analysis confirmed significant survival differences between high-risk and low-risk groups in both TCGA-CRC (p < 0.05) and GSE39582 (p < 0.05). Time-dependent ROC analysis showed AUC values ranging from 0.605 to 0.696 for 1-year, 3-year, and 5-year survival in TCGA-CRC and GSE39582. Multivariate Cox analysis identified TNM_T, TNM_N, and risk score as independent prognostic factors. Conclusion: Our risk scoring system based on CCL8 and TYR effectively stratifies CRC patients into distinct prognostic groups and could guide treatment decisions, particularly when integrated with TNM staging in a nomogram.