Zhang Nan, Yue Wenli, Jiao Bihang, Cheng Duo, Wang Jingjing, Liang Fang, Wang Yingnan, Liang Xiyue, Li Kunkun, Liu Junwei, Li Yadong
Department of Oncology and Rehabilitation, Zhengzhou Central Hospital Affiliated to Zhengzhou University, No. 16 Tongbai North Road, Zhengzhou, Henan, China.
Department of Gastroenterology, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou, Henan, China.
Infect Agent Cancer. 2025 Feb 7;20(1):9. doi: 10.1186/s13027-025-00640-8.
Colorectal cancer (CRC) ranks among the frequently occurring malignant neoplasms affecting the gastrointestinal tract. This study aimed to explore JAK-STAT signaling pathway related genes in CRC and establish a new prognostic model.
The data set used in this study is from a public database. JAK-STAT-differentially expressed genes (DEGs) were identified through differential expression analysis and weighted gene co-expression network analysis (WGCNA). Prognostic genes were selected from JAK-STAT-DEGs through Mendelian randomization (MR), univariate Cox regression, and least absolute shrinkage and selection operator (LASSO) analyses. The expressions of prognostic genes were verified by RT-qPCR. Then, a risk model was built and validated by the GSE39582. Independent prognostic factors were screened underlying risk scores and different clinical indicators, resulting in the construction of a nomogram. Additionally, immune infiltration, immune scores and immune checkpoint inhibitors analyses and gene set enrichment analysis (GSEA) were carried out.
The 3,668 JAK-STAT-DEGs were obtained by intersection of 5826 CRC-DEGs and 9766 JAK-STAT key module genes. Five prognostic genes were selected (ANK3, F5, FAM50B, KLHL35, MPP2), and their expressions were significantly different between CRC and control groups. A risk model was constructed according to prognostic genes and verified by GSE39582. In addition, the nomogram exhibited superior predictive accuracy for CRC. Furthermore, immune analysis results indicated a notable positive correlation between risk score and the scores of immune (R = 0.486), stromal (R = 0.309), and ESTIMATE (R = 0.422). Immune checkpoint inhibitor ADORA2A (Cor = 0.483263) exhibited the strongest positive correlation with risk score. And MPP2 exhibited the most potent activating influence on the cell cycle pathway, whereas ANK3 demonstrated the most significant inhibitory effect within the apoptosis pathway.
A new JAK-STAT related CRC prognostic model was constructed and validated, which possessed an underlying predictive potential for CRC patients' prognosis and could potentially enhance tailored guidance for immunotherapy.
结直肠癌（CRC）是影响胃肠道的常见恶性肿瘤之一。本研究旨在探索CRC中JAK-STAT信号通路相关基因并建立新的预后模型。
本研究使用的数据集来自公共数据库。通过差异表达分析和加权基因共表达网络分析（WGCNA）鉴定JAK-STAT差异表达基因（DEGs）。通过孟德尔随机化（MR）、单变量Cox回归和最小绝对收缩和选择算子（LASSO）分析从JAK-STAT-DEGs中选择预后基因。通过RT-qPCR验证预后基因的表达。然后，构建风险模型并通过GSE39582进行验证。根据风险评分和不同临床指标筛选独立预后因素，构建列线图。此外，进行免疫浸润、免疫评分和免疫检查点抑制剂分析以及基因集富集分析（GSEA）。
通过5826个CRC-DEGs与9766个JAK-STAT关键模块基因的交集获得3668个JAK-STAT-DEGs。选择了5个预后基因（ANK3、F5、FAM50B、KLHL35、MPP2），它们在CRC组和对照组之间的表达存在显著差异。根据预后基因构建风险模型并通过GSE39582进行验证。此外，列线图对CRC表现出优异的预测准确性。此外，免疫分析结果表明风险评分与免疫评分（R = 0.486）、基质评分（R = 0.309）和ESTIMATE评分（R = 0.422）之间存在显著正相关。免疫检查点抑制剂ADORA2A（Cor = 0.483263）与风险评分的正相关性最强。MPP2对细胞周期通路的激活影响最强，而ANK3在凋亡通路中表现出最显著的抑制作用。
构建并验证了一种新的JAK-STAT相关CRC预后模型，该模型对CRC患者的预后具有潜在预测潜力，并可能增强免疫治疗的个性化指导。
