通讯作者: 尤青海, amormor@126.com

DOI：10.12201/bmr.202509.00054

Construction of a TFF3-Related Prognostic Model for Lung Adenocarcinoma Based on Lasso-Cox Regression and Its Predictive Value for Immunotherapy

• 摘要：目的 构建一种肠三叶因子(Trefoil factor 3, TFF3)相关的肺腺癌(Lung adenocarcinoma, LUAD)预后模型，并分析此模型对免疫治疗的预测价值。方法 利用肿瘤免疫分析(Tumor immune estimation resource, TIMER)、UALCAN和CPTAC数据库分析TFF3表达及其与LUAD分期的关系。利用肿瘤免疫单细胞中心(Tumor immune single cell hub, TISCH)数据库分析TFF3在肺癌组织内不同细胞中的表达并行定位分析。根据人类蛋白质图谱(Human protein atlas, HPA)数据库从免疫组化方面分析TFF3在LUAD组织内的表达。根据TFF3表达水平，将癌症基因组图谱(The cancer genome atlas, TGCA)数据库中LUAD患者分为两组，行差异分析后获得TFF3相关的差异表达基因。然后，利用单因素生存分析和Lasso-Cox回归构建TFF3相关的LUAD预后标签及其风险分数的计算公式，利用Kaplan-Meier和受试者工作特征(Receiver operating characteristic, ROC)曲线评估该标签的预测效能。根据风险分数、T分期、N分期、年龄和性别，建立LUAD预后列线图(nomogram)，分析风险分数等参数对LUAD进行预后的直观预测。结果 TFF3 mRNA和蛋白在LUAD组织内表达比正常对照组多，且LUAD分期越高，TFF3 mRNA和蛋白表达越多。单细胞数据分析示TFF3主要表达在肺癌组织的肿瘤细胞内，在免疫细胞等细胞中基本不表达，且免疫组化证实TFF3主要在LUAD的肿瘤细胞内表达。差异分析筛选得到600个TFF3相关的差异基因，单因素分析进一步筛选12个有预后价值的差异基因，使用Lasso-Cox回归筛选并构建包含8个基因的TFF3相关的预后基因标签，计算得出相关的风险分数，低风险组LUAD患者总体预后显著优于高风险组(P<0.001),且预后敏感度和特异度较好。LUAD分期增加，风险分数随之增加。根据风险分数绘制的列线图结合临床参数能很好的预测患者预后。结论 基于TFF3相关基因构建的预后模型不仅可以有效预测患者总体生存率，还可预测免疫治疗疗效。

  关键词： 肺腺癌；肠三叶因子；免疫检查点抑制剂；列线图；Lasso-Cox回归; ; ; ; 

   

  Abstract: Objective To construct a prognostic model of Lung Adenocarcinoma (LUAD) related to intestinal Trefoil Factor 3 (TFF3) and evaluate the predictive value of this model for immunotherapy. Methods　 Tumor immune estimation resource(TIMER), UALCAN，and CPTAC databases were utilized to analyze TFF3 expression and its correlation with LUAD staging. The tumor immune single cell hub(TISCH) database was employed to examine TFF3 expression across different cell types within lung cancer tissues，followed by localization analysis. Immunohistochemical expression of TFF3 in LUAD tissues was analyzed using the human protein atlas (HPA) database. LUAD patients in the cancer genome atlas (TGCA) database were stratified into two groups based on TFF3 expression levels. Differential gene expression analysis identified TFF3-associated differentially expressed genes. Univariate survival analysis and Lasso-Cox regression were then employed to construct TFF3-related LUAD prognostic signatures and their risk score calculation formulas. The predictive efficacy of these signatures was evaluated using Kaplan-Meier curves and receiver operating characteristic (ROC) curves. A LUAD prognostic nomogram was established based on risk score，T stage，N stage，age，and gender to enable intuitive prediction of LUAD prognosis using parameters including risk score. Results　TFF3 mRNA and protein expression were higher in LUAD tissues than in normal controls，with increased expression correlating with higher LUAD staging. Single-cell data analysis revealed TFF3 expression primarily localized to tumor cells within LUAD tissues, with negligible expression in immune cells and other cell types. Immunohistochemistry confirmed TFF3 expression predominantly occurred within LUAD tumor cells. Differential analysis identified 600 TFF3-associated differentially expressed genes. Univariate analysis further selected 12 differentially expressed genes with prognostic value. Using Lasso-Cox regression，an 8-gene TFF3-associated prognostic signature was constructed. The calculated risk scores showed that LUAD patients in the low-risk group had significantly better overall prognosis than those in the high-risk group (P<0.001)，with good sensitivity and specificity. Risk scores increased with LUAD stage progression. A risk-score-based nomogram, integrated with clinical parameters, effectively predicted patient prognosis. Conclusion　The TFF3-based prognostic model not only predicts overall survival but also forecasts immunotherapy efficacy.

  Key words: Lung adenocarcinoma; TFF3; Immune checkpoint inhibitor; Nomogram; Lasso-Cox regression

  提交时间：2025-09-26

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• 序号	提交日期	编号	操作
  1	2025-09-16	10.12201/bmr.202509.00054V1	下载

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