Table 2_Integrative multi-omics and Mendelian randomization analysis reveal SPP1+ tumor-associated macrophage-driven prognostic signature for hepatocellular carcinoma.docx

BackgroundThe SPP1+ tumor-associated macrophages (TAMs) have been implicated in tumor metastasis and immune evasion. However, the prognostic significance of SPP1+ TAMs in hepatocellular carcinoma (HCC) remains largely unexplored. This study aimed to identify SPP1+ TAMs-related genes and construct a model to predict overall survival (OS) in HCC patients.
MethodsSingle-cell RNA sequencing (scRNA-seq) datasets from HCC patients were analyzed to identify SPP1+ TAMs. SPP1+ TAMs-related risk score (STRS) was developed using Mendelian randomization (MR) analysis and Least Absolute Shrinkage and Selection Operator (LASSO) regression. HCC patients from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts were stratified into high- and low-STRS groups based on STRS. Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curve analysis, and functional enrichment analysis were performed to assess the prognostic value of STRS.
ResultsSPP1+ TAMs exhibited strong associations with immunosuppressive functions. 16 SPP1+ TAMs-related genes were used to construct STRS. Patients in the high-STRS group had significantly worse OS than those in the low-STRS group (p < 0.001). ROC analysis demonstrated robust predictive power, with AUC values ranging from 0.685 to 0.748 for 1-year OS, 0.717 to 0.739 for 2-year OS, and 0.719 to 0.738 for 3-year OS. The STRS model also exhibited strong predictive capability for the distinction of drug resistance.
ConclusionThis study identified SPP1+ TAMs-related genes as key prognostic indicators in HCC. The STRS model provides an effective tool for predicting patient survival and may facilitate personalized treatment strategies for HCC. These findings enhance the understanding of TAMs-driven immune modulation in HCC and highlight potential therapeutic targets for improving patient outcomes.

背景
SPP1阳性肿瘤相关巨噬细胞（tumor-associated macrophages, TAMs）已被证实参与肿瘤转移与免疫逃逸过程，但SPP1+ TAMs在肝细胞癌（hepatocellular carcinoma, HCC）中的预后意义仍有待深入探究。本研究旨在筛选SPP1+ TAMs相关基因，并构建模型以预测肝细胞癌患者的总生存期（overall survival, OS）。
方法
本研究通过分析肝细胞癌患者的单细胞RNA测序（single-cell RNA sequencing, scRNA-seq）数据集鉴定SPP1+ TAMs；采用孟德尔随机化（Mendelian randomization, MR）分析与最小绝对收缩和选择算子（Least Absolute Shrinkage and Selection Operator, LASSO）回归，构建SPP1+ TAMs相关风险评分（SPP1+ TAMs-related risk score, STRS）。基于该评分，将来自癌症基因组图谱（Cancer Genome Atlas, TCGA）与基因表达综合数据库（Gene Expression Omnibus, GEO）队列的肝细胞癌患者划分为高STRS组与低STRS组。随后通过Kaplan-Meier生存分析、受试者工作特征（receiver operating characteristic, ROC）曲线分析及功能富集分析，评估STRS的预后价值。
结果
SPP1+ TAMs与免疫抑制功能显著相关。本研究共筛选出16个SPP1+ TAMs相关基因用于构建STRS模型。高STRS组患者的总生存期显著劣于低STRS组患者（p < 0.001）。ROC分析显示该模型具备良好的预测效能：1年总生存期的曲线下面积（AUC）值范围为0.685~0.748，2年总生存期的AUC值范围为0.717~0.739，3年总生存期的AUC值范围为0.719~0.738。此外，STRS模型对药物耐药性的区分同样表现出较强的预测能力。
结论
本研究证实SPP1+ TAMs相关基因可作为肝细胞癌的关键预后标志物。STRS模型可为肝细胞癌患者的生存期预测提供有效工具，有助于推动肝癌患者的个性化治疗策略制定。本研究结果加深了对TAMs介导的肝细胞癌免疫调控机制的理解，并为改善患者预后的潜在治疗靶点提供了新的研究方向。