Shang Changquan, He Tiancong, Zhang Yi
Department of Surgical Oncology, Minhang Branch, Fudan University Shanghai Cancer Center, Shanghai, China.
PLoS One. 2025 Jul 2;20(7):e0325120. doi: 10.1371/journal.pone.0325120. eCollection 2025.
Hepatocellular carcinoma (HCC) is a prevalent malignancy influenced by the interplay between the immune system and tumor progression, but the detailed biological mechanism still elusive. To address this, we integrate single-cell RNA sequencing (scRNAseq) data with bulk sequencing data to investigate the prognostic significance of tumor-associated macrophages (TAMs) signatures in HCC. Utilizing bioinformatics approaches, including differential gene expression analysis, Cox regression, and logistic regression modeling, we constructed a robust prognostic model that effectively stratifies HCC patients into distinct risk groups with significant differences in survival outcomes. Applying our model to multiple HCC cohorts, robust predictive and prognostic performances were observed. Moreover, examination of the tumor microenvironment (TME) revealed distinct patterns of immune cell infiltration between high-risk and low-risk patient groups, which may contribute to the poorer outcomes observed in high-risk patients. Finally, drug sensitivity and AutoDock simulations suggest that the signature genes we identified could be potential targets for HCC therapy. In summary, this study provides novel insights into the HCC tumor microenvironment and its interaction with TAMs, offering a prognostic model with potential for improving patient stratification and guiding the development of novel therapeutic approaches. Future research ought to concentrate on confirming our findings in larger, prospective studies and examining the functional implications of TAMs in HCC progression.
肝细胞癌（HCC）是一种受免疫系统与肿瘤进展之间相互作用影响的常见恶性肿瘤，但其详细的生物学机制仍不清楚。为了解决这一问题，我们将单细胞RNA测序（scRNAseq）数据与批量测序数据相结合，以研究肿瘤相关巨噬细胞（TAM）特征在HCC中的预后意义。利用生物信息学方法，包括差异基因表达分析、Cox回归和逻辑回归建模，我们构建了一个强大的预后模型，该模型有效地将HCC患者分为不同的风险组，生存结果存在显著差异。将我们的模型应用于多个HCC队列，观察到了强大的预测和预后性能。此外，对肿瘤微环境（TME）的检查揭示了高危和低危患者组之间免疫细胞浸润的不同模式，这可能是高危患者预后较差的原因。最后，药物敏感性和自动对接模拟表明，我们鉴定出的特征基因可能是HCC治疗的潜在靶点。总之，本研究为HCC肿瘤微环境及其与TAM的相互作用提供了新的见解，提供了一个具有改善患者分层潜力并指导新型治疗方法开发的预后模型。未来的研究应集中在更大规模的前瞻性研究中证实我们的发现，并研究TAM在HCC进展中的功能意义。
