中国科学技术大学孙成小组取得一项新突破。他们揭示了空间免疫评分系统预测肝癌复发。相关论文于2025年3月12日发表在《自然》杂志上。

在这里，研究团队观察了61例患者的侵袭性前部和肿瘤中心的自然杀伤（NK）细胞的空间分布和复发相关。利用极端梯度增强和反方差加权，该团队基于5种生物标志物（SPON2、ZFP36L2、ZFP36、VIM和HLA-DRB1）的空间表达模式建立了肿瘤免疫微环境空间（TIMES）评分，以预测HCC复发风险。TIMES评分（风险比= 88.2,P = 0.001）优于目前用于患者风险分层的标准工具，包括TNM和BCLC系统。该团队在来自5个多中心队列的231例患者中验证了该模型，实现了82.2%的真实世界准确性和85.7%的特异性。这些生物标记物的预测能力是通过整合它们的空间分布而不是单独的个体标记物表达水平而出现的。包括NK细胞特异性SPON2敲除小鼠在内的体内模型显示，SPON2增强IFNγ分泌和NK细胞浸润。他们的研究介绍了TIMES，这是一种可公开访问的预测HCC复发风险的工具，为早期HCC的治疗决策提供了潜在的见解。

据介绍，鉴于肝细胞癌（HCC）切除术后的高复发率，提高对术后复发高风险患者的早期识别将有助于改善患者的预后并优先考虑医疗保健问题。

附：英文原文

Title: Spatial immune scoring system predicts hepatocellular carcinoma recurrence

Author: Jia, Gengjie, He, Peiqi, Dai, Tianli, Goh, Denise, Wang, Jiabei, Sun, Mengyuan, Wee, Felicia, Li, Fuling, Lim, Jeffrey Chun Tatt, Hao, Shuxia, Liu, Yao, Lim, Tony Kiat Hon, Ngo, Nye-Thane, Tao, Qingping, Wang, Wei, Umar, Ahitsham, Nashan, Bjrn, Zhang, Yongchang, Ding, Chen, Yeong, Joe, Liu, Lianxin, Sun, Cheng

Issue&Volume: 2025-03-12

Abstract: Given the high recurrence rates of hepatocellular carcinoma (HCC) post-resection1,2,3, improved early identification of patients at high risk for post-resection recurrence would help to improve patient outcomes and prioritize healthcare resources4,5,6. Here we observed a spatial and HCC recurrence-associated distribution of natural killer (NK) cells in the invasive front and tumour centre from 61 patients. Using extreme gradient boosting and inverse-variance weighting, we developed the tumour immune microenvironment spatial (TIMES) score based on the spatial expression patterns of five biomarkers (SPON2, ZFP36L2, ZFP36, VIM and HLA-DRB1) to predict HCC recurrence risk. The TIMES score (hazard ratio=88.2, P<0.001) outperformed current standard tools for patient risk stratification including the TNM and BCLC systems. We validated the model in 231 patients from five multicentred cohorts, achieving a real-world accuracy of 82.2% and specificity of 85.7%. The predictive power of these biomarkers emerged through the integration of their spatial distributions, rather than individual marker expression levels alone. In vivo models, including NK cell-specific Spon2-knockout mice, revealed that SPON2 enhances IFNγ secretion and NK cell infiltration at the invasive front. Our study introduces TIMES, a publicly accessible tool for predicting HCC recurrence risk, offering insights into its potential to inform treatment decisions for early-stage HCC.

DOI: 10.1038/s41586-025-08668-x

Source: https://www.nature.com/articles/s41586-025-08668-x