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解析癌症免疫:凝血信号与BIRC2作为预测性免疫治疗架构

Unravelling Cancer Immunity: Coagulation.Sig and BIRC2 as Predictive Immunotherapeutic Architects.

作者信息

Yao Ziang, Fan Jun, Bai Yucheng, He Jiakai, Zhang Xiang, Zhang Renquan, Xue Lei

机构信息

Department of Traditional Chinese Medicine, Peking University People's Hospital, Beijing, China.

Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.

出版信息

J Cell Mol Med. 2025 Apr;29(7):e70525. doi: 10.1111/jcmm.70525.

Abstract

Immune checkpoint inhibitors (ICIs) represent a groundbreaking advancement in cancer therapy, substantially improving patient survival rates. Our comprehensive research reveals a significant positive correlation between coagulation scores and immune-related gene expression across 30 diverse cancer types. Notably, tumours exhibiting high coagulation scores demonstrated enhanced infiltration of cytotoxic immune cells, including CD8 T cells, natural killer (NK) cells, and macrophages. Leveraging the TCGA pan-cancer database, we developed the Coagulation.Sig model, a sophisticated predictive framework utilising a coagulation-related genes (CRGs) to forecast immunotherapy outcomes. Through rigorous analysis of ten ICI-treated cohorts, we identified and validated seven critical CRGs: BIRC2, HMGB1, STAT2, IFNAR1, BID, SPATA2, IL33 and IFNG, which form the foundation of our predictive model. Functional analyses revealed that low-risk tumours characterised by higher immune cell populations, particularly CD8 T cells, demonstrated superior ICI responses. These tumours also exhibited increased mutation rates, elevated neoantigen loads, and greater TCR/BCR diversity. Conversely, high-risk tumours displayed pronounced intratumor heterogeneity (ITH) and elevated NRF2 pathway activity, mechanisms strongly associated with immune evasion. Experimental validation highlighted BIRC2 as a promising therapeutic target. Targeted BIRC2 knockdown, when combined with anti-PD-1 therapy, significantly suppressed tumour growth, enhanced CD8 T cell infiltration, and amplified IFN-γ and TNF-α secretion in tumour models. Our findings position the Coagulation.Sig model as a novel, comprehensive approach to personalised cancer treatment, with BIRC2 emerging as both a predictive biomarker and a potential therapeutic intervention point.

摘要

免疫检查点抑制剂(ICIs)是癌症治疗领域的一项突破性进展,显著提高了患者的生存率。我们的综合研究表明,在30种不同癌症类型中,凝血评分与免疫相关基因表达之间存在显著正相关。值得注意的是,凝血评分高的肿瘤表现出细胞毒性免疫细胞(包括CD8 T细胞、自然杀伤(NK)细胞和巨噬细胞)浸润增强。利用TCGA泛癌数据库,我们开发了Coagulation.Sig模型,这是一个利用凝血相关基因(CRGs)预测免疫治疗结果的复杂预测框架。通过对10个接受ICI治疗的队列进行严格分析,我们识别并验证了7个关键CRGs:BIRC2、HMGB1、STAT2、IFNAR1、BID、SPATA2、IL33和IFNG,它们构成了我们预测模型的基础。功能分析表明,以较高免疫细胞群体(特别是CD8 T细胞)为特征的低风险肿瘤表现出更好的ICI反应。这些肿瘤还表现出更高的突变率、更高的新抗原负荷和更大的TCR/BCR多样性。相反,高风险肿瘤表现出明显的肿瘤内异质性(ITH)和NRF2通路活性升高,这些机制与免疫逃逸密切相关。实验验证突出了BIRC2作为一个有前景的治疗靶点。在肿瘤模型中,靶向敲低BIRC2并联合抗PD-1治疗可显著抑制肿瘤生长、增强CD8 T细胞浸润并放大IFN-γ和TNF-α分泌。我们的研究结果将Coagulation.Sig模型定位为一种新颖、全面的个性化癌症治疗方法,BIRC2既作为预测生物标志物又作为潜在的治疗干预点而出现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d25a/11955421/784f7bc4372f/JCMM-29-e70525-g006.jpg

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