Mao Zun, Gao Zhixiang, Long Ruyu, Guo Huimin, Chen Long, Huan Sheng, Yin Guoping
Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, China.
Department of Gastroenterology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China.
Front Immunol. 2024 Jul 1;15:1409448. doi: 10.3389/fimmu.2024.1409448. eCollection 2024.
The mitotic catastrophe (MC) pathway plays an important role in hepatocellular carcinoma (HCC) progression and tumor microenvironment (TME) regulation. However, the mechanisms linking MC heterogeneity to immune evasion and treatment response remain unclear.
Based on 94 previously published highly correlated genes for MC, HCC patients' data from the Cancer Genome Atlas (TCGA) and changes in immune signatures and prognostic stratification were studied. Time and spatial-specific differences for MCGs were assessed by single-cell RNA sequencing and spatial transcriptome (ST) analysis. Multiple external databases (GEO, ICGC) were employed to construct an MC-related riskscore model.
Identification of two MC-related subtypes in HCC patients from TCGA, with clear differences in immune signatures and prognostic risk stratification. Spatial mapping further associates low MC tumor regions with significant immune escape-related signaling. Nomogram combining MC riskscore and traditional indicators was validated great effect for early prediction of HCC patient outcomes.
MC heterogeneity enables immune escape and therapy resistance in HCC. The MC gene signature serves as a reliable prognostic indicator for liver cancer. By revealing clear immune and spatial heterogeneity of HCC, our integrated approach provides contextual therapeutic strategies for optimal clinical decision-making.
有丝分裂灾难(MC)途径在肝细胞癌(HCC)进展和肿瘤微环境(TME)调节中起重要作用。然而,将MC异质性与免疫逃逸及治疗反应联系起来的机制仍不清楚。
基于先前发表的94个与MC高度相关的基因,研究了癌症基因组图谱(TCGA)中HCC患者的数据以及免疫特征和预后分层的变化。通过单细胞RNA测序和空间转录组(ST)分析评估MCG的时间和空间特异性差异。使用多个外部数据库(GEO、ICGC)构建MC相关风险评分模型。
在来自TCGA的HCC患者中鉴定出两种MC相关亚型,在免疫特征和预后风险分层方面存在明显差异。空间映射进一步将低MC肿瘤区域与显著的免疫逃逸相关信号联系起来。结合MC风险评分和传统指标的列线图在早期预测HCC患者预后方面被验证具有很好的效果。
MC异质性导致HCC中的免疫逃逸和治疗耐药。MC基因特征可作为肝癌可靠的预后指标。通过揭示HCC明确的免疫和空间异质性,我们的综合方法为优化临床决策提供了背景治疗策略。