Cui Zhongfeng, Li Hongzhi, Liu Chunli, Wang Juan, Chen Chunguang, Hu Shanlei, Zhao Xiaoli, Li Guangming
Department of Clinical Laboratory, Henan Provincial Infectious Disease Hospital, Zhengzhou 450000, China.
Department of Tuberculosis, Henan Provincial Infectious Disease Hospital, Zhengzhou 450000, China.
Aging (Albany NY). 2024 Apr 5;16(7):6550-6565. doi: 10.18632/aging.205723.
The treatment and prognosis of patients with advanced hepatocellular carcinoma (HCC) have been a major medical challenge. Unraveling the landscape of tumor immune infiltrating cells (TIICs) in the immune microenvironment of HCC is of great significance to probe the molecular mechanisms.
Based on single-cell data of HCC, the cell landscape was revealed from the perspective of TIICs. Special cell subpopulations were determined by the expression levels of marker genes. Differential expression analysis was conducted. The activity of each subpopulation was determined based on the highly expressed genes. CTLA4+ T-cell subpopulations affecting the prognosis of HCC were determined based on survival analysis. A single-cell regulatory network inference and clustering analysis was also performed to determine the transcription factor regulatory networks in the CTLA4+ T cell subpopulations.
10 cell types were identified and NK cells and T cells showed high abundance in tumor tissues. Two NK cells subpopulations were present, FGFBP2+ NK cells, B3GNT7+ NK cells. Four T cells subpopulations were present, LAG3+ T cells, CTLA4+ T cells, RCAN3+ T cells, and HPGDS+ Th2 cells. FGFBP2+ NK cells, and CTLA4+ T cells were the exhaustive subpopulation. High CTLA4+ T cells contributed to poor prognostic outcomes and promoted tumor progression. Finally, a network of transcription factors regulated by NR3C1, STAT1, and STAT3, which were activated, was present in CTLA4+ T cells.
CTLA4+ T cell subsets in HCC exhibited functional exhaustion characteristics that probably inhibited T cell function through a transcription factor network dominated by NR3C1, STAT1, and STAT3.
晚期肝细胞癌（HCC）患者的治疗和预后一直是重大医学挑战。剖析HCC免疫微环境中肿瘤免疫浸润细胞（TIICs）的格局对于探究分子机制具有重要意义。
基于HCC的单细胞数据，从TIICs角度揭示细胞格局。通过标记基因的表达水平确定特殊细胞亚群。进行差异表达分析。基于高表达基因确定每个亚群的活性。基于生存分析确定影响HCC预后的CTLA4 + T细胞亚群。还进行了单细胞调控网络推断和聚类分析，以确定CTLA4 + T细胞亚群中的转录因子调控网络。
鉴定出10种细胞类型，肿瘤组织中NK细胞和T细胞丰度较高。存在两个NK细胞亚群，即FGFBP2 + NK细胞、B3GNT7 + NK细胞。存在四个T细胞亚群，即LAG3 + T细胞、CTLA4 + T细胞、RCAN3 + T细胞和HPGDS + Th2细胞。FGFBP2 + NK细胞和CTLA4 + T细胞是详尽的亚群。高CTLA4 + T细胞导致预后不良并促进肿瘤进展。最后，CTLA4 + T细胞中存在由被激活的NR3C1、STAT1和STAT3调控的转录因子网络。
HCC中的CTLA4 + T细胞亚群表现出功能耗竭特征，可能通过由NR3C1、STAT1和STAT3主导的转录因子网络抑制T细胞功能。
