Impact of single-cell cell cycle regulation of intercellular communication on the prognosis of hepatocellular carcinoma in the tumor microenvironment

Despite the emergence of new therapies such as, immunotherapy, the treatment and diagnosis of Hepatocellular Carcinoma (HCC) still face many challenges, and the therapeutic outcomes for patients remain less than satisfactory. The study identified differentially expressed genes in HCC through differential analysis and then used univariate cox regression analysis to identify genes associated with prognosis. The intersection of these two sets of genes was used to obtain differentially expressed prognostic genes in HCC, which were then subjected to enrichment analysis. We analyzed two single-cell RNA sequencing (scRNA-seq) datasets from HCC patients, comprising 24,637 cells. Non-negative Matrix Factorization (NMF) clustering was used to identify cell cycle regulation in HCC tumor microenvironment (TME) cells, including three cell subpopulations: proliferating cells (PC), dendritic cells (DC), and macrophages (MAC). We employed the CellChat package to analyze cell-cell communication, the Monocle package for pseudotime trajectory analysis, and the SCENIC software package to study gene regulatory networks. Survival analysis was also performed using cell cycle-related features. A total of 26 clusters, including 15 major cell types, were identified in the HCC samples. Complex cell-cell communication networks were observed among these cell types. Enrichment analysis revealed that these cells were mainly enriched in pathways related to the cell cycle. The expression of cell cycle-related genes was elevated in tumor samples, and changes in cell cycle-related genes in specific subtypes were associated with different overall survival rates. The study focused on single-cell level data analysis of the cell cycle. The bubble plot results showed that the cell cycle scores were significantly upregulated in the PC, DC, and MAC subpopulations. Further subtyping revealed that these subtypes exhibited distinct biological states, cell-cell communication, and metabolic pathways. This study demonstrates that cell cycle regulation and cell-cell communication within the HCC tumor microenvironment impact tumor progression and patient prognosis. Cell cycle dysregulation in TME cells correlates with poor prognosis and immunotherapy efficacy, suggesting cell cycle targeting as a therapeutic strategy.

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Publication Details

Journal
Clinical and Experimental Medicine
Published
2025-11-25
DOI
https://doi.org/10.1007/s10238-025-01963-x
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

Impact of single-cell cell cycle regulation of intercellular communication on the prognosis of hepatocellular carcinoma in the tumor microenvironment

Xinglang Mou, Rui Deng, Shuxiong Nong, Cong Hu
Clinical and Experimental Medicine
Single-cell and spatial transcriptomics
article

Impact of single-cell cell cycle regulation of intercellular communication on the prognosis of hepatocellular carcinoma in the tumor microenvironment

Xinglang Mou, Rui Deng, Shuxiong Nong, Cong Hu
article en

Abstract

Despite the emergence of new therapies such as, immunotherapy, the treatment and diagnosis of Hepatocellular Carcinoma (HCC) still face many challenges, and the therapeutic outcomes for patients remain less than satisfactory. The study identified differentially expressed genes in HCC through differential analysis and then used univariate cox regression analysis to identify genes associated with prognosis. The intersection of these two sets of genes was used to obtain differentially expressed prognostic genes in HCC, which were then subjected to enrichment analysis. We analyzed two single-cell RNA sequencing (scRNA-seq) datasets from HCC patients, comprising 24,637 cells. Non-negative Matrix Factorization (NMF) clustering was used to identify cell cycle regulation in HCC tumor microenvironment (TME) cells, including three cell subpopulations: proliferating cells (PC), dendritic cells (DC), and macrophages (MAC). We employed the CellChat package to analyze cell-cell communication, the Monocle package for pseudotime trajectory analysis, and the SCENIC software package to study gene regulatory networks. Survival analysis was also performed using cell cycle-related features. A total of 26 clusters, including 15 major cell types, were identified in the HCC samples. Complex cell-cell communication networks were observed among these cell types. Enrichment analysis revealed that these cells were mainly enriched in pathways related to the cell cycle. The expression of cell cycle-related genes was elevated in tumor samples, and changes in cell cycle-related genes in specific subtypes were associated with different overall survival rates. The study focused on single-cell level data analysis of the cell cycle. The bubble plot results showed that the cell cycle scores were significantly upregulated in the PC, DC, and MAC subpopulations. Further subtyping revealed that these subtypes exhibited distinct biological states, cell-cell communication, and metabolic pathways. This study demonstrates that cell cycle regulation and cell-cell communication within the HCC tumor microenvironment impact tumor progression and patient prognosis. Cell cycle dysregulation in TME cells correlates with poor prognosis and immunotherapy efficacy, suggesting cell cycle targeting as a therapeutic strategy.

Clinical and Experimental MedicineVol. 26(1)
Wuhan University (CN), Zhongnan Hospital of Wuhan University (CN), Affiliated Hospital of Youjiang Medical University for Nationalities (CN), First People's Hospital of Chongqing (CN)
Openalex Percentile: Top 67%
Single-cell and spatial transcriptomics
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