Single-cell reanalysis highlights the MIF-PTGDR axis as a candidate immunoregulatory program in hepatocellular
Dingzhi Liu1, Lang Yan1, Huiya Chen2
1Hepatological Surgery Department, Chongqing University Three Gorges Hospital, Chongqing, China.
Background:
Hepatocellular carcinoma (HCC) remains one of the most lethal malignancies worldwide, and immune evasion is a major determinant of tumor progression and therapeutic resistance. The tumor microenvironment (TME) contains multiple dysfunctional and suppressive immune states, among which regulatory T cells (Tregs) and exhausted T-cell populations are particularly important. Despite recent advances in HCC biology, the intercellular signaling programs associated with these immune states remain incompletely characterized at single-cell resolution. Therefore, this study aimed to reanalyze public single-cell RNA sequencing (scRNA-seq) data to identify candidate interaction networks and immunoregulatory signaling axes associated with T-cell dysfunction in HCC.
Methods:
Publicly available single-cell RNA sequencing data were obtained from the Gene Expression Omnibus (GEO) database and analyzed in a reanalysis framework focused on immune-cell heterogeneity. Quality control, normalization, dimensionality reduction, and clustering were performed using Seurat-based workflows. Cell-type annotation was conducted primarily through canonical marker gene expression patterns. Differential expression, cell-cell communication analysis, trajectory inference, gene co-expression analysis, and pathway enrichment analysis were used to characterize signaling programs associated with dysfunctional T-cell states, with particular attention to macrophage migration inhibitory factor (MIF) and prostaglandin D2 receptor (PTGDR) signaling.
Results:
Reanalysis of the single-cell dataset identified major cellular populations including CD8 + T cells, regulatory T cells (Tregs), macrophages, and proliferating cells, highlighting marked heterogeneity within the HCC microenvironment. Three Treg-associated subclusters, designated Treg-C1, Treg-C2, and Treg-C3, showed distinct transcriptional characteristics. Cell-cell communication analysis suggested that MIF signaling through CD74, CXCR4, and CD44 may represent a prominent immunoregulatory communication program linking tumor-associated cell populations with T-cell compartments. PTGDR was enriched in selected immune-cell populations and was associated with gene programs related to cytokine signaling, cell adhesion, and T-cell activation. Trajectory and co-expression analyses further supported the presence of dynamic immune-state transitions and heterogeneous regulatory programs within the analyzed dataset.
Conclusion:
In conclusion, this single-cell reanalysis delineated interaction patterns among immune-associated cell populations in HCC and highlighted the MIF-CD74/CXCR4/CD44 and PTGDR signaling axes as candidate immunoregulatory programs. These findings refine the interpretation of T-cell dysfunction in the HCC microenvironment and provide a rationale for further mechanistic and translational validation, rather than direct confirmation of therapeutic targets. Clinical Trial Registration This study is not a clinical trial.
