ArticleDiscover oncology2026
Single-cell reanalysis highlights the MIF-PTGDR axis as a candidate immunoregulatory program in hepatocellular carcinoma.
Article in Discover oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundHepatocellular 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.
methodsPublicly 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.
resultsReanalysis 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.
conclusionIn 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.
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