Potential crosstalk between Naïve CD4 T cells and SPP1 Macrophages is associated with clinical outcome and therapeutic response in hepatocellular carcinoma.

BACKGROUND

The highly heterogeneity of the tumor microenvironment (TME) in hepatocellular carcinoma (HCC) results in diverse clinical outcomes and therapeutic responses. This study aimed to investigate potential intercellular crosstalk and its impact on clinical outcomes and therapeutic responses.

METHODS

Single-cell RNA sequencing (scRNA-seq), spatial transcriptomics (ST) and bulk RNA sequencing (RNA-seq) datasets were integrated to comprehensively analyze the intercellular interactions within the TME. Multiplex immunohistochemistry was conducted to validate the intercellular interactions. A machine learning-based integrative procedure was used in bulk RNA-seq datasets to generate a risk model to predict prognosis and therapeutic responses.

RESULTS

Survival analyses based on the bulk RNA-seq datasets revealed the negative impact of the naïve Cluster of Differentiation 4 (CD4) T cells and Secreted Phosphoprotein 1 (SPP1) macrophages on prognosis. Furthermore, their intricate intercellular crosstalk and spatial colocalization were also observed by scRNA-seq and ST analyses. Based on this crosstalk, a machine learning model, termed the naïve CD4 T cell and SPP1 macrophage prognostic score (TMPS), was established in the bulk-RNA seq datasets for prognostic prediction. The TMPS achieved C-index values of 0.785, 0.715, 0.692 and 0.857, respectively, across 4 independent cohorts. A low TMPS was associated with a significantly increased survival rates, improved response to immunotherapy and reduced infiltration of immunosuppressive cells, such as. regulatory T cells. Finally, 8 potential sensitive drugs and 6 potential targets were predicted for patients based on their TMPS.

CONCLUSION

The crosstalk between naïve CD4 T cells and SPP1 macrophages play a crucial role in the TME. TMPS can reflect this crosstalk and serve as a valuable tool for prognostic stratification and guiding clinical decision-making.