Integrated multi-omics analysis of single-cell and spatial transcriptomics reveals distinct hpv-associated immune microenvironment features and prognostic signatures in cervical cancer

Background Cervical cancer (CC) is a highly heterogeneous malignancy primarily driven by persistent infection with high-risk human papillomavirus (HPV). However, comprehensive analyses of heterogeneity in the immune microenvironment, particularly its spatial heterogeneity, between HPV-positive and HPV-negative CC remain limited, despite their critical clinical significance. Methods We performed single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) sequencing on collected cervical cancer samples, integrating scRNA-seq, ST, and bulk RNA-seq to analyze distinct cell subtypes and characterize their spatial distribution. Multiplex immunofluorescence analysis was further utilized to validate HPV status-specific expression patterns. Cox regression and LASSO regression analyses were used to identify the prognostic signature on the TCGA dataset. Results Through integrative analysis, we found that HPV-positive samples demonstrated elevated proportions of CD4 + T cells and cDC2s, whereas HPV-negative samples exhibited increased CD8 + T cell infiltration. In HPV-positive CC, epithelial cells acted as primary regulators of cDC2s via the ANXA1 - FPR1/3 pathway, with cDC2s subsequently modulating CD4 + T cells and interferon-related CD8 + T cell subtypes. In contrast, HPV-negative CC featured epithelial cells predominantly influencing monocytes and macrophages, which then interacted with CD8 + T cells. Notably, the MDK - LRP1 ligand-receptor interaction emerged as a potential key mechanism for recruiting immunosuppressive cells into CC tumors, fostering an immunosuppressive microenvironment. Further, we constructed a risk score model based on an epithelial cell-related signature (ERS), which was significantly associated with patient survival. Noteworthy variations were observed in immune cell infiltration and immune microenvironment among distinct risk groups. Conclusion Based on integrated multi-omics data, we precisely delineated the spatial transcriptional features of the tumor microenvironment in CC with different HPV statuses, including identifying distinct CD8 + T cell states and cell-cell communication. In addition, we developed an ERS closely associated with the immune environment and prognosis of CC. These results increase our understanding of the molecular mechanisms of cervical cancer under different HPV statuses and provide assistance for the precise treatment of cervical cancer.