A prognostic model based on Scissor+ cancer-associated macrophages identified from bulk and single cell RNA sequencing data in ovarian cancer.

BACKGROUND

Ovarian cancer (OC) represents the most lethal malignancy in gynecological oncology. This study analyzes functional subsets of tumor-associated macrophages (TAMs) using a single-cell sequencing database to construct a precise prognostic model and investigate its associated immune response mechanisms.

METHODS

We characterized differences in cell types and TAM subtypes between OC and normal ovarian tissue using the GSE184880 single-cell RNA sequencing (scRNA-seq) dataset. By integrating scissor analysis with The Cancer Genome Atlas (TCGA) survival data, we identified prognostic Scissor+ macrophage signatures and extracted key differentially expressed genes (DEGs). Core genes selected via least absolute shrinkage and selection operator (LASSO)-Cox regression and Random Forest survival modeling were used to build a prognostic risk model, which was validated in TCGA and external cohorts (GSE26712, GSE63885, and GSE140082). Further analyses examined the single-cell expression patterns, immune microenvironment associations, and microRNA (miRNA)/transcription factor (TF) co-expression networks of these core genes.

RESULTS

The macrophage proportion was increased in OC, with enriched M2-type TAMs and reduced M1-type TAMs; 94 Scissor+ macrophage DEGs were identified, including five core genes: IL1B, pro-inflammatory cytokine; ISG20, antiviral immune ribonuclease; ABCC3, ATP-binding cassette transporter; ZFP36, mRNA stability RNA-binding protein; IL2RG, immune cell cytokine receptor. The constructed model showed significantly reduced overall survival (OS) in the high-risk group across external cohorts (P<0.05). The high-risk group exhibited enrichment of immunosuppressive cells such as M2-type TAMs and regulatory T cells (Tregs), while the low-risk group showed enrichment of immune-promoting cells including CD4+ memory T cells. The core genes participated in immune regulation via miRNA/TF networks.

CONCLUSIONS

This study establishes the first Scissor+ macrophage-based prognostic model for OC, demonstrating consistent predictive performance. It reveals how TAM subtype imbalance contributes to immune microenvironment remodeling, offering new insights for prognostic stratification and immunotherapeutic targeting in OC.