Identification of FN1 and TIMP1 as macrophage-associated programmed cell death-related prognostic markers in glioblastoma via integrated bulk and single-cell RNA sequencing

Abstract

Glioblastoma (GBM) is the most common primary intracranial malignancy in adults, characterized by poor survival and high mortality. Emerging evidence suggests that macrophage-associated programmed cell death (MacPCD) plays a critical role in GBM pathogenesis. However, the underlying mechanisms remain poorly understood. This study aimed to identify MacPCD-related prognostic genes in GBM and explore their functional roles. Transcriptomic data from the GSE68848 dataset were integrated with Macrophage-associated programmed cell death-related genes (MacPCD-RGs) to identify differentially expressed genes (DEGs). Univariate Cox and LASSO regression analyses were performed using the TCGA-GBM training set to construct a prognostic risk model. Beyond prognostic stratification, we conducted a comprehensive multi-omic landscape analysis, including gene set enrichment analysis (GSEA), tumor microenvironment (TME) characterization, tumor mutational burden (TMB) assessment, immunotherapy response prediction, and drug sensitivity prediction. Finally, single-cell RNA sequencing (scRNA-seq) was employed to resolve microenvironmental heterogeneity, identify key cell types and elucidate intercellular communication and developmental trajectories. Analysis of GSE68848 identified 902 DEGs, of which five intersected with MacPCD-RGs. FN1 and TIMP1 were subsequently identified as core prognostic markers. The risk model demonstrated superior predictive performance across the CGGA-325 and GSE83300 validation cohorts. Functional analysis linked the risk score to specific signaling pathways, PTEN mutations, infiltration of immune cell subsets (e.g. NKT cells) and sensitivity to Trametinib. Tumor-associated macrophages (TAMs) were identified as the key cell type, exhibiting intense interaction with pericytes and enrichment in fructose/mannose metabolism. Furthermore, pseudotime analysis revealed that FN1 and TIMP1 expression peaked during the initial stages of TAM differentiation. This study identified FN1 and TIMP1 as pivotal MacPCD-related prognostic genes in GBM. The risk model based on these markers exhibits moderate predictive performance, offering a reliable tool for clinical prognosis and paving the way for personalized immunotherapy strategies.