Integration of clinical characteristics and molecular signatures of the tumor microenvironment to predict the prognosis of neuroblastoma

This study aimed to analyze the clinical characteristics, cell types, and molecular characteristics of the tumor microenvironment to better predict the prognosis of neuroblastoma (NB).  The gene expression data and corresponding clinical information of 498 NB patients were obtained from the Gene Expression Omnibus (GEO: GSE62564) and ArrayExpress (accession: E-MTAB-8248). The relative cell abundances were estimated using single-sample gene set enrichment analysis (ssGSEA) with th e R gene set variation analysis (GSVA) package. We performed Cox regression analyses to identify marker genes indicating cell subsets and combined these with prognostically relevant clinical factors to develop a new prognostic model. Data from the E-MTAB-8248 cohort verified the predictive accuracy of the prognostic model. Single-cell RNA-seq data were analyzed by using the R Seurat package. Multivariate survival analysis for each gene, using clinical characteristics as cofactors, identified 34 prognostic genes that showed a significant correlation with both event-free survival (EFS) and over all survival (OS) (log-rank test,P value <  0.05). The pathway enrichment analysis revealed that these prognostic genes were highly enriched in the marker genes of NB cells with mesenchymal features and protein translation. Ultimately,USP39,RPL8,IL1RAPL1,MAST4,CSRP2,ATP5E, International Neuroblastoma Staging System (INSS) stage, age, andMYCN status were selected to build an optimized Cox model for NB ri...
Source: Journal of Molecular Medicine - Category: Molecular Biology Source Type: research