Identification of key genes related to cancer associated fibroblasts in neuroblastoma: A comprehensive bioinformatics approach.

Abstract

BackgroundNeuroblastoma (NB) is one of the most common and aggressive pediatric solid tumors, characterized by a highly complex pathogenesis. Within the tumor microenvironment (TME), cancer-associated fibroblasts (CAFs) constitute a major cell population and play a pivotal role in facilitating communication among various stromal cells. However, the specific functions and contributions of CAFs in NB remain incompletely understood.ObjectiveTo investigate the impact of CAFs-related genes on the prognosis of NB, we developed a risk model to facilitate the diagnosis and prognostication of patients.MethodsIn this study, a CAFs gene prognostic model for NB was established using single-cell analysis and genomic sequencing data. The effectiveness of this prognostic model was subsequently evaluated through the development of a nomogram, immune infiltration analysis, drug prediction, and gene set enrichment analysis. Ultimately, the expression levels of the identified key genes were experimentally validated in NB tissues.ResultsA novel prognostic model for CAFs related to NB prognosis was established through single-cell analysis and transcriptome dataset analysis. The prognosis of the high-risk group was worse than that of the low-risk group. The validity of the model was confirmed by nomogram, drug sensitivity analysis, and immune infiltration methods. Finally, the high expression of the key gene STEAP2 in NB tissues was verified by experiments.ConclusionsThe study introduces a new predictive model that uses CAF markers to forecast the prognosis of NB. STEAP2 plays a key role in identifying high-risk neuroblastoma and may become a potential therapeutic target for NB.