Work

Construction and Validation of an Integrated Bulk and Single‐Cell Transcriptome–Based Prognostic Model for Pediatric Glioma

Year: 2026

Type: article

Abstract: Pediatric glioma displays distinct molecular features and clinical behavior compared with adult glioma, highlighting the need for pediatric‐specific prognostic biomarkers and therapeutic strategies. This study aimed to develop and validate a robust prognostic model for pediatric glioma through integration of bulk and single‐cell transcriptomic data and to characterize its biological and clinical relevance. Gene expression profiles and clinical information were collected from the TCGA, CGGA, and GSE84465 cohorts. Single‐cell RNA‐sequencing data were analyzed using dimensionality reduction, clustering, and cell–cell communication approaches to delineate tumor heterogeneity and the immune microenvironment. Cells were further stratified according to mitochondrial gene‐set scores to explore functional differences. Differential genes were subjected to GO and KEGG enrichment analyses, and key prognostic genes were selected using LASSO regression to construct a risk model, which was subsequently validated in independent datasets. Immune infiltration, mutation patterns, and drug sensitivity were evaluated using multiple computational algorithms. The model effectively stratified patients into high‐ and low‐risk groups with significantly different survival outcomes. The risk score correlated strongly with immune cell infiltration, somatic mutation landscapes, and predicted therapeutic responses, indicating its potential value for guiding personalized treatment. In summary, this integrative transcriptomic analysis reveals the molecular heterogeneity of pediatric glioma and establishes a reliable prognostic signature that may facilitate risk stratification and precision therapy.

Source: International Journal of Clinical Practice

DOI: 10.1155/ijcp/6882378

Authors: Chan Zhao, Panjian Lai, Xin Liu, Yuan Gao

Institutions: Jinhua Central Hospital, Second Hospital of Hebei Medical University

Language: English

Topic: Glioma Diagnosis and Treatment

Subfield: Genetics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,350