Faculty, Staff and Student Publications

Language

English

Publication Date

6-1-2024

Journal

Computers in Biology and Medicine

DOI

10.1016/j.compbiomed.2024.108304

PMID

38663352

Abstract

Background: Brain tumours are known to have a high mortality and morbidity rate due to their localised and frequent invasive growth. The concept that glioma resistance could originate from the dissimilarity in the vulnerability of clonogenic glial stem cells to chemotherapeutic drugs and radiation has driven the scientific community to reexamine the comprehension of glioma growth and strategies that target these cells or modify their stemness.

Methods: Based on the enrichment scores of 12 stemness signatures, we identified glioma subtypes in both tumour bulks and single cells by clustering analysis. Furthermore, we comprehensively compared molecular and clinical features among the glioma subtypes.

Results: Consistently, in seven different datasets, hierarchical clustering uncovered three subtypes of glioma, termed Stem-H, Stem-M, and Stem-L, with high, medium, and low stemness signatures, respectively. Stem-H and Stem-L exhibited the most unfavorable and favourable overall and disease-free survival, respectively. Stem-H showed the highest enrichment scores of the EMT, invasion, proliferation, differentiation, and metastasis processes signatures, while Stem-L displayed the lowest. Stem-H harboured a greater proportion of late-stage tumours compared to Stem-L. Moreover, Stem-H manifested higher tumour mutation burden, DNA damage repair and cell cycle activity, intratumour heterogeneity, and a more frequent incidence of TP53 and EGFR mutations than Stem-L. In contrast, Stem-L had higher O6-Methylguanine-DNA Methyltransferase (MGMT) methylation levels.

Conclusion: The classification of glioma based on stemness may offer new insights into the biology of the tumour, as well as more accurate clinical management of the disease.

Keywords

Humans, Glioma, Brain Neoplasms, Transcriptome, Neoplastic Stem Cells, Single-Cell Analysis, Clustering analysis, Glioma, Molecular features, Stemness, Stemness subtypes

Published Open-Access

yes

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