Identification of EMT-associated prognostic features among grade II/III gliomas.
Sci Rep
; 14(1): 2822, 2024 02 03.
Article
in En
| MEDLINE
| ID: mdl-38307919
ABSTRACT
Grade II/III gliomas have a highly heterogeneous clinical course. Identifying prognostic biomarkers in grade II/III gliomas is essential to guide clinical management. We explored epithelial-mesenchymal transition (EMT)-related genes to uncover prognostic features in grade II/III gliomas. Consensus cluster analysis of 200 EMT-related genes classified 512 grade II/III glioma samples into two molecular subtypes, C1 and C2. The C1 subtype had significantly worse overall survival compared to the C2 subtype. Pathway analysis revealed C1 tumors were highly associated with tumor progression pathways and demonstrated higher immune cell infiltration scores. Differential expression analysis identified four genes (ACTN1, AQP1, LAMC3, NRM) that discriminated the two subtypes. Validation in external datasets confirmed that high expression of this four-gene signature predicted poor prognosis in grade II/III gliomas. Cellular experiments showed ACTN1, AQP1 and NRM promoted glioma cell proliferation, migration and invasion. We examined correlations of the signature genes with T cell exhaustion markers and found ACTN1 expression had the strongest association. Immunohistochemistry analysis further demonstrated that ACTN1 protein expression in grade II/III gliomas was negatively correlated with patient overall survival. In summary, our study identified a concise four-gene signature that robustly predicts grade II/III gliomas prognosis across multiple datasets. The signature provides clinical relevance in distinguishing more aggressive grade II/III glioma tumors. Targeting the ACTN1, AQP1 and NRM genes may offer new therapeutic opportunities to improve grade II/III gliomas patient outcomes.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Brain Neoplasms
/
Glioma
Type of study:
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
Limits:
Humans
Language:
En
Journal:
Sci Rep
Year:
2024
Document type:
Article
Affiliation country:
China