High-risk, Expression-Based Prognostic Long Noncoding RNA Signature in Neuroblastoma

Area of Science:

• Oncology
• Genomics
• Molecular Biology

Background:

• Neuroblastoma (NB) risk stratification relies on clinical factors, but patient responses vary.
• MYCN amplification is a key NB driver associated with poor outcomes.
• Long noncoding RNAs (lncRNAs) are implicated in cancer, but their prognostic role in NB is unclear, especially with MYCN amplification influencing expression.

Purpose of the Study:

• To develop and validate a novel prognostic signature for neuroblastoma (NB) based on long noncoding RNA (lncRNA) expression.
• To assess the signature's ability to predict event-free survival (EFS) independently of established clinical risk factors.
• To improve precise clinical stratification for NB patients.

Main Methods:

• RNA-sequencing data from a discovery cohort (n=493) and three independent cohorts were analyzed for lncRNA expression.
• A prognostic signature was constructed using univariate Cox regression and a risk score method.
• Patient risk groups were stratified using a novel threshold criterion, and survival outcomes were analyzed via Kaplan-Meier curves and multivariable Cox regression.

Main Results:

• A 16-lncRNA signature was identified, showing significant association with poor event-free survival (EFS) in the discovery cohort (P < 1E-16).
• The lncRNA signature independently predicted EFS (HR=3.21, P=5.95E-07) and was validated across independent cohorts.
• The signature demonstrated high accuracy for EFS prediction (AUC=0.788).

Conclusions:

• The first RNA-seq-based 16-lncRNA prognostic signature for neuroblastoma (NB) has been developed.
• This signature may enhance precise clinical stratification and improve event-free survival (EFS) prediction in NB patients.
• The findings highlight the potential of lncRNAs as biomarkers for NB prognosis.