In silico analysis of long non-coding RNAs in medulloblastoma and its subgroups

NEUROBIOLOGY OF DISEASE

卷:141

Article

Joshi, Piyush^1,2  Jallo, George³  Perera, Ranjan J.^1,2,4 

[1] Johns Hopkins All Childrens Hosp, Canc & Blood Disorder Inst, 600 5th St South, St Petersburg, FL 33701 USA

[2] Johns Hopkins Univ, Sidney Kimmel Comprehens Canc Ctr, Sch Med, Dept Oncol, 1650 Orleans St, Baltimore, MD 21231 USA

[3] Johns Hopkins All Childrens Hosp, Inst Brain Protect Sci, 600 5th St South, St Petersburg, FL 33701 USA

[4] Sanford Burnham Prebys Med Discovery Inst, 10901 N Torrey Pines Rd, La Jolla, CA 92037 USA

关键词: Long non-coding RNAs;    Medulloblastoma;    RNA-seq analysis;    Diagnostic model;    Prognostic model;   

DOI  :  10.1016/j.nbd.2020.104873

来源: Elsevier

【 摘 要 】

Medulloblastoma is the most common malignant pediatric brain tumor with high fatality rate. Recent large-scale studies utilizing genome-wide technologies have sub-grouped medulloblastomas into four major subgroups: wingless (WNT), sonic hedgehog (SHH), group 3, and group 4. However, there has yet to be a global analysis of long non-coding RNAs, a crucial part of the regulatory transcriptome, in medulloblastoma. Here, we performed bioinformatic analysis of RNA-seq data from 175 medulloblastoma patients. Differential lncRNA expression subgrouped medulloblastomas into the four main molecular subgroups. Some of these lncRNAs were subgroup-specific, with a random forest-based machine-learning algorithm identifying an 11-lncRNA diagnostic signature. We also validated the diagnostic signature in patient derived xenograft (PDX) models. We further identified a 17-lncRNA prognostic model using LASSO based penalized Cox' PH model (Score HR = 13.6301, 95% CI = 8.857-20.98, logrank p-value <= 2e-16). Our analysis represents the first global lncRNA analysis in medulloblastoma. Our results identify putative candidate lncRNAs that could be evaluated for their functional role in medulloblastoma genesis and progression or as diagnostic and prognostic biomarkers.