Exon-level expression analyses identify MYCN and NTRK1 as major determinants of alternative exon usage and robustly predict primary neuroblastoma outcome.

ABSTRACT:

Background

Using mRNA expression-derived signatures as predictors of individual patient outcome has been a goal ever since the introduction of microarrays. Here, we addressed whether analyses of tumour mRNA at the exon level can improve on the predictive power and classification accuracy of gene-based expression profiles using neuroblastoma as a model.

Methods

In a patient cohort comprising 113 primary neuroblastoma specimens expression profiling using exon-level analyses was performed to define predictive signatures using various machine-learning techniques. Alternative transcript use was calculated from relative exon expression. Validation of alternative transcripts was achieved using qPCR- and cell-based approaches.

Results

Both predictors derived from the gene or

SUBMITTER: Schramm A 

PROVIDER: S-EPMC3494449 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature