Integration of genome-wide profiles of DNA copy number alterations (CNAs) and gene expression variations (GEVs) could provide combined power to the identification of driver genes and gene networks in tumors. Here we merge matched genome and transcriptome microarray analyses from neuroblastoma samples to derive correlation patterns of CNAs and GEVs, irrespective of their genomic location. Neuroblastoma correlation patterns are strongly asymmetrical, being on average 10 CNAs linked to 1 GEV, and show the widespread prevalence of long range covariance. Functional enrichment and network analysis of the genes covarying with CNAs consistently point to a major cell function, the regulation of mitotic spindle assembly. Moreover, elevated expression of 14 key genes promoting this function is strongly associated to high-risk neuroblastomas with 1p loss and MYCN amplification in a set of 410 tumor samples (P <0.00001). Independent CNA/GEV profiling on neuroblastoma cell lines shows that increased levels of expression of these genes are linked to 1p loss. By this approach, we reveal a convergence of clustered neuroblastoma CNAs toward increased expression of a group of prognostic and functionally cooperating genes. We therefore propose gain of function of the spindle assembly machinery as a lesion potentially offering new targets for therapy of high-risk neuroblastoma.
ASJC Scopus subject areas
- Cancer Research