Oligodendrogliomas are primary human brain tumors with a characteristic 1p/19q co-deletion of important prognostic relevance, but little is known about the pathology of this chromosomal mutation. We developed a network-based approach to identify novel cancer gene candidates in the region of the 1p/19q co-deletion. Gene regulatory networks were learned from gene expression and copy number data of 178 oligodendrogliomas and further used to quantify putative impacts of differentially expressed genes of the 1p/19q region on cancer-relevant pathways. We predicted 8 genes with strong impact on signaling pathways and 14 genes with strong impact on metabolic pathways widespread across the region of the 1p/19 co-deletion. Many of these candidates (e.g. ELTD1, SDHB, SEPW1, SLC17A7, SZRD1, THAP3, ZBTB17) are likely to push, whereas others (e.g. CAP1, HBXIP, KLK6, PARK7, PTAFR) might counteract oligodendroglioma development. For example, ELTD1, a functionally validated glioblastoma oncogene located on 1p, was overexpressed. Further, the known glioblastoma tumor suppressor SLC17A7 located on 19q was underexpressed. Moreover, known epigenetic alterations triggered by mutated SDHB in paragangliomas suggest that underexpressed SDHB in oligodendrogliomas may support and possibly enhance the epigenetic reprogramming induced by the IDH-mutation. We further analyzed rarely observed deletions and duplications of chromosomal arms within oligodendroglioma subcohorts identifying putative oncogenes and tumor suppressors that possibly influence the development of oligodendroglioma subgroups. Our in-depth computational study contributes to a better understanding of the pathology of the 1p/19q co-deletion and other chromosomal arm mutations. This might open opportunities for functional validations and new therapeutic strategies.
Keywords: 1p/19q co-deletion; Bioinformatics; Cancer genomics; Computational systems biology; Network biology; Network inference; Network propagation; Oligodendrogliomas.