[OMICS and biomarkers of glial tumors].

BACKGROUND

OMICS is the term used to designate new biological sciences investigating a large group of molecules in biological samples. For instance, genomics and transcriptomics study changes in genome and transcription expression respectively. Numerous others OMICS are emerging (e.g. epigen-, prote-, metabol-, lipid-, glucid-OMICS). Support from bioinformatics and biostatistics, together with new molecular biology technologies for screening these large molecular groups (i.e. high-throughput biological arrays), has led to the development of these scientific fields. They help to draw relevant molecular identity cards of tumors.

BACKGROUND

Glial tumors form a heterogeneous morphological and clinical tumor group including astrocytomas (from grade I to IV), oligodendrogliomas and oligoastrocytomas (grades II and III). OMICS has enabled a better understanding of clinical and biological behavior of these tumors identifying new molecular abnormalities and relevant biomarkers (i.e. diagnostic, prognostic, predictive of response to treatments and predisposing to gliomas). BRAF abnormalities are diagnostic markers in pilocytic astrocytomas and pleomorphic xanthoastrocytomas (duplication with rearrangement and V600E mutation, respectively). Translocation (1;19)(q10;p10) is associated with oligodendroglial phenotype and better prognosis in gliomas. MGMT promoter methylation is predictive of response to chemotherapy in grade IV astrocytomas (GBM). In GBM, high-throughput studies have discovered: genetic and genomic disruption of tyrosine kinase receptors, TP53 and RB signaling pathways in the vast majority of cases; several transcriptomic (e.g. neural, proneural, classic and mesenchymal), epigenomic (e.g. CpG Island Methylator phenotype versus non methylator phenotype) and proteomic (e.g. EGFR, PDGFR and NF1) patterns with biological and/or clinical impacts. Finally, OMICS have identified recurrent IDH1/IDH2 mutations with prognostic significance in glial tumors and five single nucleotide polymorphisms associated with susceptibility to gliomas (e.g. TERT, CCDC26, PHLDB1, RTEL1 and CDKN2A/CDKN2B). These latter data combined with already known inherited cancer syndromes (i.e. Turcot type 1, Cowden, melanoma-astrocytoma, Li-Fraumeni, tuberous sclerosis complex, type I and II neurofibromatosis) improve our knowledge of genetic predisposition to gliomas.

CONCLUSIONS

Data generated by OMICS are huge, multidimensional and promising. Bioinformatics and biostatistics will allow their integration (integromics) toward a precise dissection of their clinical of biological significance in neuro-oncology.

CONCLUSIONS

OMICS have a growing impact in neuro-oncology improving basic research in brain tumors and clinical management of patients through the discovery of biomarkers.