Dissecting the Dual Drug Candidates Against Glioblastoma and Oligodendroglioma Through Integrated Transcriptome Analysis and Virtual Screening.

Cancer is one of the prominent causes of death, and brain cancer accounts for about 2% of this figure, with glioma being the major type. This study aims to identify biomarker candidates for glioma subtypes, specifically glioblastoma (GBM) and oligodendroglioma (ODG), as well as to disclose repurposed drug candidates common to these brain tumors. Gene expression profiles were analyzed and integrated with data from proteomics interactions as well as miRNA regulation. 23 mutual core DEGs (differentially expressed genes) were identified. Correlation networks and protein interaction networks were constructed from these core DEGs. Hubs of the protein interaction networks (CALM1), miRNA - core DEG interaction network (SOX4, MTHFD2, and CALM1), and correlation networks such as ABCA2, TPPP, PPP1R16B, SPOCK3, and SPARC, as well as central miRNAs (hsa-miR-1-3p, hsa-miR-19b-3p, and hsa-miR-335-5p) were identified. Furthermore, candidate therapeutic agents were revealed. Docking-based virtual screening suggests that budesonide, sirolimus, cephaeline, etoposide, and staurosporine may target proteins upregulated in GBM and ODG, such as APOC, MTHFD2, and LPL, in addition to their actual targets. Particularly, sirolimus and protriptyline exhibited comparable binding affinities against MTHFD2 (-11.23 kcal/mol) and LPL (-7.45 kcal/mol), respectively, compared to their actual targets. The holistic network-based approach applied in this study may be advantageous in the illumination of these subtypes and may aid in the design of improved therapeutics in treatment of the studied gliomas.