Background: Glioblastoma (GBM) is an intracranial brain tumor characterized by a high final lethality rate and recurrence rate, and limited available therapies. With the development of high-throughput sequencing technology, the genomic and transcriptomic features of GBM have been fully characterized. Therefore, our study aimed to identify its underlying genetic mechanisms, thus facilitating the development of novel therapies for GBM. Methods: Based on the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases, differential expression of RNAs in GBM and control group was analyzed. After constructing the long noncoding RNA (lncRNA)-miRNA-mRNA regulatory network of GBM, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGGs) were performed to analyze related key nodes and the lncRNAs interacting with them. Further univariate Cox regression was conducted to explore independent factors, and then multivariate Cox regression was performed to construct risk prediction models. Results: We first constructed the lncRNA-miRNA-mRNA regulatory network of GBM and two effective prediction models that included 2 mRNAs [transcription factor 12 (TCF12) and discoidin, CUB and LCCL domain containing 2 (DCBLD2)] and 5 lncRNAs (C10orf25, LINC00343, HOXA transcript antisense RNA, myeloid-specific 1 (HOTAIRM1), FGF12 antisense RNA 2 (FGF12-AS2) and H19). Additionally, we identified several key molecules [TCF12, integrin beta 3 (ITGB3), high mobility group AT-hook 2 (HMGA2), C10orf25 and LINC00336] closely associated with GBM prognosis. C10orf25/miR-218/DCBLD2 may be an important regulatory pathway in GBM. Conclusions: Key molecules (TCF12, ITGB3, HMGA2, C10orf25, LINC00336 and H19) that are independent prognostic factors may be possible biomarkers to further optimize GBM prognosis. Two effective prognostic risk models that include 2 mRNAs (TCF12 and DCBLD2) and 5 lncRNAs (C10orf25, LINC00343, HOTAIRM1, FGF12-AS2 and H19) were constructed. C10orf25/miR-218/DCBLD2 may be an important regulatory pathway associated with the pathogenesis of GBM. Our findings contribute to further understanding the pathogenesis of GBM and finding possible candidate genes for prognostic and therapeutic usage with GBM.