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Simple Summary Most glioblastoma patients succumb to the disease within 12 to 18 months, and only 9% are alive 2 years after diagnosis. Even with extensive research, the life expectancy of glioblastoma patients has not changed in decades. We aimed to identify differences in the transcriptomic profiles of glioblastoma patients with long and short survival. With large-scale transcriptomic analysis, we examined information from publicly available datasets (TCGA and CGGA) in combination with FFPE patient tissue samples. We identified one gene, the long noncoding RNA CRNDE, whose overexpression is directly correlated with poor patient survival. Therefore, we suggest its further confirmation as a negative prognostic glioblastoma biomarker. Glioblastoma management still lacks suitable diagnostic, predictive, and prognostic biomarkers for early disease diagnosis, and treatment follow-up. We believe our findings can serve as the basis for identification of new and potential suitable disease biomarkers by looking beyond the classical molecules (DNA, RNA, and proteins) into the noncoding genome. Abstract Glioblastoma is the most common and malignant brain malignancy worldwide, with a 10-year survival of only 0.7%. Aggressive multimodal treatment is not enough to increase life expectancy and provide good quality of life for glioblastoma patients. In addition, despite decades of research, there are no established biomarkers for early disease diagnosis and monitoring of patient response to treatment. High throughput sequencing technologies allow for the identification of unique molecules from large clinically annotated datasets. Thus, the aim of our study was to identify significant molecular changes between short- and long-term glioblastoma survivors by transcriptome RNA sequencing profiling, followed by differential pathway-activation-level analysis. We used data from the publicly available repositories The Cancer Genome Atlas (TCGA; number of annotated cases = 135) and Chinese Glioma Genome Atlas (CGGA; number of annotated cases = 218), and experimental clinically annotated glioblastoma tissue samples from the Institute of Pathology, Faculty of Medicine in Ljubljana corresponding to 2–58 months overall survival (n = 16). We found one differential gene for long noncoding RNA CRNDE whose overexpression showed correlation to poor patient OS. Moreover, we identified overlapping sets of congruently regulated differential genes involved in cell growth, division, and migration, structure and dynamics of extracellular matrix, DNA methylation, and regulation through noncoding RNAs. Gene ontology analysis can provide additional information about the function of protein- and nonprotein-coding genes of interest and the processes in which they are involved. In the future, this can shape the design of more targeted therapeutic approaches.

Glioblastoma is the most common and malignant brain malignancy worldwide, with a 10-year survival of only 0.7%. Aggressive multimodal treatment is not enough to increase life expectancy and provide good quality of life for glioblastoma patients. In addition, despite decades of research, there are no established biomarkers for early disease diagnosis and monitoring of patient response to treatment. High throughput sequencing technologies allow for the identification of unique molecules from large clinically annotated datasets. Thus, the aim of our study was to identify significant molecular changes between short- and long-term glioblastoma survivors by transcriptome RNA sequencing profiling, followed by differential pathway-activation-level analysis. We used data from the publicly available repositories The Cancer Genome Atlas (TCGA, number of annotated cases = 135) and Chinese Glioma Genome Atlas (CGGA, number of annotated cases = 218), and experimental clinically annotated glioblastoma tissue samples from the Institute of Pathology, Faculty of Medicine in Ljubljana corresponding to 2–58 months overall survival (n = 16). We found one differential gene for long noncoding RNA CRNDE whose overexpression showed correlation to poor patient OS. Moreover, we identified overlapping sets of congruently regulated differential genes involved in cell growth, division, and migration, structure and dynamics of extracellular matrix, DNA methylation, and regulation through noncoding RNAs. Gene ontology analysis can provide additional information about the function of protein- and nonprotein-coding genes of interest and the processes in which they are involved. In the future, this can shape the design of more targeted therapeutic approaches.

World Health Organization grade IV diffuse gliomas, known as glioblastomas, are the most common malignant brain tumors, and they show poor prognosis. Multimodal treatment of surgery followed by radiation and chemotherapy is not sufficient to increase patient survival, which is 12 to 18 months after diagnosis. Despite extensive research, patient life expectancy has not significantly improved over the last decade. Previously, we identified FREM2 and SPRY1 as genes with differential expression in glioblastoma cell lines compared to nonmalignant astrocytes. In addition, the FREM2 and SPRY1 proteins show specific localization on the surface of glioblastoma cells. In this study, we explored the roles of the FREM2 and SPRY1 genes and their proteins in glioblastoma pathology using human tissue samples. We used proteomic, transcriptomic, and bioinformatics approaches to detect changes at different molecular levels. We demonstrate increased FREM2 protein expression levels in glioblastomas compared to reference samples. At the transcriptomic level, both FREM2 and SPRY1 show increased expression in tissue samples of different glioma grades compared to nonmalignant brain tissue. To broaden our experimental findings, we analyzed The Cancer Genome Atlas glioblastoma patient datasets. We discovered higher FREM2 and SPRY1 gene expression levels in glioblastomas compared to lower grade gliomas and reference samples. In addition, we observed that low FREM2 expression was associated with progression of IDH-mutant low-grade glioma patients. Multivariate analysis showed positive association between FREM2 and favorable prognosis of IDH-wild type glioblastoma. We conclude that FREM2 has an important role in malignant progression of glioblastoma, and we suggest deeper analysis to determine its involvement in glioblastoma pathology.