Dataset Information

Subtype-specific signaling pathways and genomic aberrations associated with prognosis of glioblastoma.

ABSTRACT:

Background

A high heterogeneity and activation of multiple oncogenic pathways have been implicated in failure of targeted therapies in glioblastoma (GBM).

Methods

Using The Cancer Genome Atlas data, we identified subtype-specific prognostic core genes by a combined approach of genome-wide Cox regression and Gene Set Enrichment Analysis. The results were validated with 8 combined public datasets containing 608 GBMs. We further examined prognostic chromosome aberrations and mutations.

Results

In classical and mesenchymal subtypes, 2 receptor tyrosine kinases (RTKs) (MET and IGF1R), and the genes in RTK downstream pathways such as phosphatidylinositol-3 kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR), and nuclear factor-kappaB (NF-kB), were commonly detected as prognostic core genes. Classical subtype-specific prognostic core genes included those in cell cycle, DNA repair, and the Janus kinase/signal transducers and activators of transcription (JAK-STAT) pathway. Immune-related genes were enriched in the prognostic genes showing negative promoter cytosine-phosphate-guanine (CpG) methylation/expression correlations. Mesenchymal subtype-specific prognostic genes were those related to mesenchymal cell movement, PI3K/Akt, mitogen-activated protein kinase (MAPK)/extracellular signal-regulated kinase (ERK), Wnt/?-catenin, and Wnt/Ca2+ pathways. In copy number alterations and mutations, 6p loss and TP53 mutation were associated with poor and good survival, respectively, in the classical subtype. In the mesenchymal subtype, patients with PIK3R1 or PCLO mutations showed poor prognosis. In the glioma CpG island methylator phenotype (G-CIMP) subtype, patients harboring 10q loss, 12p gain, or 14q loss exhibited poor survival. Furthermore, 10q loss was significantly associated with the recently recognized G-CIMP subclass showing relatively low CpG methylation and poor prognosis.

Conclusion

These subtype-specific alterations have promising potentials as new prognostic biomarkers and therapeutic targets combined with surrogate markers of GBM subtypes. However, considering the small number of events, the results of copy number alterations and mutations require further validations.

SUBMITTER: Park AK

PROVIDER: S-EPMC6303485 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Publications

Subtype-specific signaling pathways and genomic aberrations associated with prognosis of glioblastoma.

Park Ae Kyung AK Kim Pora P Ballester Leomar Y LY Esquenazi Yoshua Y Zhao Zhongming Z

Neuro-oncology 20190101 1

<h4>Background</h4>A high heterogeneity and activation of multiple oncogenic pathways have been implicated in failure of targeted therapies in glioblastoma (GBM).<h4>Methods</h4>Using The Cancer Genome Atlas data, we identified subtype-specific prognostic core genes by a combined approach of genome-wide Cox regression and Gene Set Enrichment Analysis. The results were validated with 8 combined public datasets containing 608 GBMs. We further examined prognostic chromosome aberrations and mutation ...[more]

PMID: 30053126

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Project description:Background: Among central nervous system tumors, glioblastoma (GBM) is considered to be the most destructive malignancy. Recurrence is one of the most fatal aspects of GBM. However, the driver molecules that trigger GBM recurrence are currently unclear. Methods: The mRNA expression data and clinical information of GBM and normal tissues were collected from the Chinese Glioma Genome Atlas The Cancer Genome Atlas (TCGA), and REpository for Molecular BRAin Neoplasia DaTa (REMBRANDT) cohorts. The DESeq2 R package was used to identify the differentially expressed genes between primary and recurrent GBM. ClueGO, Kyoto Encyclopedia of Genes and Genomes (KEGG), Biological Process in Gene ontology (GO-BP), and the Protein ANalysis THrough Evolutionary Relationships (PANTHER) pathway analyses were performed to explore the enriched signaling pathways in upregulated DEGs in recurrent GBM. A gene list that contained potential oncogenes that showed a significant negative correlation with patient survival from The Cancer Genome Atlas was used to further screen driver candidates for recurrent GBM. Univariate Cox proportional hazards regression analyses were used to investigate the risk score for the mRNA expression of the candidates. Single-cell RNA sequencing (scRNA-Seq) analyses were used to determine the cell type-specific distribution of Fc gamma receptor II b (FcγRIIb) in GBM. Immunohistochemistry (IHC) was used to confirm the FcγRIIb-positive cell populations in primary and paired recurrent GBM. Results: Through DEG analysis and overlap analysis, a total of 10 genes that are upregulated in recurrent GBM were screened. Using validation databases, FcγRIIb was identified from the 10 candidates that may serve as a driver for recurrent GBM. FCGR2B expression, not mutation, further showed a highly negative correlation with the poor prognosis of patients with recurrent GBM. Furthermore, scRNA-Seq analyses revealed that tumor-associated macrophage- and dendritic cell-specific FCGR2B was expressed. Moreover, FcγRIIb also showed a strong positive correlation coefficient with major immune-associated signaling pathways. In clinical specimens, FcγRIIb-positive cell populations were higher in recurrent GBM than in primary GBM. Conclusion: This study provides novel insights into the role of FcγRIIb in recurrent GBM and a promising strategy for treatment as an immune therapeutic target.

Dataset Information

Subtype-specific signaling pathways and genomic aberrations associated with prognosis of glioblastoma.

Background

Methods

Results

Conclusion

Publications

Subtype-specific signaling pathways and genomic aberrations associated with prognosis of glioblastoma.

Similar Datasets

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