Dataset Information

SuperQuant-assisted comparative proteome analysis of glioblastoma subpopulations allows for identification of potential novel therapeutic targets and cell markers.

ABSTRACT: Glioblastoma (GBM) is a highly aggressive brain cancer with poor prognosis and low survival rate. Invasive cancer stem-like cells (CSCs) are responsible for tumor recurrence because they escape current treatments. Our main goal was to study the proteome of three GBM subpopulations to identify key molecules behind GBM cell phenotypes and potential cell markers for migrating cells. We used SuperQuant-an enhanced quantitative proteome approach-to increase proteome coverage. We found 148 proteins differentially regulated in migrating CSCs and 199 proteins differentially regulated in differentiated cells. We used Ingenuity Pathway Analysis (IPA) to predict upstream regulators, downstream effects and canonical pathways associated with regulated proteins. IPA analysis predicted activation of integrin-linked kinase (ILK) signaling, actin cytoskeleton signaling, and lysine demethylase 5B (KDM5B) in CSC migration. Moreover, our data suggested that microRNA-122 (miR-122) is a potential upstream regulator of GBM phenotypes as miR-122 activation was predicted for differentiated cells while its inhibition was predicted for migrating CSCs. Finally, we validated transferrin (TF) and procollagen-lysine 2-oxoglutarate 5-dioxygenase 2 (PLOD2) as potential markers for migrating cells.

SUBMITTER: Verano-Braga T

PROVIDER: S-EPMC5823648 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

SuperQuant-assisted comparative proteome analysis of glioblastoma subpopulations allows for identification of potential novel therapeutic targets and cell markers.

Verano-Braga Thiago T Gorshkov Vladimir V Munthe Sune S Sørensen Mia D MD Kristensen Bjarne W BW Kjeldsen Frank F

Oncotarget 20180125 10

Glioblastoma (GBM) is a highly aggressive brain cancer with poor prognosis and low survival rate. Invasive cancer stem-like cells (CSCs) are responsible for tumor recurrence because they escape current treatments. Our main goal was to study the proteome of three GBM subpopulations to identify key molecules behind GBM cell phenotypes and potential cell markers for migrating cells. We used SuperQuant-an enhanced quantitative proteome approach-to increase proteome coverage. We found 148 proteins di ...[more]

PMID: 29507698

Similar Datasets

Project description:BackgroundBurkholderia cenocepacia is an endemic soil dweller and emerging opportunistic pathogen in patients with cystic fibrosis (CF). The identification of virulence factors and potential therapeutic targets has been hampered by the genomic diversity within the species as many factors are not shared among the pathogenic members of the species.Methodology/principal findingsIn this study, global identification of putative virulence factors was performed by analyzing the transcriptome of two related strains of B. cenocepacia (one clinical, one environmental) under conditions mimicking cystic fibrosis sputum versus soil. Soil is a natural reservoir for this species; hence, genes induced under CF conditions relative to soil may represent adaptations that have occurred in clinical strains. Under CF conditions, several genes encoding proteins thought to be involved in virulence were induced and many new ones were identified. Our analysis, in combination with previous studies, reveals 458 strain-specific genes, 126 clinical-isolate-specific, and at least four species-specific genes that are induced under CF conditions. The chromosomal distribution of the induced genes was disproportionate to the size of the chromosome as genes expressed under soil conditions by both strains were more frequent on the second chromosome and those differentially regulated between strains were more frequent on the third chromosome. Conservation of these induced genes was established using the 11 available Bcc genome sequences to indicate whether potential therapeutic targets would be species-wide.Conclusions/significanceComparative transcriptomics is a useful way to identify new potential virulence factors and therapeutic targets for pathogenic bacteria. We identified eight genes induced under CF conditions that were also conserved in the Bcc and may constitute particularly attractive therapeutic targets due to their signal sequence, predicted cellular location, and homology to known therapeutic targets.

Dataset Information

SuperQuant-assisted comparative proteome analysis of glioblastoma subpopulations allows for identification of potential novel therapeutic targets and cell markers.

Publications

SuperQuant-assisted comparative proteome analysis of glioblastoma subpopulations allows for identification of potential novel therapeutic targets and cell markers.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets