Gene/Protein
Disease
Symptom
Drug
Enzyme
Compound
Pivot Concepts:
Gene/Protein
Disease
Symptom
Drug
Enzyme
Compound
Target Concepts:
Gene/Protein
Disease
Symptom
Drug
Enzyme
Compound
Query: UMLS:C0017638 (
glioma
)
30,880
document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)
Glioma
, one of the most common cancers in human, is classified to different grades according to the degrees of malignancy. Glioblastoma (GBM) is known to be the most malignant (Grade IV) whereas low-grade astrocytoma (LGA, Grade II) is relatively benign. The mechanism underlying the pathogenesis and progression of
glioma
malignancy remains unclear. Here we report a quantitative proteomic study to elucidate the differences between GBM and LGA using liquid chromatography and tandem mass spectrometry followed by label-free quantification. A total of 136 proteins were differentially expressed in GBM for at least five folds in comparison with LGA. Ontological analysis revealed a close correlation between GBM-associated proteins and RNA processing. Interaction network analysis indicated that the GBM-associated proteins in the RNA processing were linked to crucial signaling transduction modulators including epidermal growth factor receptor (EGFR), signal transducer and activator of transcription 1 (STAT1), and mitogen-activated protein kinase 1 (MAPK1), which were further connected to the proteins important for neuronal structural integrity, development and functions. Upregulation of 40S ribosomal protein S5 (RPS5), Ferritin Heavy chain (FTH1) and STAT1, and downregulation of
tenascin R
(
TNR
) were validated as representatives by immune assays. In summary, we revealed a panel of GBM-associated proteins and the important modulators centered at the RNA-processing network in
glioma
malignancy that may become novel biomarkers and help elucidate the underlying mechanism.
...
PMID:Label-free quantitative proteomics unravels the importance of RNA processing in glioma malignancy. 2834 Nov 97
Objective
: This study was aimed to identify prognostic factors in
glioma
by analysis of the gene expression and DNA methylation data.
Methods
: The RNAseq and DNA methylation data associated with
glioma
were downloaded from GEO and TCGA databases to analyze the differentially expressed genes (DEGs) and methylated genes between tumor and normal tissues. Function and pathway analyses, co-expression network and survival analysis were performed based on these DEGs. The intersection genes of DEGs and differentially methylated genes were obtained followed by function analysis.
Results
: Total 2190 DEGs were identified between tumor and normal tissues, which were significantly enriched in neuron differentiation associated functions, as well as ribosome pathway. There were 6186 methylation sites (2834 up-regulated and 3352 down-regulated) with significant differences in tumor vs. normal. In the constructed co-expression network, DPP6, MAPK10 and RPL3 were hub genes. Survival analysis of 20 DEGs obtained 18 prognostic genes, among which 9 were differentially methylated, such as LHFPL tetraspan subfamily member 3 (LHFPL3), cadherin 20 (CDH20), complexin 2 (CPLX2), and
tenascin R
(
TNR
). The intersection of DEGs and differentially methylated genes (632 genes) were significantly enriched in functions of neuron differentiation.
Conclusion
: DPP6, MAPK10 and RPL3 may play important roles in tumorigenesis of
glioma
. Additionally, methylation of LHFPL3, CDH20, CPLX2, and
TNR
may serve as prognostic factors of
glioma
.
...
PMID:Prognostic factor identification by analysis of the gene expression and DNA methylation data in glioma. 3298 60