Cancer Cell Metabolism Gene Database

  Cancer Cell Metabolism Gene DB

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Bioinformatics and Systems Medicine Laboratory Bioinformatics and Systems Medicine Laboratory

Gene Summary

Phenotypic Information (metabolism pathway, cancer, disease, phenome)

Mutations: SVs, CNVs, SNVs

Gene expression: GE, Protein, DEGE, CNV vs GE

Gene-Gene Network Information: Co-Expression Network, Interacting Genes & KEGG

Pharmacological Information: Drug-Gene Network

Cross referenced IDs

Gene Summary for GLDC
Basic gene info.Gene symbolGLDC
Gene nameglycine dehydrogenase (decarboxylating)
SynonymsGCE|GCSP|HYGN1
CytomapUCSC genome browser: 9p22
Genomic locationchr9 :6532463-6645692
Type of geneprotein-coding
RefGenesNM_000170.2,
Ensembl idENSG00000178445
Descriptionglycine cleavage system protein Pglycine decarboxylase P-proteinglycine dehydrogenase (aminomethyl-transferring)glycine dehydrogenase (decarboxylating), mitochondrialglycine dehydrogenase [decarboxylating], mitochondrial
Modification date20141219
dbXrefs MIM : 238300
HGNC : HGNC
Ensembl : ENSG00000178445
HPRD : 01996
Vega : OTTHUMG00000019524
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_GLDC
BioGPS: 2731
Gene Expression Atlas: ENSG00000178445
The Human Protein Atlas: ENSG00000178445
PathwayNCI Pathway Interaction Database: GLDC
KEGG: GLDC
REACTOME: GLDC
ConsensusPathDB
Pathway Commons: GLDC
MetabolismMetaCyc: GLDC
HUMANCyc: GLDC
RegulationEnsembl's Regulation: ENSG00000178445
miRBase: chr9 :6,532,463-6,645,692
TargetScan: NM_000170
cisRED: ENSG00000178445
ContextiHOP: GLDC
cancer metabolism search in PubMed: GLDC
UCL Cancer Institute: GLDC
Assigned class in ccmGDBC

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Phenotypic Information for GLDC(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: GLDC
Familial Cancer Database: GLDC
* This gene is included in those cancer gene databases.

.

Oncogene 1

Tumor Suppressor gene 2

Cancer Gene Census 3

CancerGenes 4

Network of Cancer Gene 5

Significant driver gene in

Therapeutic Vulnerabilities in Cancer1

cf) number; DB name
1 Oncogene; http://nar.oxfordjournals.org/content/35/suppl_1/D721.long,
2 Tumor Suppressor gene; https://bioinfo.uth.edu/TSGene/,
3 Cancer Gene Census; http://www.nature.com/nrc/journal/v4/n3/abs/nrc1299.html,
4 CancerGenes; http://nar.oxfordjournals.org/content/35/suppl_1/D721.long,
5 Network of Cancer Gene; http://ncg.kcl.ac.uk/index.php,
1Therapeutic Vulnerabilities in Cancer; http://cbio.mskcc.org/cancergenomics/statius/

check002.gifMetabolic Pathway Description
KEGG_GLYCINE_SERINE_AND_THREONINE_METABOLISM

check002.gifOthers
OMIM
Orphanet
DiseaseKEGG Disease: GLDC
MedGen: GLDC (Human Medical Genetics with Condition)
ClinVar: GLDC
PhenotypeMGI: GLDC (International Mouse Phenotyping Consortium)
PhenomicDB: GLDC

Mutations for GLDC
* Under tables are showing count per each tissue to give us broad intuition about tissue specific mutation patterns.You can go to the detailed page for each mutation database's web site.

check002.gifStructural Variants in COSMIC: go to COSMIC mutation histogram

- Statistics for Tissue and Mutation typeTop
- For Inter-chromosomal Variations
* Inter-chromosomal variantions includes 'interchromosomal amplicon to amplicon', 'interchromosomal amplicon to non-amplified dna', 'interchromosomal insertion', 'Interchromosomal unknown type'.
- For Intra-chromosomal Variations
* Intra-chromosomal variantions includes 'intrachromosomal amplicon to amplicon', 'intrachromosomal amplicon to non-amplified dna', 'intrachromosomal deletion', 'intrachromosomal fold-back inversion', 'intrachromosomal inversion', 'intrachromosomal tandem duplication', 'Intrachromosomal unknown type', 'intrachromosomal with inverted orientation', 'intrachromosomal with non-inverted orientation'.
SampleSymbol_aChr_aStart_aEnd_aSymbol_bChr_bStart_bEnd_b
ovaryGLDCchr966279556627975chr955728395572859
ovaryGLDCchr966280526628072chr955728395572859
ovaryGLDCchr966319636631983ADARB2chr1015795761579596
ovaryGLDCchr966385116638531GLDCchr966385616638581
cf) Tissue number; Tissue name (1;Breast, 2;Central_nervous_system, 3;Haematopoietic_and_lymphoid_tissue, 4;Large_intestine, 5;Liver, 6;Lung, 7;Ovary, 8;Pancreas, 9;Prostate, 10;Skin, 11;Soft_tissue, 12;Upper_aerodigestive_tract)

check002.gifRelated fusion transcripts : go to Chitars2.0
* From mRNA Sanger sequences, Chitars2.0 arranged chimeric transcripts. This table shows GLDC related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a

check002.gifOther DBs for Structural Variants
Structural Variants in Ensembl: go to Ensembl Structural variation
Structural Variants in dbVar: go to dbVar

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check002.gifCopy Number Variations in COSMIC: go to COSMIC mutation CNV/Expr
 
Mutation type/ Tissue IDbrcacnscervendomehaematopokidnLintestliverlungnsovarypancreprostskinstomathyrourina
Total # sample1 1     1 1  21  
GAIN (# sample)1 1           1  
LOSS (# sample)        1 1  2   
cf) Tissue ID; Tissue type (1; Breast, 2; Central_nervous_system, 3; Cervix, 4; Endometrium, 5; Haematopoietic_and_lymphoid_tissue, 6; Kidney, 7; Large_intestine, 8; Liver, 9; Lung, 10; NS, 11; Ovary, 12; Pancreas, 13; Prostate, 14; Skin, 15; Stomach, 16; Thyroid, 17; Urinary_tract)

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check002.gifSNV Counts per Each Loci in COSMIC data: go to COSMIC point mutation

 : Non-synonymous mutation, : Synonymous mutation, Circle size denotes number of samples.
Maximum mutation count=4

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=95)
Stat. for Synonymous SNVs
(# total SNVs=18)
Stat. for Deletions
(# total SNVs=1)
Stat. for Insertions
(# total SNVs=2)

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check002.gifTop 10 SNVs Having the Most Samples in COSMIC data
* When you move the cursor on each content, you can see more deailed mutation information on the Tooltip. Those are primary_site,primary_histology,mutation(aa),pubmedID.
GRCh37 positionMutation(aa)Unique sampleID count
chr9:6565392-6565392p.R630*5
chr9:6558671-6558671p.P647L4
chr9:6553497-6553497p.L776L3
chr9:6595073-6595073p.S401F3
chr9:6604606-6604606p.R347I3
chr9:6554674-6554674p.I770I3
chr9:6592871-6592871p.R461W3
chr9:6602171-6602171p.L365V3
chr9:6645251-6645251p.G83G3
chr9:6644632-6644632p.K106E2

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check002.gifSNV Counts per Each Loci in TCGA data

 : non-synonymous mutation, : synonymous mutation, Circle size denotes number of samples.
maximum mutation count=3

Point Mutation/ Tissue ID1234567891011121314151617181920
# sample52 101 2 2  2152 199 15
# mutation52 121 2 2  2252 1910 19
nonsynonymous SNV42 91 2 2  1742 156 15
synonymous SNV1  3       51   44 4
cf) Tissue ID; Tissue type (1; BLCA[Bladder Urothelial Carcinoma], 2; BRCA[Breast invasive carcinoma], 3; CESC[Cervical squamous cell carcinoma and endocervical adenocarcinoma], 4; COAD[Colon adenocarcinoma], 5; GBM[Glioblastoma multiforme], 6; Glioma Low Grade, 7; HNSC[Head and Neck squamous cell carcinoma], 8; KICH[Kidney Chromophobe], 9; KIRC[Kidney renal clear cell carcinoma], 10; KIRP[Kidney renal papillary cell carcinoma], 11; LAML[Acute Myeloid Leukemia], 12; LUAD[Lung adenocarcinoma], 13; LUSC[Lung squamous cell carcinoma], 14; OV[Ovarian serous cystadenocarcinoma ], 15; PAAD[Pancreatic adenocarcinoma], 16; PRAD[Prostate adenocarcinoma], 17; SKCM[Skin Cutaneous Melanoma], 18:STAD[Stomach adenocarcinoma], 19:THCA[Thyroid carcinoma], 20:UCEC[Uterine Corpus Endometrial Carcinoma])

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check002.gifTop 10 SNVs Having the Most Samples in TCGA data
* We represented just top 10 SNVs. When you move the cursor on each content, you can see more deailed mutation information on the Tooltip. Those are primary_site, primary_histology, mutation(aa), pubmedID.
Genomic PositionMutation(aa)Unique sampleID count
chr9:6553497p.L776L3
chr9:6592871p.A204T2
chr9:6644632p.R461W2
chr9:6554674p.K106Q2
chr9:6610217p.T277K2
chr9:6605162p.I770I2
chr9:6553420p.R216T1
chr9:6592147p.E877E1
chr9:6620204p.V735V1
chr9:6556173p.S557F1

check002.gifOther DBs for Point Mutations
Point Mutation Table of Ensembl: go to Ensembl variation table
Mutation of cBioPortal: go to cBioPortal's Cross-cancer alteration summary

check002.gifCopy Number for GLDC in TCGA
* Copy number data were extracted from TCGA using R package TCGA-Assembler. The URLs of all public data files on TCGA DCC data server were gathered on Jan-05-2015. Function ProcessCNAData in TCGA-Assembler package was used to obtain gene-level copy number value which is calculated as the average copy number of the genomic region of a gene.
cf) Tissue ID[Tissue type]: BLCA[Bladder Urothelial Carcinoma], BRCA[Breast invasive carcinoma], CESC[Cervical squamous cell carcinoma and endocervical adenocarcinoma], COAD[Colon adenocarcinoma], GBM[Glioblastoma multiforme], Glioma Low Grade, HNSC[Head and Neck squamous cell carcinoma], KICH[Kidney Chromophobe], KIRC[Kidney renal clear cell carcinoma], KIRP[Kidney renal papillary cell carcinoma], LAML[Acute Myeloid Leukemia], LUAD[Lung adenocarcinoma], LUSC[Lung squamous cell carcinoma], OV[Ovarian serous cystadenocarcinoma ], PAAD[Pancreatic adenocarcinoma], PRAD[Prostate adenocarcinoma], SKCM[Skin Cutaneous Melanoma], STAD[Stomach adenocarcinoma], THCA[Thyroid carcinoma], UCEC[Uterine Corpus Endometrial Carcinoma]

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Gene Expression for GLDC

check002.gifGene Expression in Cancer Cell-lines (CCLE)
* CCLE gene expression data were extracted from CCLE_Expression_Entrez_2012-10-18.res: Gene-centric RMA-normalized mRNA expression data.

check002.gifDifferential Gene Expression in Primary Tumors (TCGA)
* Normalized gene expression data of RNASeqV2 was extracted from TCGA using R package TCGA-Assembler. The URLs of all public data files on TCGA DCC data server were gathered at Jan-05-2015. Only eight cancer types have enough normal control samples for differential expression analysis.
(t test, adjusted p<0.05 (using Benjamini-Hochberg FDR))
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check002.gifCNV vs Gene Expression Plot
* This plots show the correlation between CNV and gene expression.

: Open all plots for all cancer types


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Gene-Gene Network Information
check002.gifCo-Expressed gene's network Plot
* Co-Expression network figures were drawn using R package igraph. Only the top 20 genes with the highest correlations were shown.
Red circle: input gene, orange circle: cell metabolism gene, sky circle: other gene

: Open all plots for all cancer types

AWAT1,C1orf105,CARD18,CST9,CYP2F1,CYP3A4,DGAT2,
DGAT2L6,DOCK3,ELOVL4,GLDC,KRT79,LAPTM4B,MUC15,
PLA2G2F,PNPLA1,PNPLA5,PSAPL1,SLC1A6,SOAT1,TCERG1L
BEX1,LINC00238,PRR35,CHRNA9,COL2A1,CST9,DEFB4A,
FAM135B,FAM196A,FCRLB,FOXI2,GLDC,GNG13,KISS1R,
NELL1,PTPN1,SLC6A4,SLIT1,TCL1B,TTLL8,WFDC11

ACSM2B,ADAMTS18,BANF2,LINC00293,CPN2,CYP11B2,FLJ16779,
GAS2,GFRA3,GLDC,HIST1H2AA,HS3ST4,IGF2-AS,LECT2,
LINC01512,RSPO4,SLC6A2,TMEM207,TPTE2P3,WIF1,ZSCAN10
BHLHA15,BTN1A1,C15orf39,CD27,CSF2RB,GLDC,GPRC5D,
IRF4,ITGB7,KCNA3,KRT74,LAX1,MIXL1,SEMA4A,
SEMA4D,SMOC1,SPN,TBC1D9,TLR7,TLR9,TXNDC5
check002.gifCo-Expressed gene's Protein-protein interaction Network Plot
* Co-Expression network figures were drawn using R package igraph. Only the top 20 genes with the highest correlations were shown.
Red circle: input gene, orange circle: cell metabolism gene, sky circle: other gene

: Open all plots for all cancer types

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check002.gifInteracting Genes (from Pathway Commons)

: Open all interacting genes' information including KEGG pathway for all interacting genes from DAVID

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Pharmacological Information for GLDC
check002.gifCross-referenced pharmacological DB IDs from Uniprot
DB CategoryDB NameDB's ID and Url link

check002.gifDrug-Gene Interaction Network
* Gene Centered Interaction Network.
* Drug Centered Interaction Network.
DrugBank IDTarget NameDrug GroupsGeneric NameDrug Centered NetworkDrug Structure
DB00114glycine dehydrogenase (decarboxylating)nutraceuticalPyridoxal Phosphate
DB00145glycine dehydrogenase (decarboxylating)approved; nutraceuticalGlycine


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Cross referenced IDs for GLDC
* We obtained these cross-references from Uniprot database. It covers 150 different DBs, 18 categories. http://www.uniprot.org/help/cross_references_section

: Open all cross reference information



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