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 GCLC
Basic gene info.Gene symbolGCLC
Gene nameglutamate-cysteine ligase, catalytic subunit
SynonymsGCL|GCS|GLCL|GLCLC
CytomapUCSC genome browser: 6p12
Genomic locationchr6 :53362139-53409927
Type of geneprotein-coding
RefGenesNM_001197115.1,
NM_001498.3,
Ensembl idENSG00000001084
DescriptionGCS heavy chaingamma-ECSgamma-glutamylcysteine synthetaseglutamate--cysteine ligase catalytic subunit
Modification date20141207
dbXrefs MIM : 606857
HGNC : HGNC
Ensembl : ENSG00000001084
HPRD : 06032
Vega : OTTHUMG00000160220
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_GCLC
BioGPS: 2729
Gene Expression Atlas: ENSG00000001084
The Human Protein Atlas: ENSG00000001084
PathwayNCI Pathway Interaction Database: GCLC
KEGG: GCLC
REACTOME: GCLC
ConsensusPathDB
Pathway Commons: GCLC
MetabolismMetaCyc: GCLC
HUMANCyc: GCLC
RegulationEnsembl's Regulation: ENSG00000001084
miRBase: chr6 :53,362,139-53,409,927
TargetScan: NM_001197115
cisRED: ENSG00000001084
ContextiHOP: GCLC
cancer metabolism search in PubMed: GCLC
UCL Cancer Institute: GCLC
Assigned class in ccmGDBC

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Phenotypic Information for GCLC(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: GCLC
Familial Cancer Database: GCLC
* 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_GLUTATHIONE_METABOLISM
REACTOME_SULFUR_AMINO_ACID_METABOLISM
REACTOME_METABOLISM_OF_AMINO_ACIDS_AND_DERIVATIVES

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

Mutations for GCLC
* 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
There's no inter-chromosomal structural variation.
- 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
ovaryGCLCchr65336593553365955chr65334717853347198
ovaryGCLCchr65337413953374159chr65334921453349234
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 GCLC related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
AA010005ATP11B11413182639276182639415GCLC13721465336316953363246
DB542246GCLC115265337476153374912PDSS1151481102703419527034523

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 # sample2       1        
GAIN (# sample)2                
LOSS (# sample)        1        
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=5

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=44)
Stat. for Synonymous SNVs
(# total SNVs=13)
Stat. for Deletions
(# total SNVs=0)
Stat. for Insertions
(# total SNVs=0)
There's no deleted snv.There's no inserted snv.

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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
chr6:53379056-53379056p.P233P3
chr6:53385601-53385601p.L141V3
chr6:53379057-53379057p.P233L2
chr6:53371755-53371755p.E385K2
chr6:53365257-53365257p.F484L2
chr6:53365299-53365299p.M470V2
chr6:53363579-53363579p.G630E2
chr6:53374019-53374019p.E261D1
chr6:53365038-53365038p.?1
chr6:53370274-53370274p.E437E1

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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
# sample12 91 1 1  1321  94 6
# mutation12 91 1 1  1421  94 9
nonsynonymous SNV12 7       122   51 7
synonymous SNV   21 1 1  2 1  43 2
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
chr6:53379056p.P195P,GCLC3
chr6:53373486p.F446L,GCLC2
chr6:53365257p.P246P,GCLC2
chr6:53379057p.P195Q,GCLC2
chr6:53387244p.G302R,GCLC1
chr6:53370601p.D177Y1
chr6:53373417p.P494T,GCLC1
chr6:53379269p.K288R,GCLC1
chr6:53364879p.L141L,GCLC1
chr6:53370630p.K489N,GCLC1

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 GCLC 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 GCLC

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

AFTPH,ALKBH8,ZFAND4,AP1AR,EDEM3,ELOVL5,FBXO9,
FNIP1,GCLC,IBTK,ICK,UFL1,LRRC1,MANEA,
PCYOX1,PLA2G12A,STAM2,TMED7,UBR3,USP14,ZNF451
ACO1,C8orf34,DDHD2,DMGDH,ESR2,FERMT2,GCLC,
HRASLS5,MDFIC,OSGIN2,PCYOX1,PDE3B,PLOD2,PPP2R5A,
PRKAR2B,SIK2,SLC25A16,TMEM135,TSPAN3,UBA2,UVRAG

MCUR1,CIRH1A,CUL3,GCLC,HSPH1,KPNA3,LTV1,
NARS2,NUFIP1,PAK1IP1,PPP1R2,PPP1R2P3,PRIM2,PUS7,
RHOT1,RPIA,RPP40,STRBP,TOMM34,TUBE1,XPO5
ALOX15,CREBRF,CAPN7,CDK20,CENPC,CXorf57,DLEU7,
FNDC7,GCLC,GSG1L,RIC1,KLHL24,MYLK3,PAPD5,
PIK3R1,PRTN3,RB1CC1,SENP6,SMAD4,ZNF518B,ZNF549
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 GCLC
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
DB00142glutamate-cysteine ligase, catalytic subunitapproved; nutraceuticalL-Glutamic Acid
DB00151glutamate-cysteine ligase, catalytic subunitapproved; nutraceuticalL-Cysteine
DB00515glutamate-cysteine ligase, catalytic subunitapprovedCisplatin
DB00143glutamate-cysteine ligase, catalytic subunitapproved; nutraceuticalGlutathione


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Cross referenced IDs for GCLC
* 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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