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 GSS
Basic gene info.Gene symbolGSS
Gene nameglutathione synthetase
SynonymsGSHS|HEL-S-64p|HEL-S-88n
CytomapUCSC genome browser: 20q11.2
Genomic locationchr20 :33516235-33543601
Type of geneprotein-coding
RefGenesNM_000178.2,
Ensembl idENSG00000100983
DescriptionGSH synthetaseGSH-Sepididymis secretory sperm binding protein Li 64pepididymis secretory sperm binding protein Li 88nglutathione synthase
Modification date20141207
dbXrefs MIM : 601002
HGNC : HGNC
Ensembl : ENSG00000100983
HPRD : 03000
Vega : OTTHUMG00000032315
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_GSS
BioGPS: 2937
Gene Expression Atlas: ENSG00000100983
The Human Protein Atlas: ENSG00000100983
PathwayNCI Pathway Interaction Database: GSS
KEGG: GSS
REACTOME: GSS
ConsensusPathDB
Pathway Commons: GSS
MetabolismMetaCyc: GSS
HUMANCyc: GSS
RegulationEnsembl's Regulation: ENSG00000100983
miRBase: chr20 :33,516,235-33,543,601
TargetScan: NM_000178
cisRED: ENSG00000100983
ContextiHOP: GSS
cancer metabolism search in PubMed: GSS
UCL Cancer Institute: GSS
Assigned class in ccmGDBC

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

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

Mutations for GSS
* 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
There's no intra-chromosomal structural variation.
SampleSymbol_aChr_aStart_aEnd_aSymbol_bChr_bStart_bEnd_b
pancreasGSSchr203353663233536652KAT2Achr174027316740273187
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 GSS related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
AW373865BRWD15148214055892440559066GSS140378203351648333516721
AW376720GSS182203351645233516533OASL8343812121458641121461927
L42531GSS11690203351640533543560DHFR1691181157994669579946815
AW894712GSS7289203353074033531020GSS288421203353063133530764
AW849012GSS182203351645233516533OASL8334012121458739121461927
AW848757GSS182203351645233516533OASL8351212121458567121461927
AI802443ZC2HC1A127087962747279629741GSS257638203353034033539581
BF746473MAT2A1912128577156085771663GSS119244203353375633533881

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 # sample        1 1     1
GAIN (# sample)        1 1     1
LOSS (# sample)                 
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=33)
Stat. for Synonymous SNVs
(# total SNVs=2)
Stat. for Deletions
(# total SNVs=2)
Stat. for Insertions
(# total SNVs=0)
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
chr20:33524779-33524779p.D219G3
chr20:33533841-33533841p.Q64E2
chr20:33524780-33524780p.D219Y2
chr20:33524822-33524822p.L205V2
chr20:33517312-33517312p.M398T1
chr20:33533834-33533834p.Y66C1
chr20:33519831-33519831p.P314S1
chr20:33539651-33539651p.A2V1
chr20:33529582-33529582p.S181Y1
chr20:33517323-33517323p.S394S1

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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=2

Point Mutation/ Tissue ID1234567891011121314151617181920
# sample12171 4 1  523  74 5
# mutation12161 4 1  523  74 5
nonsynonymous SNV 2 51 2 1  323  73 5
synonymous SNV1 11  2    2     1  
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
chr20:33524578p.R252Q2
chr20:33524780p.L52L2
chr20:33533875p.D219Y2
chr20:33517328p.V380A1
chr20:33539607p.E144K1
chr20:33530761p.Y375C1
chr20:33517333p.P138A1
chr20:33539633p.Q366H1
chr20:33524591p.S126A1
chr20:33533805p.A357A1

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 GSS 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 GSS

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

ACSS2,CEP250,CPNE1,DYNLRB1,EDEM2,EIF6,ERGIC3,
GGT7,GSS,MMP24,MYH7B,NFS1,NPEPL1,PIGU,
RBMY1A3P,RBMY1E,RBMY1F,RBMY3AP,ROMO1,TRPC4AP,UQCC1
AP1S1,ASL,BSCL2,CDK5,COASY,COMT,COQ4,
DAK,EBP,ERP29,GMPPA,GSS,LMAN2,MBOAT7,
NANS,NMRAL1,P4HB,SCAMP4,SLC35A2,TMED3,TMEM141

ACTR5,AAR2,CDK5RAP1,CHMP4B,CTNNBL1,DDX27,DYNLRB1,
EIF2S2,EIF6,ERGIC3,GSS,HM13,LSM14B,NFS1,
PDRG1,PIGU,RALY,SLC35C2,TOMM34,UBE2V1,UQCC1
AP1M2,APEH,BDH1,MPLKIP,DCAF12,DUS1L,GOT1,
GSS,NDUFA10,NDUFV1,PIGU,RAB25,RCE1,RPIA,
SDSL,SLC25A10,SLC35A4,SMAGP,TTLL12,TUFM,ZDHHC13
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 GSS
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
DB00143glutathione synthetaseapproved; nutraceuticalGlutathione
DB00145glutathione synthetaseapproved; nutraceuticalGlycine
DB00151glutathione synthetaseapproved; nutraceuticalL-Cysteine
DB03408glutathione synthetaseexperimentalGamma-Glutamylcysteine
DB03431glutathione synthetaseexperimentalAdenosine-5'-Diphosphate
DB04395glutathione synthetaseexperimentalPhosphoaminophosphonic Acid-Adenylate Ester
DB00515glutathione synthetaseapprovedCisplatin
DB01033glutathione synthetaseapprovedMercaptopurine
DB00563glutathione synthetaseapprovedMethotrexate


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Cross referenced IDs for GSS
* 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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