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 GSTT2
Basic gene info.Gene symbolGSTT2
Gene nameglutathione S-transferase theta 2 (gene/pseudogene)
Synonyms-
CytomapUCSC genome browser: 22q11.23
Genomic locationchr22 :24299600-24303393
Type of geneprotein-coding
RefGenesNM_000854.4,
NM_001302670.1,NR_126442.1,NR_126445.1,NR_126446.1,
Ensembl idENSG00000099984
DescriptionGST class-theta-2glutathione S-transferase theta-2
Modification date20141207
dbXrefs MIM : 600437
HGNC : HGNC
Ensembl : ENSG00000099984
HPRD : 02701
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_GSTT2
BioGPS: 2953
Gene Expression Atlas: ENSG00000099984
The Human Protein Atlas: ENSG00000099984
PathwayNCI Pathway Interaction Database: GSTT2
KEGG: GSTT2
REACTOME: GSTT2
ConsensusPathDB
Pathway Commons: GSTT2
MetabolismMetaCyc: GSTT2
HUMANCyc: GSTT2
RegulationEnsembl's Regulation: ENSG00000099984
miRBase: chr22 :24,299,600-24,303,393
TargetScan: NM_000854
cisRED: ENSG00000099984
ContextiHOP: GSTT2
cancer metabolism search in PubMed: GSTT2
UCL Cancer Institute: GSTT2
Assigned class in ccmGDBC

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Phenotypic Information for GSTT2(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: GSTT2
Familial Cancer Database: GSTT2
* 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
KEGG_METABOLISM_OF_XENOBIOTICS_BY_CYTOCHROME_P450
KEGG_DRUG_METABOLISM_CYTOCHROME_P450

check002.gifOthers
OMIM
Orphanet
DiseaseKEGG Disease: GSTT2
MedGen: GSTT2 (Human Medical Genetics with Condition)
ClinVar: GSTT2
PhenotypeMGI: GSTT2 (International Mouse Phenotyping Consortium)
PhenomicDB: GSTT2

Mutations for GSTT2
* 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
There's no structural variation information in COSMIC data for this gene.

check002.gifRelated fusion transcripts : go to Chitars2.0
* From mRNA Sanger sequences, Chitars2.0 arranged chimeric transcripts. This table shows GSTT2 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
There's no copy number variation information in COSMIC data for this gene.

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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=1

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=4)
Stat. for Synonymous SNVs
(# total SNVs=3)
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
chr22:24325605-24325605p.Y181*2
chr22:24323194-24323194p.T56T1
chr22:24323218-24323218p.L64F1
chr22:24323226-24323226p.S67N1
chr22:24323227-24323227p.?1
chr22:24324928-24324928p.D104N1
chr22:24325062-24325062p.V118M1
chr22:24325095-24325095p.K129E1
chr22:24323131-24323131p.?1
chr22:24325127-24325127p.M139I1

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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=0

Point Mutation/ Tissue ID1234567891011121314151617181920
# sample                    
# mutation                    
nonsynonymous SNV                    
synonymous SNV                    
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

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 GSTT2 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 GSTT2

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

AACS,ACSBG1,AKR1D1,LINC01554,CLEC4C,FCN2,GSTM2P1,
GSTM5,GSTT2,GUSB,HIST3H3,LOC91948,MAGEB3,MYOM2,
NANOG,LINC00160,NR1H4,RNASE11,RNASE12,SLC6A3,TMPRSS9
ABCC11,ABCC2,AKR1D1,B3GAT1,C6orf223,CLDN14,CPB2,
FIBCD1,GSTT2,HMGCR,HMGCS1,LOC255167,LRFN2,MVD,
MSMO1,SLC5A11,SLCO1B1,SYCP1,TARP,TRPC7,ZP2

ANXA5,ARHGAP10,ARHGAP29,CORO6,ELOVL4,FAM124A,GLI3,
GSTT2,HCG4,KIAA1462,NIM1K,NTNG1,PABPC4L,PALLD,
PODXL,RAB34,RGS2,RNF144B,SCHIP1,SRPX,VEGFC
ATP2B3,BOC,SSR4P1,COL6A3,FZD4,GPIHBP1,GSTT2,
HIST2H2BA,HMX1,LEFTY2,LRRC2,LYPD2,MAN1C1,MAP3K3,
MYH10,OLFML3,SEZ6L,STC2,SV2B,THBS2,TSHZ2
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 GSTT2
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
DB00515glutathione S-transferase theta 2approvedCisplatin
DB01248glutathione S-transferase theta 2approved; investigationalDocetaxel


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Cross referenced IDs for GSTT2
* 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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