Cancer Cell Metabolism Gene Database

  Cancer Cell Metabolism Gene DB

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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 GPT2
Basic gene info.Gene symbolGPT2
Gene nameglutamic pyruvate transaminase (alanine aminotransferase) 2
SynonymsALT2
CytomapUCSC genome browser: 16q12.1
Genomic locationchr16 :46918307-46965201
Type of geneprotein-coding
RefGenesNM_001142466.1,
NM_133443.2,
Ensembl idENSG00000166123
DescriptionGPT 2alanine aminotransferase 2glutamate pyruvate transaminase 2glutamic--alanine transaminase 2glutamic--pyruvic transaminase 2glutamic-pyruvate transaminase 2
Modification date20141207
dbXrefs MIM : 138210
HGNC : HGNC
Ensembl : ENSG00000166123
HPRD : 06307
Vega : OTTHUMG00000132541
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_GPT2
BioGPS: 84706
Gene Expression Atlas: ENSG00000166123
The Human Protein Atlas: ENSG00000166123
PathwayNCI Pathway Interaction Database: GPT2
KEGG: GPT2
REACTOME: GPT2
ConsensusPathDB
Pathway Commons: GPT2
MetabolismMetaCyc: GPT2
HUMANCyc: GPT2
RegulationEnsembl's Regulation: ENSG00000166123
miRBase: chr16 :46,918,307-46,965,201
TargetScan: NM_001142466
cisRED: ENSG00000166123
ContextiHOP: GPT2
cancer metabolism search in PubMed: GPT2
UCL Cancer Institute: GPT2
Assigned class in ccmGDBC

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Phenotypic Information for GPT2(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: GPT2
Familial Cancer Database: GPT2
* 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_ALANINE_ASPARTATE_AND_GLUTAMATE_METABOLISM
REACTOME_METABOLISM_OF_AMINO_ACIDS_AND_DERIVATIVES

check002.gifOthers
OMIM
Orphanet
DiseaseKEGG Disease: GPT2
MedGen: GPT2 (Human Medical Genetics with Condition)
ClinVar: GPT2
PhenotypeMGI: GPT2 (International Mouse Phenotyping Consortium)
PhenomicDB: GPT2

Mutations for GPT2
* 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
ovaryGPT2chr164692391146923931chr164780940447809424
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 GPT2 related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
BF772696ST51721187372848737355GPT259215164695620246958329

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 # sample11               
GAIN (# sample)11               
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=3

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=29)
Stat. for Synonymous SNVs
(# total SNVs=11)
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
chr16:46956231-46956231p.S372L3
chr16:46943698-46943698p.D227Y2
chr16:46956237-46956237p.R374H2
chr16:46943652-46943652p.I211I2
chr16:46960947-46960947p.F493F1
chr16:46950592-46950592p.E291E1
chr16:46934657-46934657p.K133Q1
chr16:46958311-46958311p.S408L1
chr16:46943701-46943701p.A228T1
chr16:46962845-46962845p.K503M1

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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
# sample 226  2 1  4611154 7
# mutation 226  2 1  4611163 7
nonsynonymous SNV 214  2    34 1 12 5
synonymous SNV  12    1  121 151 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
chr16:46943652p.A142V,GPT22
chr16:46943744p.I111I,GPT22
chr16:46943767p.D97D1
chr16:46956287p.I129I,GPT21
chr16:46934670p.V327V,GPT21
chr16:46950578p.I6I,GPT21
chr16:46931606p.D136D,GPT21
chr16:46958347p.Y340Y,GPT21
chr16:46940822p.F8F,GPT21
chr16:46952534p.M368I,GPT21

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 GPT2 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 GPT2

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

ASNS,CMC2,CFAP20,C16orf87,AUNIP,CDCA8,EMC8,
GPT2,KARS,TLDC1,NAE1,NIP7,NUP93,ORC6,
PAK1IP1,PSAT1,RANBP1,RBM17,RGMA,SHCBP1,SNRPD1
ACAT1,ADHFE1,CS,DLD,DLST,ETFA,ETFDH,
GPT2,HSPB6,KIAA0408,NDUFV3,PDHA1,PDK2,GATB,
PFKFB1,PGM1,PHYH,PLIN5,RNF157,SLC2A4,SLC6A8

AARS,SAPCD2,CCDC86,GARS,GFPT1,GGCT,GOT2,
GPT2,HNRNPAB,LONP1,ORC6,PDF,PGP,PHGDH,
PKMYT1,PSAT1,SAC3D1,SLC19A1,SLC29A2,STC2,ZNF598
ANLN,AURKA,CCNB1,CDC20,CDCA8,CENPA,CENPO,
CEP55,CLDN14,GPT2,GSDMB,KIF18A,KPNA2,MUC1,
MYEOV,NFE2L3,PDIA4,PLK1,POC1A,PSAT1,TMEM214
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 GPT2
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
DB00114glutamic pyruvate transaminase (alanine aminotransferase) 2nutraceuticalPyridoxal Phosphate
DB00142glutamic pyruvate transaminase (alanine aminotransferase) 2approved; nutraceuticalL-Glutamic Acid
DB00160glutamic pyruvate transaminase (alanine aminotransferase) 2approved; nutraceuticalL-Alanine
DB00780glutamic pyruvate transaminase (alanine aminotransferase) 2approvedPhenelzine


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Cross referenced IDs for GPT2
* 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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