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 MTAP
Basic gene info.Gene symbolMTAP
Gene namemethylthioadenosine phosphorylase
SynonymsBDMF|DMSFH|DMSMFH|HEL-249|LGMBF|MSAP|c86fus
CytomapUCSC genome browser: 9p21
Genomic locationchr9 :21802634-21865969
Type of geneprotein-coding
RefGenesNM_002451.3,
Ensembl idENSG00000099810
Description5'-methylthioadenosine phosphorylaseMTA phosphorylaseMTAPaseMeSAdo phosphorylaseS-methyl-5'-thioadenosine phosphorylaseepididymis luminal protein 249
Modification date20141207
dbXrefs MIM : 156540
HGNC : HGNC
Ensembl : ENSG00000099810
HPRD : 01134
Vega : OTTHUMG00000019690
ProteinUniProt: Q13126
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_MTAP
BioGPS: 4507
Gene Expression Atlas: ENSG00000099810
The Human Protein Atlas: ENSG00000099810
PathwayNCI Pathway Interaction Database: MTAP
KEGG: MTAP
REACTOME: MTAP
ConsensusPathDB
Pathway Commons: MTAP
MetabolismMetaCyc: MTAP
HUMANCyc: MTAP
RegulationEnsembl's Regulation: ENSG00000099810
miRBase: chr9 :21,802,634-21,865,969
TargetScan: NM_002451
cisRED: ENSG00000099810
ContextiHOP: MTAP
cancer metabolism search in PubMed: MTAP
UCL Cancer Institute: MTAP
Assigned class in ccmGDBA - This gene has a literature evidence and it belongs to cancer gene.
References showing role of MTAP in cancer cell metabolism1. Shlomi T, Fan J, Tang B, Kruger WD, Rabinowitz JD (2014) Quantitation of cellular metabolic fluxes of methionine. Analytical chemistry 86: 1583-1591. go to article
2. Munshi PN, Lubin M, Bertino JR (2014) 6-Thioguanine: A drug with unrealized potential for cancer therapy. The oncologist: theoncologist. 2014-0178. go to article

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

check002.gifOthers
OMIM 112250; phenotype.
112250; phenotype.
156540; gene.
156540; gene.
Orphanet 85182; Diaphyseal medullary stenosis - bone malignancy.
85182; Diaphyseal medullary stenosis - bone malignancy.
DiseaseKEGG Disease: MTAP
MedGen: MTAP (Human Medical Genetics with Condition)
ClinVar: MTAP
PhenotypeMGI: MTAP (International Mouse Phenotyping Consortium)
PhenomicDB: MTAP

Mutations for MTAP
* 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
haematopoietic_and_lymphoid_tissueMTAPchr92184895721848957MTAPchr92184895721848957
pancreasMTAPchr92180262821802648chr91376669313766713
pancreasMTAPchr92180337721803397MTAPchr92180367721803697
pancreasMTAPchr92181228921812309chr92223740822237428
pancreasMTAPchr92182102921821049chr92251820522518225
pancreasMTAPchr92182866521828685MTAPchr92182972921829749
pancreasMTAPchr92182867521828695MTAPchr92182991221829932
pancreasMTAPchr92182913921829159chr92257234222572362
pancreasMTAPchr92182973221829752MTAPchr92182992021829940
pancreasMTAPchr92183355821833578CDKN2B-AS1chr92202349022023510
pancreasMTAPchr92184036321840363chr92283462922834629
pancreasMTAPchr92184269321842713CDKN2B-AS1chr92204764622047666
pancreasMTAPchr92184931921849319ELAVL2chr92374519523745195
pancreasMTAPchr92185114821851168CDKN2B-AS1chr92207641422076434
pancreasMTAPchr92185537921855399chr92585275525852775
pancreasMTAPchr92186074121860761CDKN2B-AS1chr92202672122026741
pancreasMTAPchr92186448821864508chr92232054522320565
pancreasMTAPchr92186565721865677CDKN2B-AS1chr92208531322085333
skinMTAPchr92181066721810667FLJ35282chr92269703622697036
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 MTAP related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
CN365873MTAP111092197090821971017MTAP10516792197471521974777
CR738223UPF2161101201146112011521MTAP5522092186102621861193

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 # sample529 1 1  14 1  144 12
GAIN (# sample)1         1      
LOSS (# sample)429 1 1  14    144 12
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=14)
Stat. for Synonymous SNVs
(# total SNVs=9)
Stat. for Deletions
(# total SNVs=1)
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
chr9:21816739-21816739p.K49K3
chr9:21837988-21837988p.P143P2
chr9:21816750-21816750p.V53A1
chr9:21854633-21854633p.L152F1
chr9:21859391-21859391p.S260S1
chr9:21816758-21816758p.V56I1
chr9:21854687-21854687p.V170I1
chr9:21859395-21859395p.E262K1
chr9:21816760-21816760p.V56V1
chr9:21854695-21854695p.I172I1

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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 1 1  2 3  12   51 7
# mutation 1 1  2 3  12   71 8
nonsynonymous SNV 1    2 2   2   41 4
synonymous SNV   1    1  1    3  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
chr9:21837988p.P143P2
chr9:21818104p.F113L1
chr9:21854712p.A218A1
chr9:21818193p.S123F1
chr9:21854722p.P256S1
chr9:21837927p.C136R1
chr9:21854770p.S260S1
chr9:21837965p.E142E1
chr9:21854777p.E262K1
chr9:21837985p.C145G1

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 MTAP 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 MTAP

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

CDKN2A-AS1,CAAP1,CDKN2A,FAM136A,HAUS6,KIAA0020,FOCAD,
KLHL9,MELK,MTAP,NFIB,PLAA,POLR1E,PRKX,
RCL1,SERBP1,SUV39H2,SYNCRIP,TEX10,TOMM5,UHRF2
GOPC,JRKL,KIAA1804,KLHL9,MBLAC2,MBTD1,MTAP,
NFXL1,PAN3,PHF6,PUM2,SASS6,SPIN4,SUDS3,
SUV420H1,TRIM2,USP1,ZBTB33,ZNF12,ZNF84,ZZZ3

APTX,CHORDC1,DNAJA1,EXOSC3,HAUS6,KIAA0020,LOC727896,
SLC25A51,MTAP,NCL,NOL6,POLR1E,PSIP1,QSOX2,
RCL1,SET,SIGMAR1,SMU1,STIP1,UBAP2,ZCCHC7
AP3M1,ARMCX3,KANSL1L,C3orf58,DDX19A,DHX57,EIF5B,
GEMIN5,HLTF,IPO7,CFAP97,LOC221710,LRRC58,MTAP,
MYEF2,NEDD1,NUCKS1,JADE3,PHF20,TOMM70A,ZMYM4
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 MTAP
check002.gifCross-referenced pharmacological DB IDs from Uniprot
DB CategoryDB NameDB's ID and Url link
ChemistryBindingDB Q13126; -.
ChemistryChEMBL CHEMBL4941; -.
ChemistryBindingDB Q13126; -.
ChemistryChEMBL CHEMBL4941; -.
Organism-specific databasesPharmGKB PA31220; -.
Organism-specific databasesPharmGKB PA31220; -.
Organism-specific databasesCTD 4507; -.
Organism-specific databasesCTD 4507; -.

check002.gifDrug-Gene Interaction Network
* Gene Centered Interaction Network.
* Drug Centered Interaction Network.
DrugBank IDTarget NameDrug GroupsGeneric NameDrug Centered NetworkDrug Structure
DB00173methylthioadenosine phosphorylaseapproved; nutraceuticalAdenine
DB02158methylthioadenosine phosphorylaseexperimental(1s)-1-(9-Deazaadenin-9-Yl)-1,4,5-Trideoxy-1,4-Imino-5-Methylthio-D-Ribitol
DB02281methylthioadenosine phosphorylaseexperimentalFormycin
DB02282methylthioadenosine phosphorylaseexperimental5'-Deoxy-5'-Methylthioadenosine
DB02933methylthioadenosine phosphorylaseexperimental5'-Deoxy-5'-(Methylthio)-Tubercidin


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Cross referenced IDs for MTAP
* 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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