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 AGMAT
Basic gene info.Gene symbolAGMAT
Gene nameagmatine ureohydrolase (agmatinase)
Synonyms-
CytomapUCSC genome browser: 1p36.21
Genomic locationchr1 :15898193-15911605
Type of geneprotein-coding
RefGenesNM_024758.4,
Ensembl idENSG00000116771
DescriptionAUHagmatinase, mitochondrial
Modification date20141207
dbXrefs HGNC : HGNC
HPRD : 12436
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_AGMAT
BioGPS: 79814
Gene Expression Atlas: ENSG00000116771
The Human Protein Atlas: ENSG00000116771
PathwayNCI Pathway Interaction Database: AGMAT
KEGG: AGMAT
REACTOME: AGMAT
ConsensusPathDB
Pathway Commons: AGMAT
MetabolismMetaCyc: AGMAT
HUMANCyc: AGMAT
RegulationEnsembl's Regulation: ENSG00000116771
miRBase: chr1 :15,898,193-15,911,605
TargetScan: NM_024758
cisRED: ENSG00000116771
ContextiHOP: AGMAT
cancer metabolism search in PubMed: AGMAT
UCL Cancer Institute: AGMAT
Assigned class in ccmGDBC

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

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

Mutations for AGMAT
* 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 AGMAT 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=2

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=24)
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
chr1:15904318-15904318p.S254S2
chr1:15901300-15901300p.V313M2
chr1:15909809-15909809p.S118S2
chr1:15906613-15906613p.P167L2
chr1:15904213-15904213p.G289G2
chr1:15904240-15904240p.L280L1
chr1:15909876-15909876p.R96H1
chr1:15905490-15905490p.L195P1
chr1:15900149-15900149p.V352V1
chr1:15909693-15909693p.T157I1

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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 2 71 1 31  2   83 3
# mutation 2 61 1 31  2   83 3
nonsynonymous SNV 2 3  1 31  1   31 3
synonymous SNV   31       1   52  
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
chr1:15901300p.V313M2
chr1:15904213p.G289G2
chr1:15909809p.S118S2
chr1:15905364p.A203V1
chr1:15906637p.D192N1
chr1:15900149p.V352V1
chr1:15905399p.T190T1
chr1:15909693p.A335A1
chr1:15900200p.V184M1
chr1:15905419p.G329R1

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 AGMAT 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 AGMAT

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

AGMAT,BAIAP2L2,AUNIP,TMEM252,CDH17,CTH,DEFA6,
HNF4A,HULC,IL27RA,LGALS4,MEP1A,MOGAT3,MUC13,
NOP2,PRKCQ,SLC17A4,SPANXC,TPTE2,VIL1,ZDHHC18
ACHE,AGMAT,ART3,ASB16,ASB2,CTXN3,DPF3,
E2F8,FEM1A,FLJ41941,JPH1,JSRP1,KCNQ5,MYOM3,
OBSCN,PEBP4,PFKM,PRKCQ,SLCO5A1,SRPK3,WDR62

AGMAT,AHCY,AURKA,BZW2,CASP6,CECR5,CSE1L,
DDC,DDX28,DNAJA3,HADH,KHK,LRPPRC,MGC14436,
MRTO4,MTCH2,NARS2,SDHB,SLC25A33,TBRG4,WDR12
AGMAT,AIMP2,AK2,ATP5F1,DRD5,ETFA,GCLM,
HPRT1,KIAA0391,MRRF,MTCH2,NMNAT1,OXNAD1,OXSM,
PDSS1,SLC14A2,SLC25A10,SLC25A39,SLC37A2,TMED5,UQCRC2
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 AGMAT
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
DB00125agmatine ureohydrolase (agmatinase)approved; nutraceuticalL-Arginine
DB03904agmatine ureohydrolase (agmatinase)experimentalUrea


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Cross referenced IDs for AGMAT
* 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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