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 MAT2B
Basic gene info.Gene symbolMAT2B
Gene namemethionine adenosyltransferase II, beta
SynonymsMAT-II|MATIIbeta|Nbla02999|SDR23E1|TGR
CytomapUCSC genome browser: 5q34-q35
Genomic locationchr5 :162932584-162946328
Type of geneprotein-coding
RefGenesNM_013283.4,
NM_182796.2,
Ensembl idENSG00000038274
DescriptionMAT II betabeta regulatory subunit of methionine adenosyltransferasedTDP-4-keto-6-deoxy-D-glucose 4-reductasemethionine adenosyltransferase 2 subunit betaputative dTDP-4-keto-6-deoxy-D-glucose 4-reductaseputative protein product of Nbla02999short ch
Modification date20141207
dbXrefs MIM : 605527
HGNC : HGNC
Ensembl : ENSG00000038274
HPRD : 05701
Vega : OTTHUMG00000130379
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_MAT2B
BioGPS: 27430
Gene Expression Atlas: ENSG00000038274
The Human Protein Atlas: ENSG00000038274
PathwayNCI Pathway Interaction Database: MAT2B
KEGG: MAT2B
REACTOME: MAT2B
ConsensusPathDB
Pathway Commons: MAT2B
MetabolismMetaCyc: MAT2B
HUMANCyc: MAT2B
RegulationEnsembl's Regulation: ENSG00000038274
miRBase: chr5 :162,932,584-162,946,328
TargetScan: NM_013283
cisRED: ENSG00000038274
ContextiHOP: MAT2B
cancer metabolism search in PubMed: MAT2B
UCL Cancer Institute: MAT2B
Assigned class in ccmGDBC

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Phenotypic Information for MAT2B(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: MAT2B
Familial Cancer Database: MAT2B
* 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
KEGG_SELENOAMINO_ACID_METABOLISM
REACTOME_SULFUR_AMINO_ACID_METABOLISM
REACTOME_METABOLISM_OF_AMINO_ACIDS_AND_DERIVATIVES

check002.gifOthers
OMIM
Orphanet
DiseaseKEGG Disease: MAT2B
MedGen: MAT2B (Human Medical Genetics with Condition)
ClinVar: MAT2B
PhenotypeMGI: MAT2B (International Mouse Phenotyping Consortium)
PhenomicDB: MAT2B

Mutations for MAT2B
* 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 MAT2B related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
BP259408S100A1313021153600914153604262MAT2B2973825162939116162939201

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      
GAIN (# sample)          1      
LOSS (# sample)      1          
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=4

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=34)
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
chr5:162945299-162945299p.R301Q4
chr5:162940613-162940613p.N93I2
chr5:162945236-162945236p.R280I2
chr5:162943705-162943705p.E225E2
chr5:162944660-162944660p.P261S2
chr5:162939192-162939192p.H72R2
chr5:162939205-162939205p.?1
chr5:162943584-162943584p.A185V1
chr5:162930412-162930412p.M4I1
chr5:162945229-162945229p.R278C1

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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 52      41   34 9
# mutation 1 52      41   34 10
nonsynonymous SNV 1 5       41   32 10
synonymous SNV    2            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
chr5:162945236p.R291I,MAT2B2
chr5:162945299p.R312Q,MAT2B2
chr5:162943532p.P2S1
chr5:162945230p.M239I,MAT2B1
chr5:162930404p.M4I1
chr5:162943584p.A268V,MAT2B1
chr5:162930412p.E5E1
chr5:162943622p.P272S,MAT2B1
chr5:162945287p.P27S,MAT2B1
chr5:162932707p.Q288Q,MAT2B1

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 MAT2B 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 MAT2B

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

CREBRF,CDC42SE2,CEP120,ERAP1,FAM114A2,FCHO2,GIMAP2,
MAT2B,MFAP3,PAPD4,POLK,PURA,PWWP2A,RAB8B,
RBM22,RBM27,SLU7,SNX2,TLR3,UBLCP1,ZCCHC10
ASF1A,ARL14EP,C11orf58,C12orf29,C7orf60,CRIPT,KBTBD3,
LAMTOR3,MAT2B,BLOC1S5,NUP54,ORC4,PCNP,PTGES3,
RBM7,SMAD4,SYPL1,THAP10,THAP1,ZNF22,ZNF639

C3orf38,C5orf15,C5orf24,CDC42SE2,CNOT8,COPS4,MAT2B,
MRPL22,NDFIP1,NUDCD2,PPP2CA,RBM22,RNF14,SELT,
SKP1,SLU7,TTC1,TTC33,UBE2B,YIPF5,ZCCHC10
ATG5,C3orf38,CHIC2,DGUOK,DPY30,EAPP,GABARAPL2,
ISCA2,MAT2B,MTIF3,NXT2,PDZD11,PEX11B,PPCS,
RCHY1,SUMO1,SUMO3,TMEM179B,TSPAN31,UBAC2,UFC1
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 MAT2B


There's no related Drug.
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Cross referenced IDs for MAT2B
* 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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