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 CHAT
Basic gene info.Gene symbolCHAT
Gene namecholine O-acetyltransferase
SynonymsCHOACTASE|CMS1A|CMS1A2
CytomapUCSC genome browser: 10q11.2
Genomic locationchr10 :50817140-50873150
Type of geneprotein-coding
RefGenesNM_001142929.1,
NM_001142933.1,NM_001142934.1,NM_020549.4,NM_020984.3,
NM_020985.3,NM_020986.3,
Ensembl idENSG00000070748
Descriptionacetyl CoA:choline O-acetyltransferasecholine acetylase
Modification date20141219
dbXrefs MIM : 118490
HGNC : HGNC
Ensembl : ENSG00000070748
HPRD : 07510
Vega : OTTHUMG00000018198
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_CHAT
BioGPS: 1103
Gene Expression Atlas: ENSG00000070748
The Human Protein Atlas: ENSG00000070748
PathwayNCI Pathway Interaction Database: CHAT
KEGG: CHAT
REACTOME: CHAT
ConsensusPathDB
Pathway Commons: CHAT
MetabolismMetaCyc: CHAT
HUMANCyc: CHAT
RegulationEnsembl's Regulation: ENSG00000070748
miRBase: chr10 :50,817,140-50,873,150
TargetScan: NM_001142929
cisRED: ENSG00000070748
ContextiHOP: CHAT
cancer metabolism search in PubMed: CHAT
UCL Cancer Institute: CHAT
Assigned class in ccmGDBC

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Phenotypic Information for CHAT(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: CHAT
Familial Cancer Database: CHAT
* 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_GLYCEROPHOSPHOLIPID_METABOLISM
REACTOME_PHOSPHOLIPID_METABOLISM
REACTOME_METABOLISM_OF_LIPIDS_AND_LIPOPROTEINS

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

Mutations for CHAT
* 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
breastCHATchr105084176650841766CHATchr105085050150850501
ovaryCHATchr105084148750841507CHATchr105084373750843757
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 CHAT 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
 
Mutation type/ Tissue IDbrcacnscervendomehaematopokidnLintestliverlungnsovarypancreprostskinstomathyrourina
Total # sample 1    1          
GAIN (# sample) 1    1          
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=6

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=81)
Stat. for Synonymous SNVs
(# total SNVs=42)
Stat. for Deletions
(# total SNVs=2)
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
chr10:50835688-50835688p.R323H5
chr10:50873054-50873054p.E737K3
chr10:50856579-50856579p.C436*3
chr10:50859978-50859978p.G520G3
chr10:50835781-50835781p.T354R3
chr10:50835719-50835719p.L333L2
chr10:50856570-50856570p.D433E2
chr10:50822376-50822376p.D47E2
chr10:50827764-50827764p.?2
chr10:50854586-50854586p.R383S2

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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=3

Point Mutation/ Tissue ID1234567891011121314151617181920
# sample52 224 5 3  16131 318917
# mutation52 234 5 3  16131 31910111
nonsynonymous SNV21 154 5 2  108  2114 4
synonymous SNV31 8    1  651 18617
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
chr10:50835688p.R205H,CHAT3
chr10:50859978p.G402G,CHAT3
chr10:50833529p.R314R,CHAT2
chr10:50863176p.S8S,CHAT2
chr10:50824639p.P137S,CHAT2
chr10:50856565p.A439V,CHAT2
chr10:50856570p.E358K,CHAT1
chr10:50870714p.R448R,CHAT1
chr10:50830170p.R28R1
chr10:50857604p.G561V,CHAT1

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 CHAT 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 CHAT

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

C6orf132,CHAT,CLASP1,CT45A5,CTAG1B,LOC148824,NIFK,
MRPS10,MSGN1,NARF,NDRG1,NXF2,PIWIL1,PRSS33,
RIOK1,SIX2,SLC18A3,TMEM117,TSN,USP25,XPO5
NA,NA,NA,NA,NA,NA,NA,
NA,NA,NA,NA,NA,NA,NA,
NA,NA,NA,NA,NA,NA,NA

ASTN1,ATCAY,PIANP,CABP7,CHAT,CLVS2,DPYSL4,
FAM196A,FUT9,HPCAL4,JPH4,KIAA1045,LRRC4B,RGAG4,
SLC7A14,SSTR2,SYT4,SYT6,TCEAL5,TMEM59L,UNC80
ACAN,AWAT2,BMX,C20orf141,NCOR1P1,CCDC129,CHAT,
CLEC4G,GPX5,KPRP,LCE2C,LPA,MEPE,CHODL-AS1,
OR2D2,PGLYRP3,POU2F3,SH2D7,SNORA79,TRIM6-TRIM34,ZSWIM2
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 CHAT
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
DB00122choline O-acetyltransferaseapproved; nutraceuticalCholine
DB01156choline O-acetyltransferaseapprovedBupropion
DB03128choline O-acetyltransferaseexperimentalAcetylcholine
DB00843choline O-acetyltransferaseapprovedDonepezil


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Cross referenced IDs for CHAT
* 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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