Cancer Cell Metabolism Database ~~ Bioinformatics and Systems Medicine Laboratory ~~

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 DDC

Basic gene info.	Gene symbol	DDC
	Gene name	dopa decarboxylase (aromatic L-amino acid decarboxylase)
	Synonyms	AADC
	Cytomap	UCSC genome browser: 7p12.2
	Genomic location	chr7 :50526133-50628768
	Type of gene	protein-coding
	RefGenes	NM_000790.3, NM_001082971.1,NM_001242886.1,NM_001242887.1,NM_001242888.1, NM_001242889.1,NM_001242890.1,
	Ensembl id	ENSG00000132437
	Description	aromatic-L-amino-acid decarboxylase
	Modification date	20141211
dbXrefs	MIM : 107930
	HGNC : HGNC
	Ensembl : ENSG00000132437
	HPRD : 00145
	Vega : OTTHUMG00000023353
Protein	UniProt: go to UniProt's Cross Reference DB Table
Expression	CleanEX: HS_DDC
	BioGPS: 1644
	Gene Expression Atlas: ENSG00000132437
	The Human Protein Atlas: ENSG00000132437
Pathway	NCI Pathway Interaction Database: DDC
	KEGG: DDC
	REACTOME: DDC
	ConsensusPathDB
	Pathway Commons: DDC
Metabolism	MetaCyc: DDC
	HUMANCyc: DDC
Regulation	Ensembl's Regulation: ENSG00000132437
	miRBase: chr7 :50,526,133-50,628,768
	TargetScan: NM_000790
	cisRED: ENSG00000132437
Context	iHOP: DDC
	cancer metabolism search in PubMed: DDC
	UCL Cancer Institute: DDC
Assigned class in ccmGDB	C

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Phenotypic Information for DDC(metabolism pathway, cancer, disease, phenome)

Cancer Description
Cancer	CGAP: DDC
	Familial Cancer Database: DDC

* 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/

Metabolic Pathway Description
KEGG_HISTIDINE_METABOLISM KEGG_TYROSINE_METABOLISM KEGG_PHENYLALANINE_METABOLISM KEGG_TRYPTOPHAN_METABOLISM REACTOME_METABOLISM_OF_AMINO_ACIDS_AND_DERIVATIVES

Others
OMIM
Orphanet
Disease	KEGG Disease: DDC
	MedGen: DDC (Human Medical Genetics with Condition)
	ClinVar: DDC
Phenotype	MGI: DDC (International Mouse Phenotyping Consortium)
Phenotype	PhenomicDB: DDC

Mutations for DDC

* 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.

Structural Variants in COSMIC : go to COSMIC mutation histogram

- Statistics for Tissue and Mutation type

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- For Inter-chromosomal Variations

* Inter-chromosomal variantions includes 'interchromosomal amplicon to amplicon', 'interchromosomal amplicon to non-amplified dna', 'interchromosomal insertion', 'Interchromosomal unknown type'.

- For Intra-chromosomal Variations

There's no intra-chromosomal structural variation.

Sample	Symbol_a	Chr_a	Start_a	End_a	Symbol_b	Chr_b	Start_b	End_b
pancreas	DDC	chr7	50573256	50573276		chr6	29490618	29490638

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)

Related fusion transcripts : go to Chitars2.0

* From mRNA Sanger sequences, Chitars2.0 arranged chimeric transcripts. This table shows DDC related fusion information.

Head Gene

Tail Gene

Accession

Gene_a

qStart_a

qEnd_a

Chromosome_a

tStart_a

tEnd_a

Gene_a

qStart_a

qEnd_a

Chromosome_a

tStart_a

tEnd_a

Other DBs for Structural Variants

Structural Variants in Ensembl: go to Ensembl Structural variation

Structural Variants in dbVar: go to dbVar

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Copy Number Variations in COSMIC : go to COSMIC mutation CNV/Expr

Mutation type/ Tissue ID	brca	cns	cerv	endome	haematopo	kidn	Lintest	liver	lung	ns	ovary	pancre	prost	skin	stoma	thyro	urina
Total # sample	7	3	1	2	1	4	3		5		2			2	7	4	1
GAIN (# sample)	7	3	1	1		4	3		4		2			2	7	3
LOSS (# sample)				1	1				1							1	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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SNV 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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Somatic Mutation Counts per Tissue in COSMIC data

Stat. for Non-Synonymous SNVs (# total SNVs=59)	Stat. for Synonymous SNVs (# total SNVs=19)

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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Top 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 position	Mutation(aa)	Unique sampleID count
chr7:50607722-50607722	p.T69M	3
chr7:50534976-50534976	p.R393L	3
chr7:50596938-50596938	p.M180L	2
chr7:50537852-50537852	p.L353L	2
chr7:50607667-50607667	p.P87P	2
chr7:50596945-50596945	p.A177A	2
chr7:50605614-50605614	p.E127K	2
chr7:50537776-50537776	p.R379S	2
chr7:50605624-50605624	p.G123G	2
chr7:50611760-50611760	p.R8R	2

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SNV 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 ID	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20
# sample	3	1		6	2		5		3			5	8	4		1	19	5		10
# mutation	3	1		6	3		5		3			6	8	4		1	22	5		13
nonsynonymous SNV	3	1		4	3		5		3			4	6	2			11	5		12
synonymous SNV				2								2	2	2		1	11			1

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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Top 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 Position	Mutation(aa)	Unique sampleID count
chr7:50607722	p.E89K,DDC	2
chr7:50605624	p.G85G,DDC	2
chr7:50537852	p.L275L,DDC	2
chr7:50605614	p.T69M,DDC	2
chr7:50563091	p.D395N,DDC	1
chr7:50607692	p.R315C,DDC	1
chr7:50596906	p.D193N,DDC	1
chr7:50611675	p.L95F,DDC	1
chr7:50531032	p.D59G,DDC	1
chr7:50537777	p.A394A,DDC	1

Other 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

Copy Number for DDC 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 DDC

Gene 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.

Differential 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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CNV 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

Co-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


AACS,ACSM1,AKR1D1,B3GAT1,C6orf223,DDC,FCN2, GSTM5,GSTT2,GUSB,ISX,KCNA4,LOC91948,LST-3TM12, MYOM2,PNLIPRP3,RNASE11,RNASE12,SLCO1B1,SULT1C3,TMPRSS9	ABCC12,ACSM1,ADCY10,AKR1D1,C15orf43,CTNNA2,DDC, ELOVL7,EPS8L3,HIST1H2AG,HIST1H2BJ,HIST1H3G,IYD,LOC285692, OR10A7,OR10S1,OR52E8,RIMS1,SLC12A3,SLC26A6,ZP2

AGMAT,AHCY,AIMP2,ASL,BZW2,MPLKIP,TMEM243, MALSU1,YAE1D1,CCT6A,CHCHD2,CYCS,DDC,DDX56, GGCT,HIBADH,LSM5,NUPL2,ORC5,TBRG4,ZNRF2	ACY1,CHN2,CLDN15,CYP2J2,DDC,DHRS4L2,EPHX2, GOLT1A,HNF4G,LOC201651,LRRC28,MACC1,MMEL1,MS4A8, MYO1A,OTC,PCK2,PTGR1,SLC2A9,SLC37A4,AGMO

Co-Expressed gene's Protein-protein interaction Network Plot

: Open all plots for all cancer types

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Interacting 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 DDC

Cross-referenced pharmacological DB IDs from Uniprot

DB Category

DB Name

DB's ID and Url link

Drug-Gene Interaction Network

* Gene Centered Interaction Network.

* Drug Centered Interaction Network.

DrugBank ID	Target Name	Drug Groups	Generic Name	Drug Centered Network	Drug Structure
DB00114	dopa decarboxylase (aromatic L-amino acid decarboxylase)	nutraceutical	Pyridoxal Phosphate
DB00190	dopa decarboxylase (aromatic L-amino acid decarboxylase)	approved	Carbidopa
DB00126	dopa decarboxylase (aromatic L-amino acid decarboxylase)	approved; nutraceutical	Vitamin C
DB00184	dopa decarboxylase (aromatic L-amino acid decarboxylase)	approved	Nicotine
DB01235	dopa decarboxylase (aromatic L-amino acid decarboxylase)	approved	Levodopa
DB00988	dopa decarboxylase (aromatic L-amino acid decarboxylase)	approved	Dopamine
DB00135	dopa decarboxylase (aromatic L-amino acid decarboxylase)	approved; nutraceutical	L-Tyrosine
DB00360	dopa decarboxylase (aromatic L-amino acid decarboxylase)	approved; investigational	Tetrahydrobiopterin
DB00150	dopa decarboxylase (aromatic L-amino acid decarboxylase)	approved; nutraceutical	L-Tryptophan
DB01001	dopa decarboxylase (aromatic L-amino acid decarboxylase)	approved	Salbutamol

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Cross referenced IDs for DDC

* 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