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 AFMID
Basic gene info.Gene symbolAFMID
Gene namearylformamidase
SynonymsFKF|KF|KFA
CytomapUCSC genome browser: 17q25.3
Genomic locationchr17 :76183397-76203782
Type of geneprotein-coding
RefGenesNM_001010982.4,
NM_001145526.2,NR_027083.1,
Ensembl idENSG00000183077
DescriptionFKFKFAKFaseN-formylkynurenine formamidasekynurenine formamidaseprobable arylformamidase
Modification date20141207
dbXrefs HGNC : HGNC
Ensembl : ENSG00000183077
HPRD : 16478
Vega : OTTHUMG00000153957
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_AFMID
BioGPS: 125061
Gene Expression Atlas: ENSG00000183077
The Human Protein Atlas: ENSG00000183077
PathwayNCI Pathway Interaction Database: AFMID
KEGG: AFMID
REACTOME: AFMID
ConsensusPathDB
Pathway Commons: AFMID
MetabolismMetaCyc: AFMID
HUMANCyc: AFMID
RegulationEnsembl's Regulation: ENSG00000183077
miRBase: chr17 :76,183,397-76,203,782
TargetScan: NM_001010982
cisRED: ENSG00000183077
ContextiHOP: AFMID
cancer metabolism search in PubMed: AFMID
UCL Cancer Institute: AFMID
Assigned class in ccmGDBC

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Phenotypic Information for AFMID(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: AFMID
Familial Cancer Database: AFMID
* 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_TRYPTOPHAN_METABOLISM
KEGG_GLYOXYLATE_AND_DICARBOXYLATE_METABOLISM
REACTOME_METABOLISM_OF_AMINO_ACIDS_AND_DERIVATIVES

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

Mutations for AFMID
* 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
* Inter-chromosomal variantions includes 'interchromosomal amplicon to amplicon', 'interchromosomal amplicon to non-amplified dna', 'interchromosomal insertion', 'Interchromosomal unknown type'.
- 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
ovaryAFMIDchr177618740776187427AFMIDchr177618877876188798
pancreasAFMIDchr177618897276188992AFMIDchr177619348576193505
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 AFMID related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
W90454A2M12841292439159247627AFMID278411177620364876203780
BX509939IDS1290X148560307148560595AFMID276671177620206276203316
BX647783AFMID2644177618344376203316IDS630925X148560300148560595

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 # sample1                
GAIN (# sample)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=3

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=26)
Stat. for Synonymous SNVs
(# total SNVs=7)
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
chr17:76201787-76201787p.E250K3
chr17:76201792-76201792p.F251F3
chr17:76200772-76200772p.T115M2
chr17:76187059-76187059p.E24D2
chr17:76187085-76187085p.V33A2
chr17:76201534-76201534p.V193V2
chr17:76201678-76201678p.?2
chr17:76201688-76201688p.D217Y1
chr17:76198600-76198600p.T59S1
chr17:76201796-76201796p.R253*1

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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
# sample21 5  2 1  5 1  71 5
# mutation21 5  2 1  5 1  51 6
nonsynonymous SNV21 3  2 1  3 1  31 4
synonymous SNV   2       2    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
chr17:76201792p.F251F,AFMID3
chr17:76200772p.T115M,AFMID2
chr17:76187059p.E24D,AFMID2
chr17:76201707p.A108A,AFMID1
chr17:76198676p.Q303H,AFMID1
chr17:76201752p.Y152C,AFMID1
chr17:76200751p.G195V,AFMID1
chr17:76201777p.L215M,AFMID1
chr17:76200752p.D217Y,AFMID1
chr17:76201782p.D3N,AFMID1

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 AFMID 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 AFMID

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

AFMID,AKR1C2,AKR1D1,C15orf43,CLPSL1,C6orf223,ARMC12,
CDC42EP5,DBI,GGT1,GGT3P,GGTLC1,GGTLC2,HPD,
KCNG2,LOC644165,RRP7B,SERHL2,SERHL,SPINK8,SULT1C3
ABCC11,AFMID,ALOX15B,B3GAT1,C15orf43,C6orf223,DHRS2,
GGT1,HMGCS2,HPGD,HSD3B2,LST-3TM12,MPV17L,NSUN2,
PNLIPRP3,SERHL2,SERHL,SRD5A1,TARP,TMPRSS11F,UGT2B10

AFMID,ANAPC11,AUP1,TEN1,C17orf89,DCXR,EIF1,
GPS1,ICT1,MRPL12,MRPL38,MRPS7,NARF,NAT9,
NME2,NT5C3B,PHB,RPL38,SUMO2,TMEM101,TSEN54
AFMID,BID,C12orf66,FOPNL,EIF4EBP1,GEMIN7,GSTO2,
KRTCAP3,NIPSNAP1,RPL18A,RPL29,RPLP0,SFXN4,SUMF2,
SYNGR2,TARBP2,TBCCD1,TBL2,TGIF1,TMEM5,YIPF2
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 AFMID
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
DB00130arylformamidaseapproved; nutraceutical; investigationalL-Glutamine
DB00160arylformamidaseapproved; nutraceuticalL-Alanine
DB00150arylformamidaseapproved; nutraceuticalL-Tryptophan


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Cross referenced IDs for AFMID
* 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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