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 PNPO
Basic gene info.Gene symbolPNPO
Gene namepyridoxamine 5'-phosphate oxidase
SynonymsHEL-S-302|PDXPO
CytomapUCSC genome browser: 17q21.32
Genomic locationchr17 :46018888-46026674
Type of geneprotein-coding
RefGenesNM_018129.3,
Ensembl idENSG00000108439
Descriptionepididymis secretory protein Li 302pyridoxal 5'-phosphate synthasepyridoxamine-phosphate oxidasepyridoxine 5'-phosphate oxidasepyridoxine-5'-phosphate oxidase
Modification date20141207
dbXrefs MIM : 603287
HGNC : HGNC
HPRD : 04476
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_PNPO
BioGPS: 55163
Gene Expression Atlas: ENSG00000108439
The Human Protein Atlas: ENSG00000108439
PathwayNCI Pathway Interaction Database: PNPO
KEGG: PNPO
REACTOME: PNPO
ConsensusPathDB
Pathway Commons: PNPO
MetabolismMetaCyc: PNPO
HUMANCyc: PNPO
RegulationEnsembl's Regulation: ENSG00000108439
miRBase: chr17 :46,018,888-46,026,674
TargetScan: NM_018129
cisRED: ENSG00000108439
ContextiHOP: PNPO
cancer metabolism search in PubMed: PNPO
UCL Cancer Institute: PNPO
Assigned class in ccmGDBC

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Phenotypic Information for PNPO(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: PNPO
Familial Cancer Database: PNPO
* 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
REACTOME_METABOLISM_OF_VITAMINS_AND_COFACTORS

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

Mutations for PNPO
* 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
pancreasPNPOchr174602617146026191C17orf28chr177295068172950701
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 PNPO related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
BG231914PNPO14163174602550246025651ALDH1A2161457155824580158246097
BQ218587PNPO1150174601908746020728RNF141145826111053460410535273
BM674466CLPTM11407194549621045497052PNPO403678174602372646024222
BQ346020LENG81395195496938054969862PNPO391528174602625146026388
BU741757PNPO15384174602527246025641KCNT23777661196441331196441720
AB209036PSMC511056176190518561908877PNPO10525749174602631846031022

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=10)
Stat. for Synonymous SNVs
(# total SNVs=6)
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
chr17:46020698-46020698p.S55S3
chr17:46023710-46023710p.E190K2
chr17:46022936-46022936p.P125P1
chr17:46024062-46024062p.R234W1
chr17:46019090-46019090p.E17K1
chr17:46022984-46023003p.?1
chr17:46024107-46024107p.R249C1
chr17:46019116-46019116p.L25L1
chr17:46023278-46023278p.Y157H1
chr17:46019171-46019171p.D44N1

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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
# sample21 2       1    21 2
# mutation21 2       1    21 2
nonsynonymous SNV21 2       1    11  
synonymous SNV                1  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
chr17:46024107p.L25L1
chr17:46019116p.M96I1
chr17:46022006p.G103W1
chr17:46022025p.G103G1
chr17:46022027p.P125S1
chr17:46022934p.P125P1
chr17:46022936p.Y157H1
chr17:46023278p.Q174H1
chr17:46023331p.E190K1
chr17:46023710p.G208D1

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 PNPO 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 PNPO

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

ANKRD40,C3orf49,CA10,CALCOCO2,CBX1,CDK5RAP3,MRPL10,
KAT7,NFE2L1,PDK2,PIWIL3,PNPO,PRR15L,SLC35B1,
SNX11,SP2,SPAG9,SPOP,TOB1,UBE2Z,UTP18
AP1M2,KDF1,CYB561,ENTPD2,EPN3,JUP,LPAR2,
LSR,MARCKSL1,MIA,MIPEP,PIK3R2,PNPO,PROM2,
PRR19,RAB3D,SERINC2,SEZ6L2,SLC9A1,SPINT1,UBE2Z

AARSD1,ATP5G1,CCDC137,CCDC43,COASY,DBF4B,EFTUD2,
EME1,ERAL1,G6PC3,KAT2A,MKS1,MRPL10,PHB,
PNPO,POLDIP2,SLC25A19,SLC25A39,SMARCD2,SNF8,TUBG1
AGMAT,APEH,C9orf41,CAT,FAAH,FAH,HADH,
HN1L,HSDL2,IMP3,LOC729082,MEST,MLYCD,NPY6R,
PCYT2,PNPO,SAMM50,SHMT1,SLC25A10,TBRG4,UNG
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 PNPO
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
DB00114pyridoxamine 5'-phosphate oxidasenutraceuticalPyridoxal Phosphate
DB03247pyridoxamine 5'-phosphate oxidaseexperimentalRiboflavin Monophosphate
DB03345pyridoxamine 5'-phosphate oxidaseexperimentalBeta-Mercaptoethanol


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Cross referenced IDs for PNPO
* 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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