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 PTGIS
Basic gene info.Gene symbolPTGIS
Gene nameprostaglandin I2 (prostacyclin) synthase
SynonymsCYP8|CYP8A1|PGIS|PTGI
CytomapUCSC genome browser: 20q13.13
Genomic locationchr20 :48120410-48184707
Type of geneprotein-coding
RefGenesNM_000961.3,
Ensembl idENSG00000124212
Descriptioncytochrome P450, family 8, subfamily A, polypeptide 1prostacyclin synthaseprostaglandin I2 synthase
Modification date20141207
dbXrefs MIM : 601699
HGNC : HGNC
Ensembl : ENSG00000124212
HPRD : 09046
Vega : OTTHUMG00000033077
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_PTGIS
BioGPS: 5740
Gene Expression Atlas: ENSG00000124212
The Human Protein Atlas: ENSG00000124212
PathwayNCI Pathway Interaction Database: PTGIS
KEGG: PTGIS
REACTOME: PTGIS
ConsensusPathDB
Pathway Commons: PTGIS
MetabolismMetaCyc: PTGIS
HUMANCyc: PTGIS
RegulationEnsembl's Regulation: ENSG00000124212
miRBase: chr20 :48,120,410-48,184,707
TargetScan: NM_000961
cisRED: ENSG00000124212
ContextiHOP: PTGIS
cancer metabolism search in PubMed: PTGIS
UCL Cancer Institute: PTGIS
Assigned class in ccmGDBC

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

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

Mutations for PTGIS
* 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
There's no intra-chromosomal structural variation.
SampleSymbol_aChr_aStart_aEnd_aSymbol_bChr_bStart_bEnd_b
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 PTGIS 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 # sample3       1     3  
GAIN (# sample)3       1     3  
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=4

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=53)
Stat. for Synonymous SNVs
(# total SNVs=11)
Stat. for Deletions
(# total SNVs=0)
Stat. for Insertions
(# total SNVs=1)
There's no deleted 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
chr20:48129793-48129793p.V344M4
chr20:48129705-48129705p.R373Q3
chr20:48129637-48129637p.E396K2
chr20:48140669-48140669p.L261L2
chr20:48156225-48156225p.A185A2
chr20:48129710-48129710p.D371D2
chr20:48140727-48140727p.L241L2
chr20:48130909-48130909p.F293L2
chr20:48140776-48140776p.G225V2
chr20:48127613-48127613p.G437E2

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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
# sample23 81 3 1  522  125 4
# mutation23 81 3 1  522  135 7
nonsynonymous SNV12 61 3    512  104 6
synonymous SNV11 2    1   1   31 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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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
chr20:48129705p.R373Q3
chr20:48140776p.G225V2
chr20:48156158p.R208C2
chr20:48129765p.V492M1
chr20:48166673p.D336N1
chr20:48130909p.R208H1
chr20:48124559p.E489D1
chr20:48156225p.L335P1
chr20:48130782p.M486T1
chr20:48130929p.S325S1

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 PTGIS 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 PTGIS

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

ACSL4,ANGPTL1,ANK2,ARHGAP31,CCDC80,CNRIP1,CORO2B,
FAT4,FNDC4,IGF1,KCTD12,LIX1L,LRP1,LRRN4CL,
LYVE1,MRGPRF,PTGIS,RGL1,RHOJ,TNXB,ZEB2
ABI3BP,AHNAK2,AXL,C1QTNF2,CILP,DNM1,F10,
GFPT2,GPR133,LMX1A,MAP1A,MFAP4,NT5E,PODN,
PROCR,PTGIS,SCARA5,SSC5D,TIMP2,TMEM35,XG

AOC3,BHMT2,BOC,CCDC80,CDO1,CPXM2,CRYAB,
EFEMP1,FBLN5,HTR2B,ITGA7,LHFP,MAP1B,PTGER3,
PTGIS,SLIT2,SLIT3,SYNPO,TMEM130,TNS1,ZFHX4
A4GALT,ABCA3,ANK2,BOC,CHST3,COL8A1,DBN1,
EBF3,FBN1,FGFR1,FSTL1,GPR133,HSPA12A,MAP1B,
NAP1L3,NLGN2,PALM,PTGIS,SYT11,TMTC1,ZBTB47
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 PTGIS
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
DB00812prostaglandin I2 (prostacyclin) synthaseapprovedPhenylbutazone
DB01240prostaglandin I2 (prostacyclin) synthaseapprovedEpoprostenol
DB08675prostaglandin I2 (prostacyclin) synthaseexperimental(6E)-7-{6-[(1E)-OCT-1-ENYL]-2,3-DIAZABICYCLO[2.2.1]HEPT-2-EN-5-YL}HEPT-6-ENOIC ACID
DB00564prostaglandin I2 (prostacyclin) synthaseapproved; investigationalCarbamazepine
DB00252prostaglandin I2 (prostacyclin) synthaseapprovedPhenytoin
DB00917prostaglandin I2 (prostacyclin) synthaseapprovedDinoprostone
DB00482prostaglandin I2 (prostacyclin) synthaseapproved; investigationalCelecoxib


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Cross referenced IDs for PTGIS
* 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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