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 INPP5A
Basic gene info.Gene symbolINPP5A
Gene nameinositol polyphosphate-5-phosphatase, 40kDa
Synonyms5PTASE
CytomapUCSC genome browser: 10q26.3
Genomic locationchr10 :134351352-134596984
Type of geneprotein-coding
RefGenesNM_005539.3,
Ensembl idENSG00000068383
Description43 kDa inositol polyphosphate 5-phophataseCTCL tumor antigen HD-CL-02InsP3 5-phosphataseinositol polyphosphate-5-phosphatase, 40kDinositol trisphosphate-5-phosphatase, 40kDtype I inositol 1,4,5-trisphosphate 5-phosphatasetype I inositol-1,4,5-trisph
Modification date20141207
dbXrefs MIM : 600106
HGNC : HGNC
Ensembl : ENSG00000068383
HPRD : 02521
Vega : OTTHUMG00000019293
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_INPP5A
BioGPS: 3632
Gene Expression Atlas: ENSG00000068383
The Human Protein Atlas: ENSG00000068383
PathwayNCI Pathway Interaction Database: INPP5A
KEGG: INPP5A
REACTOME: INPP5A
ConsensusPathDB
Pathway Commons: INPP5A
MetabolismMetaCyc: INPP5A
HUMANCyc: INPP5A
RegulationEnsembl's Regulation: ENSG00000068383
miRBase: chr10 :134,351,352-134,596,984
TargetScan: NM_005539
cisRED: ENSG00000068383
ContextiHOP: INPP5A
cancer metabolism search in PubMed: INPP5A
UCL Cancer Institute: INPP5A
Assigned class in ccmGDBC

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Phenotypic Information for INPP5A(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: INPP5A
Familial Cancer Database: INPP5A
* 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_INOSITOL_PHOSPHATE_METABOLISM

check002.gifOthers
OMIM
Orphanet
DiseaseKEGG Disease: INPP5A
MedGen: INPP5A (Human Medical Genetics with Condition)
ClinVar: INPP5A
PhenotypeMGI: INPP5A (International Mouse Phenotyping Consortium)
PhenomicDB: INPP5A

Mutations for INPP5A
* 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
ovaryINPP5Achr10134490772134490792INPP5Achr10134490392134490412
ovaryINPP5Achr10134493718134493738INPP5Achr10134518024134518044
ovaryINPP5Achr10134587778134587798chr10134857475134857495
pancreasINPP5Achr10134596766134596786SLC24A3chr201937106319371083
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 INPP5A related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
BF368694PAPPA1859119126716119126800INPP5A7949110134410696134411106

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      
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=27)
Stat. for Synonymous SNVs
(# total SNVs=3)
Stat. for Deletions
(# total SNVs=1)
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
chr10:134563082-134563082p.K265T3
chr10:134463965-134463965p.R88*2
chr10:134459368-134459368p.?2
chr10:134523928-134523928p.I205I2
chr10:134463923-134463923p.E74*2
chr10:134563295-134563295p.K283N1
chr10:134523908-134523908p.P199T1
chr10:134591246-134591246p.R350H1
chr10:134563050-134563050p.T254T1
chr10:134463968-134463968p.V89F1

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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
# sample41 21 2 1  34   86 3
# mutation41 21 2 1  34   86 4
nonsynonymous SNV31 21   1  34   44 3
synonymous SNV1     2         42 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
chr10:134521849p.G204E1
chr10:134563053p.D320H1
chr10:134579348p.R221Q1
chr10:134523866p.I321V1
chr10:134563057p.R236W1
chr10:134591194p.P325P1
chr10:134523875p.V242V1
chr10:134563059p.A333T1
chr10:134459401p.M49I1
chr10:134591246p.T245T1

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 INPP5A 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 INPP5A

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

ALDH18A1,ALDH1A2,ECHS1,GLRX3,HK1,INPP5A,LRRC27,
PAOX,PCBD1,PIP5K1B,PPP2R2D,PWWP2B,SAR1A,SPANXD,
SUPV3L1,TCTN3,TSPAN15,TUBGCP2,VPS26A,ZMIZ1,ZNF511
ACAT1,CASQ2,EPM2A,FEZ2,HADHB,HSPB6,INPP5A,
LOC401093,NNT,OGDH,OPTN,PARK2,PGM1,PHYH,
PKNOX2,PPP3CB,RXRG,SGCG,SNTA1,SOX6,ZAK

ACTG2,CNN1,CSRP1,DACT3,DES,FLNC,FXYD1,
GPM6A,HSPB6,INPP5A,LDB3,LOC401093,MYH11,PDZRN4,
PRIMA1,PSD,PYGM,RBPMS2,SGCA,SYNPO2,TCEAL2
ACTG2,ATP1A2,BVES,CAMK2G,DACT3,DES,DMPK,
INPP5A,KY,LDB3,MOB2,MYOM1,NTSR1,PCP4L1,
PDLIM7,PDZD4,PNCK,PYGM,SLC2A4,SLC8A2,SMTN
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 INPP5A


There's no related Drug.
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Cross referenced IDs for INPP5A
* 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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