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 PI4KB
Basic gene info.Gene symbolPI4KB
Gene namephosphatidylinositol 4-kinase, catalytic, beta
SynonymsNPIK|PI4K-BETA|PI4K92|PI4KBETA|PI4KIIIBETA|PIK4CB
CytomapUCSC genome browser: 1q21
Genomic locationchr1 :151264272-151300133
Type of geneprotein-coding
RefGenesNM_001198773.1,
NM_001198774.1,NM_001198775.1,NM_002651.2,
Ensembl idENSG00000143393
DescriptionPtdIns 4-kinase betaphosphatidylinositol 4-kinase betaphosphatidylinositol 4-kinase, wortmannin-sensitivetype III phosphatidylinositol 4-kinase beta
Modification date20141207
dbXrefs MIM : 602758
HGNC : HGNC
Ensembl : ENSG00000143393
HPRD : 11805
Vega : OTTHUMG00000012348
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_PI4KB
BioGPS: 5298
Gene Expression Atlas: ENSG00000143393
The Human Protein Atlas: ENSG00000143393
PathwayNCI Pathway Interaction Database: PI4KB
KEGG: PI4KB
REACTOME: PI4KB
ConsensusPathDB
Pathway Commons: PI4KB
MetabolismMetaCyc: PI4KB
HUMANCyc: PI4KB
RegulationEnsembl's Regulation: ENSG00000143393
miRBase: chr1 :151,264,272-151,300,133
TargetScan: NM_001198773
cisRED: ENSG00000143393
ContextiHOP: PI4KB
cancer metabolism search in PubMed: PI4KB
UCL Cancer Institute: PI4KB
Assigned class in ccmGDBC

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Phenotypic Information for PI4KB(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: PI4KB
Familial Cancer Database: PI4KB
* 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
REACTOME_PHOSPHOLIPID_METABOLISM
REACTOME_PI_METABOLISM
REACTOME_METABOLISM_OF_LIPIDS_AND_LIPOPROTEINS

check002.gifOthers
OMIM
Orphanet
DiseaseKEGG Disease: PI4KB
MedGen: PI4KB (Human Medical Genetics with Condition)
ClinVar: PI4KB
PhenotypeMGI: PI4KB (International Mouse Phenotyping Consortium)
PhenomicDB: PI4KB

Mutations for PI4KB
* 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
ovaryPI4KBchr1151277597151277617PI4KBchr1151271911151271931
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 PI4KB related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
AW889702FARS2129148656229195622938PI4KB1382811151274372151274741

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=5

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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=19)
Stat. for Deletions
(# total SNVs=3)
Stat. for Insertions
(# total SNVs=1)

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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
chr1:151274743-151274743p.P530S5
chr1:151266606-151266606p.G731G2
chr1:151280277-151280277p.P331S2
chr1:151271347-151271347p.R663H2
chr1:151288192-151288192p.S268P2
chr1:151280086-151280086p.P394P2
chr1:151265387-151265387p.R810W2
chr1:151265399-151265399p.D806N2
chr1:151288881-151288881p.G38E1
chr1:151274754-151274754p.L526Q1

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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
# sample32 72   4  525  56112
# mutation32 72   4  525  56113
nonsynonymous SNV31 32   3  515  4419
synonymous SNV 1 4    1   1   12 4
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
chr1:151271347p.R466W,PI4KB2
chr1:151265387p.D462N,PI4KB2
chr1:151265399p.G387G,PI4KB2
chr1:151266606p.R319H,PI4KB2
chr1:151280270p.L269R,PI4KB1
chr1:151288396p.N28S,PI4KB1
chr1:151276082p.Y147C,PI4KB1
chr1:151288881p.R258Q,PI4KB1
chr1:151282708p.L10V,PI4KB1
chr1:151271348p.S146L,PI4KB1

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 PI4KB 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 PI4KB

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

APH1A,CDC42SE1,CHD1L,CRTC2,LYSMD1,MRPL9,PI4KB,
PIP5K1A,PIPSL,POGZ,PRCC,PRUNE,PSMB4,PSMD4,
SCNM1,SETDB1,TARS2,TDRKH,VPS45,VPS72,ZNF687
ATXN7L3,BAP1,BRD9,CIZ1,CRTC1,EXOC7,STRIP1,
FBF1,HDAC6,KLC4,MBD1,PI4KB,POFUT2,PPOX,
RANBP3,RXRB,SKIV2L,SMG5,TSC2,TYK2,ZC3H7B

ARHGEF11,CRTC2,DCAF8,DEDD,GABPB2,GON4L,INTS3,
METTL13,PI4KB,POGK,PRCC,RPRD2,SETDB1,SH3BP5L,
SNAP47,STX6,TARS2,UBE2Q1,UBQLN4,YY1AP1,ZNF687
PPP1R32,NOP14-AS1,EXOC3,HERC2P4,IP6K1,MAP2K7,MBD1,
MTA1,MXD4,PI4KB,SCX,TBC1D17,TP53TG3B,UBOX5,
ULK1,ZBTB45,ZNF205,ZNF500,ZNF517,ZNF689,ZNF843
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 PI4KB


There's no related Drug.
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Cross referenced IDs for PI4KB
* 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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