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 PIP4K2C
Basic gene info.Gene symbolPIP4K2C
Gene namephosphatidylinositol-5-phosphate 4-kinase, type II, gamma
SynonymsPIP5K2C
CytomapUCSC genome browser: 12q13.3
Genomic locationchr12 :57984941-57997211
Type of geneprotein-coding
RefGenesNM_001146258.1,
NM_001146259.1,NM_001146260.1,NM_024779.4,
Ensembl idENSG00000166908
DescriptionPI(5)P 4-kinase type II gammaPIP4KII-gammaphosphatidylinositol 4-phosphate 5-kinasephosphatidylinositol 5-phosphate 4-kinase type II gammaphosphatidylinositol 5-phosphate 4-kinase type-2 gammaphosphatidylinositol-4-phosphate 5-kinase, type II, gamma
Modification date20141207
dbXrefs HGNC : HGNC
Ensembl : ENSG00000166908
HPRD : 15138
Vega : OTTHUMG00000170144
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_PIP4K2C
BioGPS: 79837
Gene Expression Atlas: ENSG00000166908
The Human Protein Atlas: ENSG00000166908
PathwayNCI Pathway Interaction Database: PIP4K2C
KEGG: PIP4K2C
REACTOME: PIP4K2C
ConsensusPathDB
Pathway Commons: PIP4K2C
MetabolismMetaCyc: PIP4K2C
HUMANCyc: PIP4K2C
RegulationEnsembl's Regulation: ENSG00000166908
miRBase: chr12 :57,984,941-57,997,211
TargetScan: NM_001146258
cisRED: ENSG00000166908
ContextiHOP: PIP4K2C
cancer metabolism search in PubMed: PIP4K2C
UCL Cancer Institute: PIP4K2C
Assigned class in ccmGDBC

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Phenotypic Information for PIP4K2C(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: PIP4K2C
Familial Cancer Database: PIP4K2C
* 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: PIP4K2C
MedGen: PIP4K2C (Human Medical Genetics with Condition)
ClinVar: PIP4K2C
PhenotypeMGI: PIP4K2C (International Mouse Phenotyping Consortium)
PhenomicDB: PIP4K2C

Mutations for PIP4K2C
* 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
There's no structural variation information in COSMIC data for this gene.

check002.gifRelated fusion transcripts : go to Chitars2.0
* From mRNA Sanger sequences, Chitars2.0 arranged chimeric transcripts. This table shows PIP4K2C related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
AW606546PIP4K2C7194125799417057994730MIEN1191428173788550837885744

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=2

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=37)
Stat. for Synonymous SNVs
(# total SNVs=9)
Stat. for Deletions
(# total SNVs=3)
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
chr12:57988969-57988969p.L111L2
chr12:57988971-57988971p.R112H2
chr12:57994645-57994645p.D289Y2
chr12:57992945-57992945p.R204H2
chr12:57994176-57994176p.E257K2
chr12:57987869-57987869p.S79N2
chr12:57994708-57994708p.D310Y1
chr12:57989795-57989795p.N165S1
chr12:57993195-57993195p.S225P1
chr12:57985200-57985200p.A43E1

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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
# sample53143 2 3  73   5312
# mutation53134 2 3  93   6313
nonsynonymous SNV33134 1 1  42   2113
synonymous SNV2     1 2  51   42  
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
chr12:57988951p.N147K,PIP4K2C2
chr12:57992919p.R156H,PIP4K2C2
chr12:57992945p.P105P,PIP4K2C2
chr12:57992965p.Q171Q,PIP4K2C1
chr12:57994618p.D232N,PIP4K2C1
chr12:57987825p.Q64H,PIP4K2C1
chr12:57989742p.F137Y,PIP4K2C1
chr12:57992982p.D241Y,PIP4K2C1
chr12:57994645p.P68L,PIP4K2C1
chr12:57987836p.R142R,PIP4K2C1

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 PIP4K2C 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 PIP4K2C

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

ARF3,CCDC172,C12orf66,CDK4,CTDSP2,DCTN2,DNAJC14,
METTL21B,LARP4,LOC285954,MARCH9,MARS,METTL1,NECAP1,
OR4D6,OR5A1,OS9,PIP4K2C,RAB5B,TSFM,TSPAN31
C11orf80,TMEM241,KDF1,C3orf14,CDH1,CDS1,DLG3,
ESRP1,ESRP2,FAM174B,GRHL2,HDAC1,HHAT,ILDR1,
MAP7,MARVELD2,PIP4K2C,PTPLAD1,SAMD12,SEC23B,STX3

ARF3,CDA,CDKN2B,DHRS9,DUSP5,EMP1,EPHB6,
GJB4,ITGA3,LAMA3,LAMB3,LRRC8A,MFSD5,MMP28,
OASL,PIP4K2C,PXN,RSAD2,TGFA,TICAM1,TMEM127
CAB39,CEACAM5,CGN,CLCN2,CTNND1,ELF4,ABHD17C,
GCNT3,GNA13,KIF16B,LRRC1,MARK2,NR3C2,OSBPL2,
PDCD6IP,PIP4K2C,PIP5K1B,RBM47,SPATS2L,STX3,WIPF2
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 PIP4K2C


There's no related Drug.
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Cross referenced IDs for PIP4K2C
* 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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