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 PIP5K1C
Basic gene info.Gene symbolPIP5K1C
Gene namephosphatidylinositol-4-phosphate 5-kinase, type I, gamma
SynonymsLCCS3|PIP5K-GAMMA|PIP5K1-gamma|PIP5Kgamma
CytomapUCSC genome browser: 19p13.3
Genomic locationchr19 :3630178-3700477
Type of geneprotein-coding
RefGenesNM_001195733.1,
NM_001300849.1,NM_012398.2,
Ensembl idENSG00000186111
Descriptiondiphosphoinositide kinasephosphatidylinositol 4-phosphate 5-kinase type-1 gammaptdIns(4)P-5-kinase 1 gammatype I PIP kinase
Modification date20141207
dbXrefs MIM : 606102
HGNC : HGNC
Ensembl : ENSG00000186111
HPRD : 05834
Vega : OTTHUMG00000180870
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_PIP5K1C
BioGPS: 23396
Gene Expression Atlas: ENSG00000186111
The Human Protein Atlas: ENSG00000186111
PathwayNCI Pathway Interaction Database: PIP5K1C
KEGG: PIP5K1C
REACTOME: PIP5K1C
ConsensusPathDB
Pathway Commons: PIP5K1C
MetabolismMetaCyc: PIP5K1C
HUMANCyc: PIP5K1C
RegulationEnsembl's Regulation: ENSG00000186111
miRBase: chr19 :3,630,178-3,700,477
TargetScan: NM_001195733
cisRED: ENSG00000186111
ContextiHOP: PIP5K1C
cancer metabolism search in PubMed: PIP5K1C
UCL Cancer Institute: PIP5K1C
Assigned class in ccmGDBC

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Phenotypic Information for PIP5K1C(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: PIP5K1C
Familial Cancer Database: PIP5K1C
* 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
KEGG_FC_GAMMA_R_MEDIATED_PHAGOCYTOSIS
REACTOME_PHOSPHOLIPID_METABOLISM
REACTOME_PI_METABOLISM
REACTOME_METABOLISM_OF_LIPIDS_AND_LIPOPROTEINS

check002.gifOthers
OMIM
Orphanet
DiseaseKEGG Disease: PIP5K1C
MedGen: PIP5K1C (Human Medical Genetics with Condition)
ClinVar: PIP5K1C
PhenotypeMGI: PIP5K1C (International Mouse Phenotyping Consortium)
PhenomicDB: PIP5K1C

Mutations for PIP5K1C
* 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 PIP5K1C related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
BF739320BCL9L2412111118771585118771681PIP5K1C1181931936337423633817
M90820FKBP38950144558513645603665PIP5K1C95118071936302143631072
BF989347SNX911056158360614158360718PIP5K1C1052691936752923675456
BF873394PIP5K1C13991936920123692098AKAP1394178158616695486167038

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=1

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=3)
Stat. for Synonymous SNVs
(# total SNVs=0)
There's no s-snv.
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
chr19:3653471-3653471p.V246V1
chr19:3653571-3653572p.P213L1
chr19:3661029-3661029p.T135A1
chr19:3633485-3633485p.L652F1
chr19:3643289-3643289p.S534F1
chr19:3645970-3645970p.?1
chr19:3645992-3645992p.T442M1
chr19:3646020-3646020p.E433K1
chr19:3653299-3653299p.R304W1

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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
# sample34 111 3 41 41  3108 8
# mutation34 111 3 41 41  31110 10
nonsynonymous SNV34 101 2 31 41  278 4
synonymous SNV   1  1 1      142 6
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
chr19:3642935p.Y221C,PIP5K1C2
chr19:3653547p.A568T,PIP5K1C2
chr19:3641788p.R551Q,PIP5K1C2
chr19:3656413p.D253H,PIP5K1C1
chr19:3642905p.S117S,PIP5K1C1
chr19:3664847p.P601P,PIP5K1C1
chr19:3644155p.F516F,PIP5K1C1
chr19:3651997p.C511Y,PIP5K1C1
chr19:3638918p.K251T,PIP5K1C1
chr19:3656478p.V109M,PIP5K1C1

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 PIP5K1C 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 PIP5K1C

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

AES,APBA3,BTBD2,CACTIN,TMEM259,DPP9,FZR1,
MED16,MIER2,MLLT1,PIAS4,PIP5K1C,REXO1,RFX1,
SCAMP4,SGTA,SH3GL1,SPPL2B,STK11,UBXN6,ZBTB7A
ABCB8,ALDH16A1,ARHGDIA,CLCN7,CNP,COL18A1,LRP10,
LTBP3,MLLT1,MVP,NCLN,OSBPL5,PIP5K1C,PLCB3,
RNH1,RPS6KA4,PPP6R1,SDF4,SHKBP1,SLC38A10,SLC4A2

AMOTL1,ARHGEF17,CIC,CLIP3,EHD2,FAM129A,FLNA,
HLX,KANK2,CTIF,MAP1A,MAP3K3,MAP7D1,MOB3A,
MYO9B,PIP5K1C,PTRF,SLC12A4,TGFB1I1,TLN1,ZBTB47
ADARB1,AHNAK2,CAND2,COL4A2,CSPG4,DOCK3,EHD2,
FYCO1,GLI2,GNAO1,CTIF,MTSS1L,MYH11,NACAD,
NBEA,PIP5K1C,PRICKLE2,SVIL,TEAD1,TLN1,ZNF853
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 PIP5K1C
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
DB00122phosphatidylinositol-4-phosphate 5-kinase, type I, gammaapproved; nutraceuticalCholine


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Cross referenced IDs for PIP5K1C
* 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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