Cancer Cell Metabolism Database ~~ Bioinformatics and Systems Medicine Laboratory ~~

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 symbol	PIP5K1C
	Gene name	phosphatidylinositol-4-phosphate 5-kinase, type I, gamma
	Synonyms	LCCS3\|PIP5K-GAMMA\|PIP5K1-gamma\|PIP5Kgamma
	Cytomap	UCSC genome browser: 19p13.3
	Genomic location	chr19 :3630178-3700477
	Type of gene	protein-coding
	RefGenes	NM_001195733.1, NM_001300849.1,NM_012398.2,
	Ensembl id	ENSG00000186111
	Description	diphosphoinositide kinasephosphatidylinositol 4-phosphate 5-kinase type-1 gammaptdIns(4)P-5-kinase 1 gammatype I PIP kinase
	Modification date	20141207
dbXrefs	MIM : 606102
	HGNC : HGNC
	Ensembl : ENSG00000186111
	HPRD : 05834
	Vega : OTTHUMG00000180870
Protein	UniProt: go to UniProt's Cross Reference DB Table
Expression	CleanEX: HS_PIP5K1C
	BioGPS: 23396
	Gene Expression Atlas: ENSG00000186111
	The Human Protein Atlas: ENSG00000186111
Pathway	NCI Pathway Interaction Database: PIP5K1C
	KEGG: PIP5K1C
	REACTOME: PIP5K1C
	ConsensusPathDB
	Pathway Commons: PIP5K1C
Metabolism	MetaCyc: PIP5K1C
	HUMANCyc: PIP5K1C
Regulation	Ensembl's Regulation: ENSG00000186111
	miRBase: chr19 :3,630,178-3,700,477
	TargetScan: NM_001195733
	cisRED: ENSG00000186111
Context	iHOP: PIP5K1C
	cancer metabolism search in PubMed: PIP5K1C
	UCL Cancer Institute: PIP5K1C
Assigned class in ccmGDB	C

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Phenotypic Information for PIP5K1C(metabolism pathway, cancer, disease, phenome)

Cancer 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/

Metabolic Pathway Description
KEGG_INOSITOL_PHOSPHATE_METABOLISM KEGG_FC_GAMMA_R_MEDIATED_PHAGOCYTOSIS REACTOME_PHOSPHOLIPID_METABOLISM REACTOME_PI_METABOLISM REACTOME_METABOLISM_OF_LIPIDS_AND_LIPOPROTEINS

Others
OMIM
Orphanet
Disease	KEGG Disease: PIP5K1C
	MedGen: PIP5K1C (Human Medical Genetics with Condition)
	ClinVar: PIP5K1C
Phenotype	MGI: PIP5K1C (International Mouse Phenotyping Consortium)
Phenotype	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.

Structural Variants in COSMIC : go to COSMIC mutation histogram

- Statistics for Tissue and Mutation type

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- 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.

Sample

Symbol_a

Chr_a

Start_a

End_a

Symbol_b

Chr_b

Start_b

End_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)

Related fusion transcripts : go to Chitars2.0

* From mRNA Sanger sequences, Chitars2.0 arranged chimeric transcripts. This table shows PIP5K1C related fusion information.

ID	Head Gene						Tail Gene
Accession	Gene_a	qStart_a	qEnd_a	Chromosome_a	tStart_a	tEnd_a	Gene_a	qStart_a	qEnd_a	Chromosome_a	tStart_a	tEnd_a
BF739320	BCL9L	24	121	11	118771585	118771681	PIP5K1C	118	193	19	3633742	3633817
M90820	FKBP3	8	950	14	45585136	45603665	PIP5K1C	951	1807	19	3630214	3631072
BF989347	SNX9	1	105	6	158360614	158360718	PIP5K1C	105	269	19	3675292	3675456
BF873394	PIP5K1C	13	99	19	3692012	3692098	AKAP13	94	178	15	86166954	86167038

Other DBs for Structural Variants

Structural Variants in Ensembl: go to Ensembl Structural variation

Structural Variants in dbVar: go to dbVar

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Copy Number Variations in COSMIC : go to COSMIC mutation CNV/Expr

Mutation type/ Tissue ID

brca

cns

cerv

endome

haematopo

kidn

Lintest

liver

lung

ovary

pancre

prost

skin

stoma

thyro

urina

Total # sample

GAIN (# sample)

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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SNV 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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Somatic 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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Top 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 position	Mutation(aa)	Unique sampleID count
chr19:3645992-3645992	p.T442M	1
chr19:3646020-3646020	p.E433K	1
chr19:3653299-3653299	p.R304W	1
chr19:3653471-3653471	p.V246V	1
chr19:3653571-3653572	p.P213L	1
chr19:3661029-3661029	p.T135A	1
chr19:3633485-3633485	p.L652F	1
chr19:3643289-3643289	p.S534F	1
chr19:3645970-3645970	p.?	1

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SNV 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 ID	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20
# sample	3	4		11	1		3		4	1		4	1			3	10	8		8
# mutation	3	4		11	1		3		4	1		4	1			3	11	10		10
nonsynonymous SNV	3	4		10	1		2		3	1		4	1			2	7	8		4
synonymous SNV				1			1		1							1	4	2		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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Top 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 Position	Mutation(aa)	Unique sampleID count
chr19:3641788	p.A568T,PIP5K1C	2
chr19:3653547	p.Y221C,PIP5K1C	2
chr19:3642935	p.R551Q,PIP5K1C	2
chr19:3643342	p.E644D	1
chr19:3661081	p.S534F,PIP5K1C	1
chr19:3633494	p.A352A,PIP5K1C	1
chr19:3651850	p.S175P,PIP5K1C	1
chr19:3643358	p.A633T,PIP5K1C	1
chr19:3661894	p.S530Y,PIP5K1C	1
chr19:3633507	p.E332K,PIP5K1C	1

Other 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

Copy 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

Gene 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.

Differential 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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CNV 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

Co-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

Co-Expressed gene's Protein-protein interaction Network Plot

: Open all plots for all cancer types

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Interacting 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

Cross-referenced pharmacological DB IDs from Uniprot

DB Category

DB Name

DB's ID and Url link

Drug-Gene Interaction Network

* Gene Centered Interaction Network.

* Drug Centered Interaction Network.

DrugBank ID	Target Name	Drug Groups	Generic Name	Drug Centered Network	Drug Structure
DB00122	phosphatidylinositol-4-phosphate 5-kinase, type I, gamma	approved; nutraceutical	Choline

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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