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 ACPP

Basic gene info.	Gene symbol	ACPP
	Gene name	acid phosphatase, prostate
	Synonyms	5'-NT\|ACP-3\|ACP3
	Cytomap	UCSC genome browser: 3q22.1
	Genomic location	chr3 :132036210-132087146
	Type of gene	protein-coding
	RefGenes	NM_001099.4, NM_001134194.1,NM_001292037.1,
	Ensembl id	ENSG00000014257
	Description	5'-nucleotidaseTMPaseecto-5'-nucleotidaseprostatic acid phosphataseprostatic acid phosphotasethiamine monophosphatase
	Modification date	20141207
dbXrefs	MIM : 171790
	HGNC : HGNC
	Ensembl : ENSG00000014257
	HPRD : 01378
	Vega : OTTHUMG00000159650
Protein	UniProt: P15309 go to UniProt's Cross Reference DB Table
Expression	CleanEX: HS_ACPP
	BioGPS: 55
	Gene Expression Atlas: ENSG00000014257
	The Human Protein Atlas: ENSG00000014257
Pathway	NCI Pathway Interaction Database: ACPP
	KEGG: ACPP
	REACTOME: ACPP
	ConsensusPathDB
	Pathway Commons: ACPP
Metabolism	MetaCyc: ACPP
	HUMANCyc: ACPP
Regulation	Ensembl's Regulation: ENSG00000014257
	miRBase: chr3 :132,036,210-132,087,146
	TargetScan: NM_001099
	cisRED: ENSG00000014257
Context	iHOP: ACPP
	cancer metabolism search in PubMed: ACPP
	UCL Cancer Institute: ACPP
Assigned class in ccmGDB	A - This gene has a literature evidence and it belongs to cancer gene.
References showing role of ACPP in cancer cell metabolism	1. Crisp JL, Savariar EN, Glasgow HL, Ellies LG, Whitney MA, et al. (2014) Dual targeting of integrin alphavbeta3 and matrix metalloproteinase-2 for optical imaging of tumors and chemotherapeutic delivery. Mol Cancer Ther 13: 1514-1525. doi: 10.1158/1535-7163.MCT-13-1067. pmid: 4051287. go to article 2. Olson ES, Aguilera TA, Jiang T, Ellies LG, Nguyen QT, et al. (2009) In vivo characterization of activatable cell penetrating peptides for targeting protease activity in cancer. Integr Biol (Camb) 1: 382-393. doi: 10.1039/b904890a. pmid: 2796841. go to article 3. Bae H, Lim W, Bae SM, Bazer FW, Choi Y, et al. (2014) Avian prostatic acid phosphatase: estrogen regulation in the oviduct and epithelial cell-derived ovarian carcinomas. Biol Reprod 91: 3. doi: 10.1095/biolreprod.114.118893. go to article 4. Whitney M, Crisp JL, Olson ES, Aguilera TA, Gross LA, et al. (2010) Parallel in vivo and in vitro selection using phage display identifies protease-dependent tumor-targeting peptides. J Biol Chem 285: 22532-22541. doi: 10.1074/jbc.M110.138297. pmid: 2903386. go to article 5. Datta K, Hyduke DR, Suman S, Moon BH, Johnson MD, et al. (2012) Exposure to ionizing radiation induced persistent gene expression changes in mouse mammary gland. Radiat Oncol 7: 205. doi: 10.1186/1748-717X-7-205. pmid: 3551737 go to article

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

Cancer Description
Cancer	CGAP: ACPP
	Familial Cancer Database: ACPP

* 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_RIBOFLAVIN_METABOLISM

Others
OMIM	171790; gene.
Orphanet
Disease	KEGG Disease: ACPP
	MedGen: ACPP (Human Medical Genetics with Condition)
	ClinVar: ACPP
Phenotype	MGI: ACPP (International Mouse Phenotyping Consortium)
Phenotype	PhenomicDB: ACPP

Mutations for ACPP

* 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 ACPP 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
BE768768	ACPP	8	233	3	132076886	132077108	PAFAH1B1	232	301	17	2578664	2578733
BQ372756	ACPP	11	261	3	132076858	132077108	PAFAH1B1	260	329	17	2578664	2578733

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=4

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Somatic Mutation Counts per Tissue in COSMIC data

Stat. for Non-Synonymous SNVs (# total SNVs=52)	Stat. for Synonymous SNVs (# total SNVs=12)

Stat. for Deletions (# total SNVs=2)	Stat. for Insertions (# total SNVs=0)
	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
chr3:132047117-132047117	p.R43W	4
chr3:132051046-132051046	p.R105Q	4
chr3:132071589-132071589	p.Q297P	3
chr3:132071617-132071617	p.L306L	2
chr3:132050557-132050557	p.E95K	2
chr3:132051175-132051175	p.L148R	2
chr3:132051042-132051042	p.I104F	2
chr3:132071660-132071660	p.E321K	2
chr3:132051045-132051045	p.R105*	2
chr3:132050515-132050515	p.L81F	2

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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=3

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	6	5		4			2					7	3	1		1	9	2		6
# mutation	5	4		3			2					7	3	1		1	10	3		6
nonsynonymous SNV	4	4		2			1					7		1			7	2		4
synonymous SNV	1			1			1						3			1	3	1		2

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
chr3:132051046	p.R105Q,ACPP	3
chr3:132047117	p.R43W,ACPP	3
chr3:132047150	p.P54T,ACPP	2
chr3:132071617	p.L273L,ACPP	2
chr3:132071660	p.E288K,ACPP	2
chr3:132068846	p.T352I,ACPP	1
chr3:132047123	p.M238T,ACPP	1
chr3:132075647	p.M397I	1
chr3:132056328	p.K87N,ACPP	1
chr3:132071581	p.Q243H,ACPP	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 ACPP 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 ACPP

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


ACPP,ANKRD34B,APOD,ATP13A4,AWAT2,C12orf40,CLU, ENPP7,ETFA,GPR115,IDH1,INHBB,POF1B,RRM2, SCP2,SMPDL3A,SNAR-A13,SV2C,TCL1B,TRIM24,ZNF613	ACPP,AFMID,ALCAM,ALDH3B2,HEXA-AS1,CROT,CYP4Z2P, DHCR24,FMO5,HRASLS2,CERS4,LPCAT3,PON3,PTPLAD1, PXMP4,SLC38A1,SPINK8,STYK1,TMEM45B,TMEM62,TMEM63C

ACPP,AGR2,AGR3,ANG,ASRGL1,HID1,CAPN9, MCU,CDC42EP1,CKAP4,FOXA3,GALNT8,GFI1,MB, MLPH,NEURL1,SGSM3,SPDEF,TC2N,TMED10,TSPAN13	ACPP,C2CD4A,CCL18,CYB5R2,GNA15,GYLTL1B,KCTD14, KDELR3,KYNU,NOD2,PDIA5,PGM3,PRSS22,PVRL4, S100P,SLC17A9,SLC38A5,TCN1,TMEM173,TMEM39A,TSTA3

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 ACPP

Cross-referenced pharmacological DB IDs from Uniprot

DB Category	DB Name	DB's ID and Url link
Chemistry	BindingDB	P15309; -.
Chemistry	ChEMBL	CHEMBL2633; -.
Organism-specific databases	PharmGKB	PA24449; -.
Organism-specific databases	CTD	55; -.

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
DB02944	acid phosphatase, prostate	experimental	Alpha-D-Mannose
DB03390	acid phosphatase, prostate	experimental	N-Propyl-Tartramic Acid
DB03577	acid phosphatase, prostate	experimental	Alpha-Benzyl-Aminobenzyl-Phosphonic Acid

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Cross referenced IDs for ACPP

* 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