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 ACPP
Basic gene info.Gene symbolACPP
Gene nameacid phosphatase, prostate
Synonyms5'-NT|ACP-3|ACP3
CytomapUCSC genome browser: 3q22.1
Genomic locationchr3 :132036210-132087146
Type of geneprotein-coding
RefGenesNM_001099.4,
NM_001134194.1,NM_001292037.1,
Ensembl idENSG00000014257
Description5'-nucleotidaseTMPaseecto-5'-nucleotidaseprostatic acid phosphataseprostatic acid phosphotasethiamine monophosphatase
Modification date20141207
dbXrefs MIM : 171790
HGNC : HGNC
Ensembl : ENSG00000014257
HPRD : 01378
Vega : OTTHUMG00000159650
ProteinUniProt: P15309
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_ACPP
BioGPS: 55
Gene Expression Atlas: ENSG00000014257
The Human Protein Atlas: ENSG00000014257
PathwayNCI Pathway Interaction Database: ACPP
KEGG: ACPP
REACTOME: ACPP
ConsensusPathDB
Pathway Commons: ACPP
MetabolismMetaCyc: ACPP
HUMANCyc: ACPP
RegulationEnsembl's Regulation: ENSG00000014257
miRBase: chr3 :132,036,210-132,087,146
TargetScan: NM_001099
cisRED: ENSG00000014257
ContextiHOP: ACPP
cancer metabolism search in PubMed: ACPP
UCL Cancer Institute: ACPP
Assigned class in ccmGDBA - This gene has a literature evidence and it belongs to cancer gene.
References showing role of ACPP in cancer cell metabolism1. 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)
check002.gifCancer 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/

check002.gifMetabolic Pathway Description
KEGG_RIBOFLAVIN_METABOLISM

check002.gifOthers
OMIM 171790; gene.
Orphanet
DiseaseKEGG Disease: ACPP
MedGen: ACPP (Human Medical Genetics with Condition)
ClinVar: ACPP
PhenotypeMGI: ACPP (International Mouse Phenotyping Consortium)
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.

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 ACPP related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
BE768768ACPP82333132076886132077108PAFAH1B12323011725786642578733
BQ372756ACPP112613132076858132077108PAFAH1B12603291725786642578733

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            2    
GAIN (# sample)            1    
LOSS (# sample)            1    
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=4

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check002.gifSomatic 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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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
chr3:132051046-132051046p.R105Q4
chr3:132047117-132047117p.R43W4
chr3:132071589-132071589p.Q297P3
chr3:132050515-132050515p.L81F2
chr3:132075554-132075554p.Y331Y2
chr3:132036383-132036383p.R28L2
chr3:132071616-132071616p.L306H2
chr3:132063796-132063796p.S225F2
chr3:132071617-132071617p.L306L2
chr3:132050557-132050557p.E95K2

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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=3

Point Mutation/ Tissue ID1234567891011121314151617181920
# sample65 4  2    731 192 6
# mutation54 3  2    731 1103 6
nonsynonymous SNV44 2  1    7 1  72 4
synonymous SNV1  1  1     3  131 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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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
chr3:132051046p.R105Q,ACPP3
chr3:132047117p.R43W,ACPP3
chr3:132047150p.P54T,ACPP2
chr3:132071617p.L273L,ACPP2
chr3:132071660p.E288K,ACPP2
chr3:132047130p.M238T,ACPP1
chr3:132075676p.T352I,ACPP1
chr3:132056351p.M397I1
chr3:132071590p.K87N,ACPP1
chr3:132075715p.Q243H,ACPP1

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 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

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

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
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 ACPP
check002.gifCross-referenced pharmacological DB IDs from Uniprot
DB CategoryDB NameDB's ID and Url link
ChemistryBindingDB P15309; -.
ChemistryChEMBL CHEMBL2633; -.
Organism-specific databasesPharmGKB PA24449; -.
Organism-specific databasesCTD 55; -.

check002.gifDrug-Gene Interaction Network
* Gene Centered Interaction Network.
* Drug Centered Interaction Network.
DrugBank IDTarget NameDrug GroupsGeneric NameDrug Centered NetworkDrug Structure
DB02944acid phosphatase, prostateexperimentalAlpha-D-Mannose
DB03390acid phosphatase, prostateexperimentalN-Propyl-Tartramic Acid
DB03577acid phosphatase, prostateexperimentalAlpha-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



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