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 PPAP2C
Basic gene info.Gene symbolPPAP2C
Gene namephosphatidic acid phosphatase type 2C
SynonymsLPP2|PAP-2c|PAP2-g
CytomapUCSC genome browser: 19p13
Genomic locationchr19 :281043-291169
Type of geneprotein-coding
RefGenesNM_003712.3,
NM_177526.2,NM_177543.2,
Ensembl idENSG00000141934
DescriptionPAP2-gammaPAP2clipid phosphate phosphohydrolase 2phosphatidate phosphohydrolase type 2cphosphatidic acid phosphatase 2cphosphatidic acid phosphohydrolase type 2ctype-2 phosphatidic acid phosphatase-gamma
Modification date20141207
dbXrefs MIM : 607126
HGNC : HGNC
Ensembl : ENSG00000141934
HPRD : 06180
Vega : OTTHUMG00000180530
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_PPAP2C
BioGPS: 8612
Gene Expression Atlas: ENSG00000141934
The Human Protein Atlas: ENSG00000141934
PathwayNCI Pathway Interaction Database: PPAP2C
KEGG: PPAP2C
REACTOME: PPAP2C
ConsensusPathDB
Pathway Commons: PPAP2C
MetabolismMetaCyc: PPAP2C
HUMANCyc: PPAP2C
RegulationEnsembl's Regulation: ENSG00000141934
miRBase: chr19 :281,043-291,169
TargetScan: NM_003712
cisRED: ENSG00000141934
ContextiHOP: PPAP2C
cancer metabolism search in PubMed: PPAP2C
UCL Cancer Institute: PPAP2C
Assigned class in ccmGDBC

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Phenotypic Information for PPAP2C(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: PPAP2C
Familial Cancer Database: PPAP2C
* 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_GLYCEROLIPID_METABOLISM
KEGG_GLYCEROPHOSPHOLIPID_METABOLISM
KEGG_SPHINGOLIPID_METABOLISM
KEGG_FC_GAMMA_R_MEDIATED_PHAGOCYTOSIS
REACTOME_PHOSPHOLIPID_METABOLISM
REACTOME_SPHINGOLIPID_METABOLISM
REACTOME_METABOLISM_OF_LIPIDS_AND_LIPOPROTEINS

check002.gifOthers
OMIM
Orphanet
DiseaseKEGG Disease: PPAP2C
MedGen: PPAP2C (Human Medical Genetics with Condition)
ClinVar: PPAP2C
PhenotypeMGI: PPAP2C (International Mouse Phenotyping Consortium)
PhenomicDB: PPAP2C

Mutations for PPAP2C
* 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 PPAP2C related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a

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 # sample1                
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=3

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=20)
Stat. for Synonymous SNVs
(# total SNVs=9)
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
chr19:288137-288137p.N50N3
chr19:288155-288155p.A44A2
chr19:287698-287698p.S107S2
chr19:288062-288062p.H75H2
chr19:282311-282311p.?2
chr19:282753-282753p.A201V2
chr19:288132-288132p.P52L2
chr19:282783-282783p.S191F1
chr19:287668-287668p.Y117Y1
chr19:282216-282216p.Y233C1

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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
# sample12 41   2  2    84 3
# mutation12 31   2  2    95 3
nonsynonymous SNV12 1    2  1    65 1
synonymous SNV   21      1    3  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
chr19:288137p.N29N,PPAP2C3
chr19:288132p.P31L,PPAP2C2
chr19:287668p.A185T,PPAP2C1
chr19:291319p.L13L1
chr19:282291p.R151M,PPAP2C1
chr19:287697p.F7F1
chr19:282294p.C150R,PPAP2C1
chr19:287703p.V6V1
chr19:282298p.C140Y,PPAP2C1
chr19:288022p.V130I,PPAP2C1

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 PPAP2C 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 PPAP2C

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

BSG,R3HDM4,CDC34,DAZAP1,KLF16,LPAR2,LSM7,
MIER2,NCLN,PLEKHJ1,POLRMT,PPAP2C,RNF126,RTKN,
SF3A2,SGTA,SLC39A3,STAP2,TCF3,TIMM13,WDR18
C10orf35,SYNE4,CBLC,ELMO3,KRTCAP3,LOC92659,LPAR2,
MAGEF1,PKP3,POLR1C,PPAP2C,PRKCZ,PRRG2,PRSS8,
RAB25,RHOV,RTKN,SPINT1,STAP2,SYTL1,TMEM125

ADAP1,ADAT3,C16orf13,C19orf24,C19orf25,KDF1,CD320,
UBALD2,FAM195A,HIGD2A,MFSD10,MGST2,NDUFS7,NTHL1,
PPAP2C,RAD23A,SIRT6,STAP2,TECR,TIMM13,TMEM125
ACADS,ACSF3,AP1M2,KDF1,CBLC,CYB561A3,DHRS11,
DOLPP1,ESPN,ESRRA,LPCAT3,MGAT4B,MPST,NAPRT,
PPAP2C,PRKCZ,RAB20,RPS6KA1,SPHK2,TMEM125,TMUB1
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 PPAP2C


There's no related Drug.
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Cross referenced IDs for PPAP2C
* 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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