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 PIGF
Basic gene info.Gene symbolPIGF
Gene namephosphatidylinositol glycan anchor biosynthesis, class F
Synonyms-
CytomapUCSC genome browser: 2p21-p16
Genomic locationchr2 :46808412-46844251
Type of geneprotein-coding
RefGenesNM_002643.3,
NM_173074.2,
Ensembl idENSG00000151665
DescriptionGPI11 homologPIG-Fphosphatidylinositol-glycan biosynthesis class F protein
Modification date20141207
dbXrefs MIM : 600153
HGNC : HGNC
Ensembl : ENSG00000151665
HPRD : 02539
Vega : OTTHUMG00000128816
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_PIGF
BioGPS: 5281
Gene Expression Atlas: ENSG00000151665
The Human Protein Atlas: ENSG00000151665
PathwayNCI Pathway Interaction Database: PIGF
KEGG: PIGF
REACTOME: PIGF
ConsensusPathDB
Pathway Commons: PIGF
MetabolismMetaCyc: PIGF
HUMANCyc: PIGF
RegulationEnsembl's Regulation: ENSG00000151665
miRBase: chr2 :46,808,412-46,844,251
TargetScan: NM_002643
cisRED: ENSG00000151665
ContextiHOP: PIGF
cancer metabolism search in PubMed: PIGF
UCL Cancer Institute: PIGF
Assigned class in ccmGDBC

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Phenotypic Information for PIGF(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: PIGF
Familial Cancer Database: PIGF
* 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
REACTOME_METABOLISM_OF_PROTEINS

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

Mutations for PIGF
* 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
There's no inter-chromosomal structural variation.
- For Intra-chromosomal Variations
* Intra-chromosomal variantions includes 'intrachromosomal amplicon to amplicon', 'intrachromosomal amplicon to non-amplified dna', 'intrachromosomal deletion', 'intrachromosomal fold-back inversion', 'intrachromosomal inversion', 'intrachromosomal tandem duplication', 'Intrachromosomal unknown type', 'intrachromosomal with inverted orientation', 'intrachromosomal with non-inverted orientation'.
SampleSymbol_aChr_aStart_aEnd_aSymbol_bChr_bStart_bEnd_b
ovaryPIGFchr24683916646839186chr24699526046995280
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 PIGF related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
BC039303PIGF1345324683936646844169C14orf15934524401149169102791691976

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=3

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=10)
Stat. for Synonymous SNVs
(# total SNVs=2)
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
chr2:46839477-46839477p.A109A2
chr2:46808672-46808672p.I202T2
chr2:46839390-46839390p.W138*1
chr2:46842208-46842208p.E32D1
chr2:46842221-46842221p.S28L1
chr2:46840834-46840834p.E107Q1
chr2:46842225-46842225p.P27S1
chr2:46840838-46840838p.L105L1
chr2:46842248-46842248p.S19L1
chr2:46840890-46840890p.L88R1

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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
# sample1  11       1   21 3
# mutation2  11       1   21 3
nonsynonymous SNV2  11       1   21 2
synonymous SNV                   1
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
chr2:46840911p.K69E,PIGF1
chr2:46840918p.E38Q,PIGF1
chr2:46842079p.E32D,PIGF1
chr2:46842099p.S19L,PIGF1
chr2:46842192p.I202M1
chr2:46842208p.I202T1
chr2:46842248p.E107Q,PIGF1
chr2:46808671p.L88R,PIGF1
chr2:46808672p.L81S,PIGF1
chr2:46840834p.G79R,PIGF1

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 PIGF 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 PIGF

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

BOLA3,ATRAID,CISD2,COX7A2,COX7A2L,CRIPT,DAD1,
DYNC2LI1,IAH1,MCTS1,MDH1,MRPL33,MRPL35,NFU1,
NUDCD2,PIGF,PSMA2,RAB1A,RDH14,RPA3,UNC50
ACTR10,ANAPC13,ATP8B5P,C18orf32,COMMD8,DAD1,DERA,
GNG5,GTF2A2,IER3IP1,MGST2,MRPS18C,NOP10,PIGF,
POMP,RPS27L,SELT,SUMO1,TMEM126B,TOMM5,TSEN15

ACP1,ATP5C1,ATP5F1,ATP5G3,TEFM,CALM2,CKS2,
CNIH1,COX7A2L,DPY30,FAM96A,GEMIN6,MCEE,MDH1,
MEMO1,MRPL33,MRPL35,NFU1,OST4,PIGF,SNRPG
ARFIP1,ATP5F1,CHCHD1,COX16,DCTPP1,FAM96A,FPGT,
MRPL13,MRPS33,MRPS35,NUDT15,NXT2,PEX7,PIGF,
PPA2,RFWD2,SFT2D1,TMED5,TMEM68,TXNDC12,UQCRH
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 PIGF


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