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 APIP
Basic gene info.Gene symbolAPIP
Gene nameAPAF1 interacting protein
SynonymsAPIP2|CGI29|MMRP19|hAPIP
CytomapUCSC genome browser: 11p13
Genomic locationchr11 :34903842-34937939
Type of geneprotein-coding
RefGenesNM_015957.3,
Ensembl idENSG00000149089
DescriptionAPAF1-interacting proteinMTRu-1-P dehydratasemethylthioribulose-1-phosphate dehydrataseprobable methylthioribulose-1-phosphate dehydratase
Modification date20141207
dbXrefs MIM : 612491
HGNC : HGNC
Ensembl : ENSG00000149089
HPRD : 14725
Vega : OTTHUMG00000166455
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_APIP
BioGPS: 51074
Gene Expression Atlas: ENSG00000149089
The Human Protein Atlas: ENSG00000149089
PathwayNCI Pathway Interaction Database: APIP
KEGG: APIP
REACTOME: APIP
ConsensusPathDB
Pathway Commons: APIP
MetabolismMetaCyc: APIP
HUMANCyc: APIP
RegulationEnsembl's Regulation: ENSG00000149089
miRBase: chr11 :34,903,842-34,937,939
TargetScan: NM_015957
cisRED: ENSG00000149089
ContextiHOP: APIP
cancer metabolism search in PubMed: APIP
UCL Cancer Institute: APIP
Assigned class in ccmGDBC

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Phenotypic Information for APIP(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: APIP
Familial Cancer Database: APIP
* 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_CYSTEINE_AND_METHIONINE_METABOLISM
REACTOME_SULFUR_AMINO_ACID_METABOLISM
REACTOME_METABOLISM_OF_AMINO_ACIDS_AND_DERIVATIVES
REACTOME_METABOLISM_OF_POLYAMINES

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

Mutations for APIP
* 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
ovaryAPIPchr113490691834906938chr113477758434777604
ovaryAPIPchr113491115134911171PDHXchr113494401034944030
ovaryAPIPchr113491527734915297PDHXchr113494470534944725
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 APIP 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  1  2   1   3 1
GAIN (# sample)1  1      1   3  
LOSS (# sample)      2         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=2

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=15)
Stat. for Synonymous SNVs
(# total SNVs=5)
Stat. for Deletions
(# total SNVs=3)
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
chr11:34910341-34910341p.S95fs*83
chr11:34909926-34909926p.T125T2
chr11:34937813-34937813p.R7W2
chr11:34910351-34910351p.K91N2
chr11:34909852-34909852p.G150E1
chr11:34916553-34916553p.?1
chr11:34909860-34909860p.C147*1
chr11:34916561-34916561p.H52Y1
chr11:34909881-34909881p.M140I1
chr11:34916596-34916596p.W40L1

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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=1

Point Mutation/ Tissue ID1234567891011121314151617181920
# sample   3    1  2     2 2
# mutation   3    1  2     2 2
nonsynonymous SNV   1    1  1     2 2
synonymous SNV   2       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
chr11:34916561p.Q19H1
chr11:34916581p.Y216C1
chr11:34937775p.T203K1
chr11:34904346p.V199V1
chr11:34904905p.V190V1
chr11:34904916p.T167A1
chr11:34904943p.T106T1
chr11:34905014p.L100I1
chr11:34910306p.H52Y1
chr11:34910326p.G45E1

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 APIP 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 APIP

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

ABTB2,APIP,MCMBP,ARL14EP,CAPRIN1,CAT,CKAP5,
COMMD9,CSTF3,DCLRE1B,LOC283267,MTCH2,NAT10,NRAS,
NUP160,PDHX,PHTF1,QSER1,SAAL1,TRAF6,TRIM44
ACAA2,APIP,BNIP3,DECR1,FAM89A,GBE1,HADH,
HIBADH,HSDL2,IAH1,NFU1,PFKFB1,PPP1R1A,PPP2R5A,
PRDX6,RNF157,RTCA,STBD1,STRADB,SUCLG1,EMC3

APIP,C10orf99,C3orf67,CC2D1A,CD24,EHF,ELF5,
FLJ32063,GSPT2,LOC283070,MECOM,OXGR1,PLEKHG7,RDH12,
ROPN1,SATB2,SHOX,SLC4A10,SLC5A8,TMEM56,WIPI1
APIP,APOL4,C1GALT1C1,CCL2,DRAM1,FCGR1A,FCGR1B,
GOLT1B,IDO1,IL12A,IL13RA2,IL22,LILRA5,LOC400759,
MMP1,NMI,PMAIP1,PSMA3,PSMA4,SUCNR1,TNFSF13B
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 APIP


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