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 NUP85
Basic gene info.Gene symbolNUP85
Gene namenucleoporin 85kDa
SynonymsNup75
CytomapUCSC genome browser: 17q25.1
Genomic locationchr17 :73201596-73231854
Type of geneprotein-coding
RefGenesNM_024844.3,
Ensembl idENSG00000125450
Description85 kDa nucleoporinfrountnuclear pore complex protein Nup85nucleoporin Nup75nucleoporin Nup85pericentrin-1
Modification date20141207
dbXrefs MIM : 170285
HGNC : HGNC
Ensembl : ENSG00000125450
HPRD : 01363
Vega : OTTHUMG00000179482
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_NUP85
BioGPS: 79902
Gene Expression Atlas: ENSG00000125450
The Human Protein Atlas: ENSG00000125450
PathwayNCI Pathway Interaction Database: NUP85
KEGG: NUP85
REACTOME: NUP85
ConsensusPathDB
Pathway Commons: NUP85
MetabolismMetaCyc: NUP85
HUMANCyc: NUP85
RegulationEnsembl's Regulation: ENSG00000125450
miRBase: chr17 :73,201,596-73,231,854
TargetScan: NM_024844
cisRED: ENSG00000125450
ContextiHOP: NUP85
cancer metabolism search in PubMed: NUP85
UCL Cancer Institute: NUP85
Assigned class in ccmGDBC

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Phenotypic Information for NUP85(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: NUP85
Familial Cancer Database: NUP85
* 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_NON_CODING_RNA
REACTOME_METABOLISM_OF_RNA
REACTOME_METABOLISM_OF_CARBOHYDRATES

check002.gifOthers
OMIM
Orphanet
DiseaseKEGG Disease: NUP85
MedGen: NUP85 (Human Medical Genetics with Condition)
ClinVar: NUP85
PhenotypeMGI: NUP85 (International Mouse Phenotyping Consortium)
PhenomicDB: NUP85

Mutations for NUP85
* 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 NUP85 related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
DB001249WBP23204177384764773851410NUP85194564177321184373221471
DA567594ZNF7714181929365222944945NUP85417535177320808573209216
CA313471NUP8518123177323174873231853NUP85111190177323170773231786
CB243613NUP8518123177323174873231853NUP85111190177323170773231786
AA593414NUP851235177322720073227434NUP85226349177322903373229156

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=2

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=30)
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
chr17:73221509-73221509p.L269I2
chr17:73209205-73209205p.F132F2
chr17:73231708-73231708p.L635L2
chr17:73231715-73231715p.S638P2
chr17:73222233-73222233p.Q359*2
chr17:73231731-73231731p.L643H2
chr17:73227439-73227439p.A367T2
chr17:73204631-73204631p.G15C1
chr17:73227514-73227514p.L392I1
chr17:73231773-73231773p.*657*1

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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
# sample6  9  2 1  512  77 6
# mutation6  7  2 1  522  77 7
nonsynonymous SNV4  5  1 1  412  46 7
synonymous SNV2  2  1    11   31  
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
chr17:73227439p.A367T3
chr17:73204648p.P29A1
chr17:73229176p.P344S1
chr17:73214302p.L521H1
chr17:73231685p.P29L1
chr17:73227516p.L521L1
chr17:73204673p.R58C1
chr17:73229200p.L368L1
chr17:73214330p.R542H1
chr17:73231686p.I67I1

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 NUP85 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 NUP85

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

ATP5H,BIRC5,METTL23,GGA3,HN1,ICT1,JMJD6,
LLGL2,MRPL38,MRPS7,NAT9,NUP85,RECQL5,SAP30BP,
SRSF2,SLC25A19,SUMO2,ALYREF,TMEM104,TSEN54,UBE2O
ACD,TMEM234,CCDC84,DDX39A,DEF6,EGFL8,LAT,
LUC7L,NFKBIE,NUP85,PABPN1,PBX4,POLR2H,PRR14,
RHBDF2,SDCCAG3,SNHG12,TMEM86B,TNFRSF14,TOR2A,ZGLP1

ATP5H,BIRC5,C17orf53,CCDC137,EFTUD2,EIF4A3,ERAL1,
ICT1,MRPL12,MRPL38,MRPS7,NAT9,NME1,NUP85,
PHB,SRSF2,SLC25A19,TACO1,ALYREF,TSEN54,UTP18
BIRC5,DDIAS,CDCA4,CDK1,CHEK2,DBF4,DNAJC9,
DSN1,DTYMK,GINS1,GINS2,KIAA0101,NUP85,ORC6,
PCNA,POLE2,PYCR1,RAD51AP1,RANBP1,UBE2T,UTP6
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 NUP85


There's no related Drug.
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Cross referenced IDs for NUP85
* 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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