Cancer Cell Metabolism Gene Database

  Cancer Cell Metabolism Gene DB

Home

Search

Download

 Statistics

Help

About Us

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 NOP56
Basic gene info.Gene symbolNOP56
Gene nameNOP56 ribonucleoprotein
SynonymsNOL5A|SCA36
CytomapUCSC genome browser: 20p13
Genomic locationchr20 :2633177-2639039
Type of geneprotein-coding
RefGenesNM_006392.3,
NR_027700.2,
Ensembl idENSG00000101361
DescriptionNOP56 ribonucleoprotein homolognucleolar protein 56nucleolar protein 5A (56kDa with KKE/D repeat)
Modification date20141207
dbXrefs MIM : 614154
HGNC : HGNC
Ensembl : ENSG00000101361
HPRD : 10119
Vega : OTTHUMG00000031703
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_NOP56
BioGPS: 10528
Gene Expression Atlas: ENSG00000101361
The Human Protein Atlas: ENSG00000101361
PathwayNCI Pathway Interaction Database: NOP56
KEGG: NOP56
REACTOME: NOP56
ConsensusPathDB
Pathway Commons: NOP56
MetabolismMetaCyc: NOP56
HUMANCyc: NOP56
RegulationEnsembl's Regulation: ENSG00000101361
miRBase: chr20 :2,633,177-2,639,039
TargetScan: NM_006392
cisRED: ENSG00000101361
ContextiHOP: NOP56
cancer metabolism search in PubMed: NOP56
UCL Cancer Institute: NOP56
Assigned class in ccmGDBC

Top
Phenotypic Information for NOP56(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: NOP56
Familial Cancer Database: NOP56
* 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: NOP56
MedGen: NOP56 (Human Medical Genetics with Condition)
ClinVar: NOP56
PhenotypeMGI: NOP56 (International Mouse Phenotyping Consortium)
PhenomicDB: NOP56

Mutations for NOP56
* 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 NOP56 related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
DA801918NOP561532026372882637340SLC44A254450191071313110741815
CN266780NASP944514604974446072216NOP564427042026374942638650
W23530NOP561612026377242637784PPAP2B4735915696199956962311
DB044831UBL4B14171110655085110655501NOP564065712026355532636096
AV759376NOP561652026375882637652RBPMS6039883038566230386067

check002.gifOther DBs for Structural Variants
Structural Variants in Ensembl: go to Ensembl Structural variation
Structural Variants in dbVar: go to dbVar

Top
check002.gifCopy Number Variations in COSMIC: go to COSMIC mutation CNV/Expr
 
Mutation type/ Tissue IDbrcacnscervendomehaematopokidnLintestliverlungnsovarypancreprostskinstomathyrourina
Total # sample     1  1      1 
GAIN (# sample)     1  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)

Top
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

Top
check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=57)
Stat. for Synonymous SNVs
(# total SNVs=10)
Stat. for Deletions
(# total SNVs=1)
Stat. for Insertions
(# total SNVs=0)
There's no inserted snv.

Top
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
chr20:2635158-2635158p.A103T3
chr20:2636095-2636095p.E232K3
chr20:2636268-2636268p.I262R2
chr20:2636275-2636275p.I264I2
chr20:2637452-2637452p.R398*2
chr20:2638767-2638767p.T538A2
chr20:2635554-2635554p.Q177L2
chr20:2637470-2637470p.R404*2
chr20:2636584-2636584p.G305D2
chr20:2635071-2635071p.E74Q1

Top
check002.gifSNV Counts per Each Loci in TCGA data

 : non-synonymous mutation, : synonymous mutation, Circle size denotes number of samples.
maximum mutation count=5

Point Mutation/ Tissue ID1234567891011121314151617181920
# sample22 111 1 2  4331 63 10
# mutation32 131 1 2  4331 63 11
nonsynonymous SNV21 81 1 2  4321 23 11
synonymous SNV11 5         1  4   
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])

Top
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
chr20:2635158p.A103T5
chr20:2636275p.I264I2
chr20:2637863p.R154C1
chr20:2636010p.S295N1
chr20:2638897p.E497D1
chr20:2637183p.N162N1
chr20:2635176p.E332K1
chr20:2638580p.K509K1
chr20:2636061p.R163Q1
chr20:2638918p.R337G1

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 NOP56 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]

Top
Gene Expression for NOP56

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))
Top
check002.gifCNV vs Gene Expression Plot
* This plots show the correlation between CNV and gene expression.

: Open all plots for all cancer types


Top
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

C19orf48,C20orf27,NDUFAF5,CCT3,IDH3B,ITPA,LOC388796,
MRPS26,MRTO4,NOP16,NOP56,NSFL1C,PCNA,PES1,
PUS1,RPL30,SLC25A19,SNRPB2,SNRPB,SNRPD1,TRMT6
ALKBH2,C19orf48,EIF3B,MCM7,MRTO4,NAT9,NOP16,
NOP2,NOP56,NPM3,PES1,PUS1,REXO4,RPL3,
RRP1,RRP9,RUVBL1,SSRP1,WDR46,WDR74,ZMYND19

C20orf27,CRLS1,CSNK2A1,ESF1,FASTKD5,IDH3B,ITPA,
MCM8,MKKS,MRPS26,NOP56,PANK2,PCNA,PSMF1,
SNRPB2,SNRPB,SRXN1,TASP1,TRMT6,ZCCHC3,ZNF343
ABCE1,CCT2,EBNA1BP2,EEF2KMT,FTSJ1,IFRD2,LTV1,
LYAR,METTL1,MRTO4,NME1,NOC3L,NOP56,PA2G4,
PPIL1,PRMT1,PRMT5,RRP9,RUVBL1,STIP1,WDR77
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

Top
check002.gifInteracting Genes (from Pathway Commons)

: Open all interacting genes' information including KEGG pathway for all interacting genes from DAVID

Top
Pharmacological Information for NOP56


There's no related Drug.
Top
Cross referenced IDs for NOP56
* 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



Copyright © 2016-Present - The Univsersity of Texas Health Science Center at Houston @
Site Policies | State of Texas