Cancer Cell Metabolism Gene Database

  Cancer Cell Metabolism Gene DB

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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 NME1-NME2
Basic gene info.Gene symbolNME1-NME2
Gene nameNME1-NME2 readthrough
SynonymsNM23-LV|NMELV
CytomapUCSC genome browser: 17q21.3
Genomic locationchr17 :49230896-49249105
Type of geneprotein-coding
RefGenesNM_001018136.2,
NR_037149.1,
Ensembl idENSG00000243678
DescriptionNME1-NME2 proteinNME1-NME2 readthrough transcript
Modification date20141207
dbXrefs HGNC : HGNC
Ensembl : ENSG00000011052
Vega : OTTHUMG00000137475
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_NME1-NME2
BioGPS: 654364
Gene Expression Atlas: ENSG00000243678
The Human Protein Atlas: ENSG00000243678
PathwayNCI Pathway Interaction Database: NME1-NME2
KEGG: NME1-NME2
REACTOME: NME1-NME2
ConsensusPathDB
Pathway Commons: NME1-NME2
MetabolismMetaCyc: NME1-NME2
HUMANCyc: NME1-NME2
RegulationEnsembl's Regulation: ENSG00000243678
miRBase: chr17 :49,230,896-49,249,105
TargetScan: NM_001018136
cisRED: ENSG00000243678
ContextiHOP: NME1-NME2
cancer metabolism search in PubMed: NME1-NME2
UCL Cancer Institute: NME1-NME2
Assigned class in ccmGDBC

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Phenotypic Information for NME1-NME2(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: NME1-NME2
Familial Cancer Database: NME1-NME2
* 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_PURINE_METABOLISM
KEGG_PYRIMIDINE_METABOLISM
REACTOME_METABOLISM_OF_NUCLEOTIDES

check002.gifOthers
OMIM
Orphanet
DiseaseKEGG Disease: NME1-NME2
MedGen: NME1-NME2 (Human Medical Genetics with Condition)
ClinVar: NME1-NME2
PhenotypeMGI: NME1-NME2 (International Mouse Phenotyping Consortium)
PhenomicDB: NME1-NME2

Mutations for NME1-NME2
* 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
* Inter-chromosomal variantions includes 'interchromosomal amplicon to amplicon', 'interchromosomal amplicon to non-amplified dna', 'interchromosomal insertion', 'Interchromosomal unknown type'.
- For Intra-chromosomal Variations
There's no intra-chromosomal structural variation.
SampleSymbol_aChr_aStart_aEnd_aSymbol_bChr_bStart_bEnd_b
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 NME1-NME2 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 # sample3               1
GAIN (# sample)3               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=13)
Stat. for Synonymous SNVs
(# total SNVs=3)
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
chr17:49247316-49247316p.V198M2
chr17:49237425-49237425p.G71W1
chr17:49247383-49247383p.R220H1
chr17:49238549-49238549p.T86M1
chr17:49248846-49248846p.?1
chr17:49238608-49238608p.G106*1
chr17:49248891-49248891p.E244*1
chr17:49244193-49244193p.M116T1
chr17:49248918-49248918p.E253*1
chr17:49244208-49244208p.R121L1

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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=0

Point Mutation/ Tissue ID1234567891011121314151617181920
# sample                    
# mutation                    
nonsynonymous SNV                    
synonymous SNV                    
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

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 NME1-NME2 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 NME1-NME2

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

AURKAIP1,C19orf70,CLPP,CUEDC2,EEF1D,MRPL27,MRPL54,
MYL6,NDUFA11,NDUFA13,NDUFS7,NME1,NME1-NME2,NME2,
NME2P1,NUDC,PIN1,SNF8,TIMM13,UQCR11,VPS28
ASNA1,EMC10,DNPH1,COPE,EXOSC4,FIBP,GIPC1,
HSPBP1,MPG,MPND,MRPS12,NHP2,NME1,NME1-NME2,
NUBP2,PHB,PPP4C,PTRH1,RUVBL2,TIMM13,TSTA3

ALG3,ATAD3B,BCL2L12,C16orf59,AUNIP,CCDC37,MRPL28,
MRTO4,NDUFS8,TONSL,NME1-NME2,NOC2L,NUDC,PKMYT1,
POLR3K,PSMB2,RECQL4,SLC4A9,SPO11,SRM,TUBG1
CLPB,EEF2KMT,FJX1,FXN,G6PC3,GTPBP4,HAUS7,
HM13,HSPBP1,LYAR,MLKL,MMP3,NME1-NME2,NOP2,
PA2G4,RIPK2,RUVBL1,SDF2L1,SRM,USP14,WDR4
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 NME1-NME2


There's no related Drug.
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Cross referenced IDs for NME1-NME2
* 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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