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 EIF2B5
Basic gene info.Gene symbolEIF2B5
Gene nameeukaryotic translation initiation factor 2B, subunit 5 epsilon, 82kDa
SynonymsCACH|CLE|EIF-2B|EIF2Bepsilon|LVWM
CytomapUCSC genome browser: 3q27.1
Genomic locationchr3 :183852809-183863099
Type of geneprotein-coding
RefGenesNM_003907.2,
Ensembl idENSG00000145191
DescriptioneIF-2B GDP-GTP exchange factor subunit epsilontranslation initiation factor eIF-2B subunit epsilon
Modification date20141219
dbXrefs MIM : 603945
HGNC : HGNC
Ensembl : ENSG00000145191
HPRD : 04898
Vega : OTTHUMG00000156840
ProteinUniProt: Q13144
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_EIF2B5
BioGPS: 8893
Gene Expression Atlas: ENSG00000145191
The Human Protein Atlas: ENSG00000145191
PathwayNCI Pathway Interaction Database: EIF2B5
KEGG: EIF2B5
REACTOME: EIF2B5
ConsensusPathDB
Pathway Commons: EIF2B5
MetabolismMetaCyc: EIF2B5
HUMANCyc: EIF2B5
RegulationEnsembl's Regulation: ENSG00000145191
miRBase: chr3 :183,852,809-183,863,099
TargetScan: NM_003907
cisRED: ENSG00000145191
ContextiHOP: EIF2B5
cancer metabolism search in PubMed: EIF2B5
UCL Cancer Institute: EIF2B5
Assigned class in ccmGDBA - This gene has a literature evidence and it belongs to cancer gene.
References showing role of EIF2B5 in cancer cell metabolism1. Sheveleva EV, Landowski TH, Samulitis BK, Bartholomeusz G, Powis G, et al. (2012) Imexon induces an oxidative endoplasmic reticulum stress response in pancreatic cancer cells. Mol Cancer Res 10: 392-400. doi: 10.1158/1541-7786.MCR-11-0359. pmid: 3324333. go to article
2. Xue D, Lu M, Gao B, Qiao X, Zhang Y (2014) Screening for transcription factors and their regulatory small molecules involved in regulating the functions of CL1-5 cancer cells under the effects of macrophage-conditioned medium. Oncol Rep 31: 1323-1333. doi: 10.3892/or.2013.2937. go to article

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Phenotypic Information for EIF2B5(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: EIF2B5
Familial Cancer Database: EIF2B5
* 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 603896; phenotype.
603945; gene.
Orphanet 157713; Congenital or early infantile CACH syndrome.
157716; Late infantile CACH syndrome.
157719; Juvenile or adult CACH syndrome.
99853; Ovarioleukodystrophy.
99854; Cree leukoencephalopathy.
DiseaseKEGG Disease: EIF2B5
MedGen: EIF2B5 (Human Medical Genetics with Condition)
ClinVar: EIF2B5
PhenotypeMGI: EIF2B5 (International Mouse Phenotyping Consortium)
PhenomicDB: EIF2B5

Mutations for EIF2B5
* 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 EIF2B5 related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
BM011896EIF2B51321543183860093183860115EIF2B51557053183858403183860610

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 1        
GAIN (# sample)        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)

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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=8

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=51)
Stat. for Synonymous SNVs
(# total SNVs=15)
Stat. for Deletions
(# total SNVs=1)
Stat. for Insertions
(# total SNVs=1)

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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
chr3:183860605-183860605p.S529G6
chr3:183856022-183856022p.I251I3
chr3:183857942-183857942p.E280E2
chr3:183860047-183860047p.T442M2
chr3:183855535-183855535p.L150L2
chr3:183862019-183862019p.?2
chr3:183858264-183858264p.S301F2
chr3:183860379-183860379p.Q512*2
chr3:183859753-183859753p.G399G2
chr3:183859757-183859757p.R401*2

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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=8

Point Mutation/ Tissue ID1234567891011121314151617181920
# sample13117  4 21 236  3715
# mutation13112  4 21 436  3815
nonsynonymous SNV1118  2 21 325  15 4
synonymous SNV 2 4  2    111  2311
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
chr3:183860605p.S529G6
chr3:183856022p.S301C2
chr3:183857942p.I251I2
chr3:183858264p.E280E2
chr3:183856019p.E104A1
chr3:183860885p.V300V1
chr3:183858377p.V435V1
chr3:183854515p.I661T1
chr3:183860027p.L135L1
chr3:183861242p.T442M1

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 EIF2B5 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 EIF2B5

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

ABCF3,ALG3,AP2M1,BDH1,DVL3,EIF2B5,EIF4G1,
FXR1,LOC152217,LSG1,MAGEF1,MRPL47,NCBP2,NDUFB5,
PARL,POLR2H,PSMD2,RFC4,RPL35A,TMEM41A,WDR53
APEH,ATPAF2,ATPIF1,C21orf59,CARKD,CNKSR1,DCAF11,
EIF2B5,GCAT,GTF2IRD1,KIF22,NPRL2,PDRG1,PPP2R4,
PRPF40B,ROGDI,MIEF2,SNAP47,SNRPD3,TMEM186,WRNIP1

ABCF3,ACAD9,ALG3,ATR,HMCES,EEFSEC,EIF2B5,
FBXO45,ISY1,LOC220729,LSG1,MCCC1,OPA1,POLQ,
POLR2H,QTRTD1,RUVBL1,SENP2,U2SURP,TMEM41A,UMPS
BCL2L12,BIRC5,KNSTRN,C19orf48,MIS18A,ARHGEF39,CCNB1,
CDCA4,DNAJC9,EIF2B5,MRPL37,NUP85,PAICS,PRMT5,
RANBP1,RCC1,RUVBL1,RUVBL2,SAAL1,NDC1,TRAIP
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 EIF2B5
check002.gifCross-referenced pharmacological DB IDs from Uniprot
DB CategoryDB NameDB's ID and Url link
Organism-specific databasesPharmGKB PA27692; -.
Organism-specific databasesCTD 8893; -.

check002.gifDrug-Gene Interaction Network
* Gene Centered Interaction Network.
* Drug Centered Interaction Network.
DrugBank IDTarget NameDrug GroupsGeneric NameDrug Centered NetworkDrug Structure
DB00877eukaryotic translation initiation factor 2B, subunit 5 epsilon, 82kDaapproved; investigationalSirolimus


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Cross referenced IDs for EIF2B5
* 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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