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 EIF4EBP1
Basic gene info.Gene symbolEIF4EBP1
Gene nameeukaryotic translation initiation factor 4E binding protein 1
Synonyms4E-BP1|4EBP1|BP-1|PHAS-I
CytomapUCSC genome browser: 8p12
Genomic locationchr8 :37888019-37917883
Type of geneprotein-coding
RefGenesNM_004095.3,
Ensembl idENSG00000187840
DescriptioneIF4E-binding protein 1eukaryotic translation initiation factor 4E-binding protein 1phosphorylated heat- and acid-stable protein regulated by insulin 1
Modification date20141222
dbXrefs MIM : 602223
HGNC : HGNC
Ensembl : ENSG00000187840
HPRD : 03746
Vega : OTTHUMG00000164012
ProteinUniProt: Q13541
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_EIF4EBP1
BioGPS: 1978
Gene Expression Atlas: ENSG00000187840
The Human Protein Atlas: ENSG00000187840
PathwayNCI Pathway Interaction Database: EIF4EBP1
KEGG: EIF4EBP1
REACTOME: EIF4EBP1
ConsensusPathDB
Pathway Commons: EIF4EBP1
MetabolismMetaCyc: EIF4EBP1
HUMANCyc: EIF4EBP1
RegulationEnsembl's Regulation: ENSG00000187840
miRBase: chr8 :37,888,019-37,917,883
TargetScan: NM_004095
cisRED: ENSG00000187840
ContextiHOP: EIF4EBP1
cancer metabolism search in PubMed: EIF4EBP1
UCL Cancer Institute: EIF4EBP1
Assigned class in ccmGDBA - This gene has a literature evidence and it belongs to cancer gene.
References showing role of EIF4EBP1 in cancer cell metabolism1. Teo T, Yu M, Yang Y, Gillam T, Lam F, et al. (2015) Pharmacologic co-inhibition of Mnks and mTORC1 synergistically suppresses proliferation and perturbs cell cycle progression in blast crisis-chronic myeloid leukemia cells. Cancer Lett 357: 612-623. doi: 10.1016/j.canlet.2014.12.029. go to article
2. Hsu HS, Lin MH, Jang YH, Kuo TT, Liu CC, et al. (2015) The 4E-BP1/eIF4E ratio is a determinant for rapamycin response in esophageal cancer cells. J Thorac Cardiovasc Surg 149: 378-385. doi: 10.1016/j.jtcvs.2014.09.047. go to article
3. Andrikopoulou M, Salakos N, Deligeoroglou E, Pafiti A, Boutas I, et al. (2015) The role of mTOR signaling pathway in premalignant and malignant cervical lesions. Eur J Gynaecol Oncol 36: 36-43. go to article

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Phenotypic Information for EIF4EBP1(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: EIF4EBP1
Familial Cancer Database: EIF4EBP1
* 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 602223; gene.
Orphanet
DiseaseKEGG Disease: EIF4EBP1
MedGen: EIF4EBP1 (Human Medical Genetics with Condition)
ClinVar: EIF4EBP1
PhenotypeMGI: EIF4EBP1 (International Mouse Phenotyping Consortium)
PhenomicDB: EIF4EBP1

Mutations for EIF4EBP1
* 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 EIF4EBP1 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 # sample2     1          
GAIN (# sample)1     1          
LOSS (# sample)2                
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=3

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=5)
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
chr8:37914710-37914710p.S86N1
chr8:37914744-37914744p.H97Q1
chr8:37914772-37914772p.A107T1
chr8:37914773-37914773p.A107V1
chr8:37914609-37914609p.I52I1
chr8:37914774-37914774p.A107A1
chr8:37914619-37914619p.R56W1
chr8:37914775-37914775p.G108C1
chr8:37914620-37914620p.R56Q1
chr8:37914629-37914629p.L59Q1

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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=2

Point Mutation/ Tissue ID1234567891011121314151617181920
# sample1     2     11  22 1
# mutation1     2     11  22 1
nonsynonymous SNV1     1      1  12  
synonymous SNV      1     1   1  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
chr8:37914654p.V67V2
chr8:37914773p.I52I1
chr8:37914778p.R56W1
chr8:37914609p.R56Q1
chr8:37914619p.R73R1
chr8:37914620p.S86N1
chr8:37914672p.H97Q1
chr8:37914710p.A107V1
chr8:37914744p.G109C1

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 EIF4EBP1 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 EIF4EBP1

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.
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check002.gifProtein Expression Plot (RPPA)
*RPPA protein expression data were extracted from TCPA (The Cancer Proteome Atlas). Normalized data based on replicated based normalization (RBN) was used to draw following figures.

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

ALG3,ASH2L,BOLA3,BRF2,BUD31,ECE2,EIF4EBP1,
LSM1,LSM4,MRPS2,NPM3,POLR2H,PPAPDC1B,PROSC,
PSMG3,RPL30,SNHG6,SRM,TCEB1,TIMM44,UBE2S
ACSM2B,ASS1,BSG,IZUMO4,C20orf27,EIF4EBP1,FPGS,
GCDH,GLYCTK,MEF2B,MPST,NDRG4,PCBD1,PCYT2,
PDZD7,PMM1,PQLC1,PXMP2,RASL10B,RPLP2,TMEM120A

ASH2L,BRF2,CENPM,CYC1,EIF3I,EIF4EBP1,EIF5A,
EXOSC4,H2AFZ,KRTCAP3,LSM1,MFSD2B,MRPL12,MRTO4,
PROSC,PUSL1,RCC1,RPS6KB2,SRSF9,SRM,ZNF511
AFMID,C19orf48,C9orf142,CCDC34,EIF4EBP1,EXOSC5,FBXW9,
GCAT,MPG,MRPS18A,MRPS26,NAT9,NTHL1,PAFAH1B3,
PPP5C,PRPS2,SLC35B2,SSBP4,SYNGR2,TMED3,YIPF2
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 EIF4EBP1
check002.gifCross-referenced pharmacological DB IDs from Uniprot
DB CategoryDB NameDB's ID and Url link
Organism-specific databasesPharmGKB PA27715; -.
Organism-specific databasesCTD 1978; -.

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 4E binding protein 1approved; investigationalSirolimus


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Cross referenced IDs for EIF4EBP1
* 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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