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 EXOSC1
Basic gene info.Gene symbolEXOSC1
Gene nameexosome component 1
SynonymsCGI-108|CSL4|Csl4p|SKI4|Ski4p|hCsl4p|p13
CytomapUCSC genome browser: 10q24
Genomic locationchr10 :99195665-99205768
Type of geneprotein-coding
RefGenesNM_016046.3,
Ensembl idENSG00000171311
Description3'-5' exoribonuclease CSL4 homologCSL4 exosomal core protein homologexosomal core protein CSL4exosome complex component CSL4homolog of yeast exosomal core protein CSL4
Modification date20141207
dbXrefs MIM : 606493
HGNC : HGNC
HPRD : 16223
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_EXOSC1
BioGPS: 51013
Gene Expression Atlas: ENSG00000171311
The Human Protein Atlas: ENSG00000171311
PathwayNCI Pathway Interaction Database: EXOSC1
KEGG: EXOSC1
REACTOME: EXOSC1
ConsensusPathDB
Pathway Commons: EXOSC1
MetabolismMetaCyc: EXOSC1
HUMANCyc: EXOSC1
RegulationEnsembl's Regulation: ENSG00000171311
miRBase: chr10 :99,195,665-99,205,768
TargetScan: NM_016046
cisRED: ENSG00000171311
ContextiHOP: EXOSC1
cancer metabolism search in PubMed: EXOSC1
UCL Cancer Institute: EXOSC1
Assigned class in ccmGDBC

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Phenotypic Information for EXOSC1(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: EXOSC1
Familial Cancer Database: EXOSC1
* 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_MRNA
REACTOME_METABOLISM_OF_RNA

check002.gifOthers
OMIM
Orphanet
DiseaseKEGG Disease: EXOSC1
MedGen: EXOSC1 (Human Medical Genetics with Condition)
ClinVar: EXOSC1
PhenotypeMGI: EXOSC1 (International Mouse Phenotyping Consortium)
PhenomicDB: EXOSC1

Mutations for EXOSC1
* 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
ovaryEXOSC1chr109920501399205033COL5A1chr9137670326137670346
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 EXOSC1 related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
BF361687EXOSC11112109919567599195786EXOSC1107228109919638499196505

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=4)
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
chr10:99205521-99205521p.G39S2
chr10:99196960-99196960p.H157Y1
chr10:99196961-99196961p.A156A1
chr10:99196982-99196982p.N149N1
chr10:99198446-99198446p.R109L1
chr10:99200940-99200940p.R100Q1
chr10:99200974-99200974p.Y89H1
chr10:99200984-99200984p.V85V1
chr10:99203015-99203015p.V67V1
chr10:99196219-99196219p.E191K1

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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
# sample  1   2    11   23 2
# mutation  1   2    31   23 2
nonsynonymous SNV  1   1    21   12  
synonymous SNV      1    1    11 2
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
chr10:99196230p.R187L2
chr10:99196960p.F182L1
chr10:99196961p.H157Y1
chr10:99196982p.A156A1
chr10:99197027p.N149N1
chr10:99198446p.S134S1
chr10:99200984p.R109L1
chr10:99202994p.V85V1
chr10:99203015p.K74N1
chr10:99196219p.V67V1

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 EXOSC1 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 EXOSC1

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

ATP5G2,C12orf45,C19orf43,CUEDC2,EXOSC1,GSTO1,HIGD2A,
KRTCAP2,MRPL43,MTX1,NDUFB8,OST4,POLR2J,SFXN4,
SLC25A28,SNRPA,TAF10,TRAPPC1,TXNDC17,USMG5,ZDHHC16
BUD31,C17orf49,C19orf43,WDR83OS,COA3,CSNK2B,EXOSC1,
JTB,LSM2,MDP1,MRPS21,NSMCE1,PSENEN,SF3B5,
SRP14,SSBP1,TMEM219,TOMM6,TRMT112,UBA52,UXT

ATP5L,FAM204A,C19orf53,CCDC58,CWF19L1,DPY30,EXOSC1,
GEMIN6,GLRX3,MRPL43,NDUFB8,NPM3,PCGF6,RPP30,
RPS13,RPS15A,SFXN4,SNRPC,SNRPE,SNRPG,USMG5
ANAPC11,ASNA1,ATP6V1F,TMEM258,ELP6,COPZ1,EXOSC1,
FAU,LSM7,OSGEP,OST4,POLR2G,RPL19,RPL27A,
RPL35,RPS16,SERF2,SNRPC,SNRPD2,SSR2,ZNF511
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 EXOSC1


There's no related Drug.
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Cross referenced IDs for EXOSC1
* 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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