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 GLB1
Basic gene info.Gene symbolGLB1
Gene namegalactosidase, beta 1
SynonymsEBP|ELNR1|MPS4B
CytomapUCSC genome browser: 3p21.33
Genomic locationchr3 :33038099-33138314
Type of geneprotein-coding
RefGenesNM_000404.2,
NM_001079811.1,NM_001135602.1,
Ensembl idENSG00000170266
Descriptionacid beta-galactosidasebeta-galactosidaseelastin receptor 1, 67kDalactase
Modification date20141219
dbXrefs MIM : 611458
HGNC : HGNC
Ensembl : ENSG00000170266
HPRD : 01975
Vega : OTTHUMG00000155781
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_GLB1
BioGPS: 2720
Gene Expression Atlas: ENSG00000170266
The Human Protein Atlas: ENSG00000170266
PathwayNCI Pathway Interaction Database: GLB1
KEGG: GLB1
REACTOME: GLB1
ConsensusPathDB
Pathway Commons: GLB1
MetabolismMetaCyc: GLB1
HUMANCyc: GLB1
RegulationEnsembl's Regulation: ENSG00000170266
miRBase: chr3 :33,038,099-33,138,314
TargetScan: NM_000404
cisRED: ENSG00000170266
ContextiHOP: GLB1
cancer metabolism search in PubMed: GLB1
UCL Cancer Institute: GLB1
Assigned class in ccmGDBC

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Phenotypic Information for GLB1(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: GLB1
Familial Cancer Database: GLB1
* 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_GALACTOSE_METABOLISM
KEGG_SPHINGOLIPID_METABOLISM
REACTOME_GLYCOSPHINGOLIPID_METABOLISM
REACTOME_PHOSPHOLIPID_METABOLISM
REACTOME_SPHINGOLIPID_METABOLISM
REACTOME_METABOLISM_OF_LIPIDS_AND_LIPOPROTEINS
REACTOME_METABOLISM_OF_CARBOHYDRATES

check002.gifOthers
OMIM
Orphanet
DiseaseKEGG Disease: GLB1
MedGen: GLB1 (Human Medical Genetics with Condition)
ClinVar: GLB1
PhenotypeMGI: GLB1 (International Mouse Phenotyping Consortium)
PhenomicDB: GLB1

Mutations for GLB1
* 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
There's no inter-chromosomal structural variation.
- For Intra-chromosomal Variations
* Intra-chromosomal variantions includes 'intrachromosomal amplicon to amplicon', 'intrachromosomal amplicon to non-amplified dna', 'intrachromosomal deletion', 'intrachromosomal fold-back inversion', 'intrachromosomal inversion', 'intrachromosomal tandem duplication', 'Intrachromosomal unknown type', 'intrachromosomal with inverted orientation', 'intrachromosomal with non-inverted orientation'.
SampleSymbol_aChr_aStart_aEnd_aSymbol_bChr_bStart_bEnd_b
ovaryGLB1chr33311915033119170GLB1chr33311990733119927
ovaryGLB1chr33311915033119170GLB1chr33311991133119931
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 GLB1 related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
DA524376RPL281366195589730055899416GLB136651033311406333114206
BF931760DST1824065632384356324065GLB123235833309340133095013
XX000016GLB119133305554633055636CMTM78820933248333032483451
AU125113RBPJ3827842643511926435359GLB127879433306574333138610

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 # sample1                
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=4

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=41)
Stat. for Synonymous SNVs
(# total SNVs=12)
Stat. for Deletions
(# total SNVs=1)
Stat. for Insertions
(# total SNVs=0)
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
chr3:33138544-33138544p.L12L4
chr3:33114174-33114174p.Y36C3
chr3:33055752-33055752p.T510T2
chr3:33093386-33093386p.A301A2
chr3:33093430-33093430p.E287K2
chr3:33038660-33038660p.T637T2
chr3:33038745-33038745p.M609T2
chr3:33099680-33099680p.G212R2
chr3:33038747-33038747p.L608L2
chr3:33099691-33099691p.R208H1

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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
# sample32 11  3 4   11  86 7
# mutation32 10  3 4   11  96 7
nonsynonymous SNV22 8  2 4    1  64 6
synonymous SNV1  2  1     1   32 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
chr3:33038745p.M478T,GLB12
chr3:33038787p.P382L,GLB11
chr3:33110348p.E156K,GLB11
chr3:33058237p.R49H,GLB11
chr3:33093395p.T379T,GLB11
chr3:33038793p.L236H,GLB11
chr3:33110382p.R49C,GLB11
chr3:33058289p.Y36C,GLB11
chr3:33093430p.S372F,GLB11
chr3:33038803p.G231G,GLB11

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 GLB1 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 GLB1

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

ANO10,CNOT10,CRTAP,CTSA,GGCX,GLB1,HEXB,
LAMP2,LGMN,MYD88,NGLY1,NOMO1,OXNAD1,OXSM,
PDCD6IP,PLBD2,PSAP,SLC31A1,STT3B,TMPPE,ZDHHC3
ACP2,ATG7,C1orf85,CYB561D2,GALNS,GBA,GLB1,
GPR137B,GRN,HEXA,HM13,MYD88,NAGA,PDIA3P1,
PI4K2A,PIGT,RPN2,SUSD1,TBXAS1,TMEM206,TTYH3

ARSE,TCAIM,CAPN7,CASP6,CAT,CMC1,CMTM8,
CRBN,GLB1,GPD1L,HSD17B4,NAALADL2,OGG1,PPARG,
PRSS23,RPP14,SACM1L,SETMAR,SLC35F5,STT3B,TMED5
CCNI2,CPT2,DCAF12,EIF2AK1,FUCA1,GLB1,GOLPH3L,
IDH1,IL20RA,LDLRAP1,LIMK2,MFSD1,MTIF2,NGLY1,
NIPAL1,NUDT16P1,SIAE,TBC1D14,TMEM87A,VAV3,WIPI1
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 GLB1


There's no related Drug.
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Cross referenced IDs for GLB1
* 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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