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 CERK
Basic gene info.Gene symbolCERK
Gene nameceramide kinase
SynonymsLK4|dA59H18.2|dA59H18.3|hCERK
CytomapUCSC genome browser: 22q13.31
Genomic locationchr22 :47080306-47134152
Type of geneprotein-coding
RefGenesNM_182661.1,
NM_022766.5,
Ensembl idENSG00000100422
Descriptionacylsphingosine kinaselipid kinase 4lipid kinase LK4
Modification date20141207
dbXrefs MIM : 610307
HGNC : HGNC
Ensembl : ENSG00000100422
HPRD : 09878
Vega : OTTHUMG00000150395
ProteinUniProt: Q8TCT0
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_CERK
BioGPS: 64781
Gene Expression Atlas: ENSG00000100422
The Human Protein Atlas: ENSG00000100422
PathwayNCI Pathway Interaction Database: CERK
KEGG: CERK
REACTOME: CERK
ConsensusPathDB
Pathway Commons: CERK
MetabolismMetaCyc: CERK
HUMANCyc: CERK
RegulationEnsembl's Regulation: ENSG00000100422
miRBase: chr22 :47,080,306-47,134,152
TargetScan: NM_182661
cisRED: ENSG00000100422
ContextiHOP: CERK
cancer metabolism search in PubMed: CERK
UCL Cancer Institute: CERK
Assigned class in ccmGDBA - This gene has a literature evidence and it belongs to cancer gene.
References showing role of CERK in cancer cell metabolism1. Payne AW, Pant DK, Pan TC, Chodosh LA (2014) Ceramide kinase promotes tumor cell survival and mammary tumor recurrence. Cancer Res 74: 6352-6363. doi: 10.1158/0008-5472.CAN-14-1292. pmid: 4285436. go to article
2. Bini F, Frati A, Garcia-Gil M, Battistini C, Granado M, et al. (2012) New signalling pathway involved in the anti-proliferative action of vitamin D(3) and its analogues in human neuroblastoma cells. A role for ceramide kinase. Neuropharmacology 63: 524-537. doi: 10.1016/j.neuropharm.2012.04.026. go to article

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

check002.gifOthers
OMIM 610307; gene.
Orphanet
DiseaseKEGG Disease: CERK
MedGen: CERK (Human Medical Genetics with Condition)
ClinVar: CERK
PhenotypeMGI: CERK (International Mouse Phenotyping Consortium)
PhenomicDB: CERK

Mutations for CERK
* 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 CERK related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
BX384993SGOL1157032021978720219842CERK65773224708030747081015
BF807731SERINC5913457953419979534327CERK129504224708075347081132

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         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=3

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=24)
Stat. for Synonymous SNVs
(# total SNVs=8)
Stat. for Deletions
(# total SNVs=5)
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
chr22:47091113-47091113p.R348Q2
chr22:47086002-47086002p.K477fs*>612
chr22:47085891-47085891p.V513V1
chr22:47095313-47095313p.L280L1
chr22:47086098-47086098p.?1
chr22:47108119-47108119p.E151Q1
chr22:47089354-47089354p.K366*1
chr22:47116881-47116881p.I58I1
chr22:47085909-47085909p.H507H1
chr22:47095356-47095356p.S266L1

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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  13  1 21 44  133 5
# mutation  13  1 21 44  134 5
nonsynonymous SNV  12  1 11 43  124 3
synonymous SNV   1    1   1   1  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
chr22:47085936p.S498S1
chr22:47095273p.A215T1
chr22:47116006p.H487N1
chr22:47085971p.E182K1
chr22:47095313p.T461A1
chr22:47116007p.I168I1
chr22:47086049p.R454R1
chr22:47095356p.K143N1
chr22:47116101p.V452A1
chr22:47086068p.P139S1

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 CERK 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 CERK

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

ADSL,BRD1,CERK,HIRA,IL17RA,JOSD1,KLF13,
LRP6,MLXIP,NUP50,OTUD3,PDXP,POLDIP3,PPARA,
RBFOX2,SBF1,MIEF1,TBC1D22A,TCF20,TNRC6B,ZBED4
ADA,ANKS6,ARHGEF2,BICD2,CERK,DUSP22,GAB3,
IL16,FOXD2-AS1,NINJ2,PHF19,PPP1R16B,PRELP,RASGRP2,
SH3BP5,SH3KBP1,STAMBPL1,STK38,TBC1D2B,VSIG10,ZDHHC18

AMIGO1,BMF,CERK,CYB561D1,ELF1,ENPP2,GGT7,
KCNAB2,KCTD7,LEF1,LOC100286793,NFATC2,ORAI2,PDS5B,
PHACTR2,RCBTB1,SETDB2,TM9SF2,TMEM47,TNS3,UBL3
ADPRHL1,ASB13,ASTE1,CERK,CYP4F12,DHRS11,FMO5,
HSD17B11,MYL5,PDXP,PIWIL2,RAB17,SLC25A34,SLC39A5,
SLC3A1,SNX24,TMEM116,TNNC2,TRAF4,ULK3,USH1C
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 CERK


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