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 CD38
Basic gene info.Gene symbolCD38
Gene nameCD38 molecule
SynonymsADPRC 1|T10
CytomapUCSC genome browser: 4p15
Genomic locationchr4 :15779930-15850706
Type of geneprotein-coding
RefGenesNM_001775.2,
Ensembl idENSG00000004468
Description2'-phospho-ADP-ribosyl cyclase2'-phospho-ADP-ribosyl cyclase/2'-phospho-cyclic-ADP-ribose transferase2'-phospho-cyclic-ADP-ribose transferaseADP-ribosyl cyclase 1ADP-ribosyl cyclase/cyclic ADP-ribose hydrolase 1CD38 antigen (p45)NAD(+) nucleosidase
Modification date20141222
dbXrefs MIM : 107270
HGNC : HGNC
HPRD : 00116
ProteinUniProt: P28907
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_CD38
BioGPS: 952
Gene Expression Atlas: ENSG00000004468
The Human Protein Atlas: ENSG00000004468
PathwayNCI Pathway Interaction Database: CD38
KEGG: CD38
REACTOME: CD38
ConsensusPathDB
Pathway Commons: CD38
MetabolismMetaCyc: CD38
HUMANCyc: CD38
RegulationEnsembl's Regulation: ENSG00000004468
miRBase: chr4 :15,779,930-15,850,706
TargetScan: NM_001775
cisRED: ENSG00000004468
ContextiHOP: CD38
cancer metabolism search in PubMed: CD38
UCL Cancer Institute: CD38
Assigned class in ccmGDBA - This gene has a literature evidence and it belongs to cancer gene.
References showing role of CD38 in cancer cell metabolism1. Vaisitti T, Audrito V, Serra S, Buonincontri R, Sociali G, et al. (2015) The enzymatic activities of CD38 enhance CLL growth and trafficking: implications for therapeutic targeting. Leukemia 29: 356-368. doi: 10.1038/leu.2014.207. go to article
2. Liao S, Xiao S, Zhu G, Zheng D, He J, et al. (2014) CD38 is highly expressed and affects the PI3K/Akt signaling pathway in cervical cancer. Oncol Rep 32: 2703-2709. doi: 10.3892/or.2014.3537. go to article

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Phenotypic Information for CD38(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: CD38
Familial Cancer Database: CD38
* 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_NICOTINATE_AND_NICOTINAMIDE_METABOLISM

check002.gifOthers
OMIM 107270; gene.
Orphanet
DiseaseKEGG Disease: CD38
MedGen: CD38 (Human Medical Genetics with Condition)
ClinVar: CD38
PhenotypeMGI: CD38 (International Mouse Phenotyping Consortium)
PhenomicDB: CD38

Mutations for CD38
* 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
* 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
large_intestineCD38chr41581644515816445KCNIP4chr42158429821584298
large_intestineCD38chr41582256815822568chr42310048623100486
ovaryCD38chr41580692915806949chr89128209791282117
ovaryCD38chr41581308715813107chr41545709715457117
ovaryCD38chr41581378015813800PCDH7chr43085960830859628
pancreasCD38chr41580925515809275CD38chr41580299515803015
pancreasCD38chr41581552815815548chr41591261415912634
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 CD38 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 # 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=3

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=31)
Stat. for Synonymous SNVs
(# total SNVs=9)
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
chr4:15826541-15826541p.Q134R2
chr4:15842076-15842076p.D252Y2
chr4:15842113-15842113p.S264L2
chr4:15835868-15835868p.W176*2
chr4:15780076-15780076p.K13K1
chr4:15839763-15839763p.R212C1
chr4:15841733-15841733p.E248E1
chr4:15818139-15818139p.V80A1
chr4:15839767-15839777p.S213fs*131
chr4:15780091-15780091p.L18L1

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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=3

Point Mutation/ Tissue ID1234567891011121314151617181920
# sample 3 51 3 1  622  2516
# mutation 3 61 3 1  722  4518
nonsynonymous SNV 3 41 2 1  522  2216
synonymous SNV   2  1    2    23 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
chr4:15842113p.Q134R2
chr4:15818249p.V117I2
chr4:15826541p.S264L2
chr4:15780113p.G27G1
chr4:15835888p.A132A1
chr4:15842114p.S264S1
chr4:15780118p.S274F1
chr4:15818253p.I34I1
chr4:15835919p.E299K1
chr4:15842143p.P44L1

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 CD38 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 CD38

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

ADAM6,NUGGC,CCR2,CCR5,CD38,CXCR6,FASLG,
FCRL5,IL21R,IL2RG,IRF4,ITGB7,LAX1,PIM2,
POU2AF1,PRF1,PTPN7,SLAMF1,SLAMF7,TBX21,TNFRSF17
ABCB4,AGMAT,ART3,CACNA2D3,CD38,CHRNB3,COL19A1,
DPF3,E2F8,FAM78A,FLJ41941,HPCAL4,IL32,JSRP1,
MEF2C,MUSK,P2RX5,PHTF2,PRKCQ,SHD,SLCO5A1

ARHGAP25,ARHGAP30,SCIMP,CD226,CD2,CD38,GIMAP5,
IL10RA,IL21R,ITGAL,KCNA3,LAX1,MYO1G,P2RY10,
PTPRC,SASH3,SIRPG,SLAMF1,SLAMF7,TAGAP,WAS
ABI3,CD38,CD53,GNGT2,HCLS1,IL12RB1,IL2RB,
KLHDC7B,LAX1,LCP1,LCP2,LILRB1,MZB1,NLRP7,
PIM2,SEMA4D,SH2D2A,SLAMF1,SLAMF7,SNX20,TXNDC5
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 CD38


There's no related Drug.
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Cross referenced IDs for CD38
* 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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