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 SMPD3
Basic gene info.Gene symbolSMPD3
Gene namesphingomyelin phosphodiesterase 3, neutral membrane (neutral sphingomyelinase II)
SynonymsNSMASE2
CytomapUCSC genome browser: 16q22.1
Genomic locationchr16 :68392229-68482409
Type of geneprotein-coding
RefGenesNM_018667.3,
Ensembl idENSG00000103056
DescriptionnSMase-2neutral sphingomyelinase 2neutral sphingomyelinase IIsphingomyelin phosphodiesterase 3
Modification date20141207
dbXrefs MIM : 605777
HGNC : HGNC
Ensembl : ENSG00000103056
HPRD : 16154
Vega : OTTHUMG00000137559
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_SMPD3
BioGPS: 55512
Gene Expression Atlas: ENSG00000103056
The Human Protein Atlas: ENSG00000103056
PathwayNCI Pathway Interaction Database: SMPD3
KEGG: SMPD3
REACTOME: SMPD3
ConsensusPathDB
Pathway Commons: SMPD3
MetabolismMetaCyc: SMPD3
HUMANCyc: SMPD3
RegulationEnsembl's Regulation: ENSG00000103056
miRBase: chr16 :68,392,229-68,482,409
TargetScan: NM_018667
cisRED: ENSG00000103056
ContextiHOP: SMPD3
cancer metabolism search in PubMed: SMPD3
UCL Cancer Institute: SMPD3
Assigned class in ccmGDBC

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Phenotypic Information for SMPD3(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: SMPD3
Familial Cancer Database: SMPD3
* 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
Orphanet
DiseaseKEGG Disease: SMPD3
MedGen: SMPD3 (Human Medical Genetics with Condition)
ClinVar: SMPD3
PhenotypeMGI: SMPD3 (International Mouse Phenotyping Consortium)
PhenomicDB: SMPD3

Mutations for SMPD3
* 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
ovarySMPD3chr166842031868420338ESRP2chr166826490968264929
ovarySMPD3chr166842069368420713chr89933021299330232
ovarySMPD3chr166844752668447546SMPD3chr166845104168451061
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 SMPD3 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 # sample1  1  1 2 2      
GAIN (# sample)1  1    2        
LOSS (# sample)      1   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=38)
Stat. for Synonymous SNVs
(# total SNVs=12)
Stat. for Deletions
(# total SNVs=1)
Stat. for Insertions
(# total SNVs=1)

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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
chr16:68405022-68405022p.A355T3
chr16:68395565-68395565p.G603S2
chr16:68398669-68398669p.D514N2
chr16:68405993-68405993p.V31G2
chr16:68406042-68406042p.A15T2
chr16:68398702-68398702p.A503T2
chr16:68395646-68395646p.E576K2
chr16:68405587-68405587p.Q166H2
chr16:68404844-68404844p.P414L2
chr16:68405864-68405864p.S74L2

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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
# sample11 8  2    541 11412 6
# mutation11 8  2    541 11913 7
nonsynonymous SNV11 5  1    231 1109 6
synonymous SNV   3  1    31   94 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
chr16:68405851p.A78A2
chr16:68397447p.A470S1
chr16:68405291p.L357L1
chr16:68404909p.G231E1
chr16:68405595p.S74S1
chr16:68405050p.I457I1
chr16:68405944p.A355T1
chr16:68398674p.H219R1
chr16:68405331p.A61V1
chr16:68404917p.V444L1

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 SMPD3 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 SMPD3

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

AP3B2,BSN,CACNA2D2,CHRNB2,DISP2,FAM155B,HCN2,
LRTM2,MAPK8IP1,PHF21B,PSD,RTBDN,RUNDC3A,SCAMP5,
SEZ6L2,SMPD3,SPTBN4,SYP,TMEM145,TMEM198,UNC13A
SH3D21,C20orf96,CELSR1,CHDH,DFNB31,FLNB,GRTP1,
HKR1,IFT140,IKBKB,IL17RB,DNAAF1,LRRC56,MLPH,
MORN1,NINL,PSD4,SFI1,SIPA1L3,SMPD3,VWA2

BCAS1,CACFD1,CAPN5,CARD10,CDHR5,CGN,FAM63A,
IL17RE,KIAA1161,LRRC66,MAPK3,MYO7B,PDCD4,PIK3C2B,
PLXNA2,RNF103,SLC44A4,SMPD3,TJP3,TMEM131,TTC22
BAIAP2L2,CES2,DCAF11,EPS8L2,EPS8L3,FAM109A,GAL3ST1,
GUCY2C,HNF1A,KIAA2013,MICAL1,MOGAT2,MYO1A,MYO7B,
NGEF,SMPD3,USH1C,USP37,VIL1,ZNF664,ZSWIM5
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 SMPD3
check002.gifCross-referenced pharmacological DB IDs from Uniprot
DB CategoryDB NameDB's ID and Url link

check002.gifDrug-Gene Interaction Network
* Gene Centered Interaction Network.
* Drug Centered Interaction Network.
DrugBank IDTarget NameDrug GroupsGeneric NameDrug Centered NetworkDrug Structure
DB00144sphingomyelin phosphodiesterase 3, neutral membrane (neutral sphingomyelinase II)approved; nutraceuticalPhosphatidylserine
DB00143sphingomyelin phosphodiesterase 3, neutral membrane (neutral sphingomyelinase II)approved; nutraceuticalGlutathione


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Cross referenced IDs for SMPD3
* 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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