Cancer Cell Metabolism Database ~~ Bioinformatics and Systems Medicine Laboratory ~~

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 SGMS1

Basic gene info.	Gene symbol	SGMS1
	Gene name	sphingomyelin synthase 1
	Synonyms	MOB\|MOB1\|SMS1\|TMEM23\|hmob33
	Cytomap	UCSC genome browser: 10q11.2
	Genomic location	chr10 :52065344-52383737
	Type of gene	protein-coding
	RefGenes	NM_147156.3,
	Ensembl id	ENSG00000198964
	Description	medulla oblongata-derived proteinphosphatidylcholine:ceramide cholinephosphotransferase 1protein Mobtransmembrane protein 23
	Modification date	20141207
dbXrefs	MIM : 611573
	HGNC : HGNC
	Ensembl : ENSG00000198964
	HPRD : 18203
	Vega : OTTHUMG00000018231
Protein	UniProt: go to UniProt's Cross Reference DB Table
Expression	CleanEX: HS_SGMS1
	BioGPS: 259230
	Gene Expression Atlas: ENSG00000198964
	The Human Protein Atlas: ENSG00000198964
Pathway	NCI Pathway Interaction Database: SGMS1
	KEGG: SGMS1
	REACTOME: SGMS1
	ConsensusPathDB
	Pathway Commons: SGMS1
Metabolism	MetaCyc: SGMS1
	HUMANCyc: SGMS1
Regulation	Ensembl's Regulation: ENSG00000198964
	miRBase: chr10 :52,065,344-52,383,737
	TargetScan: NM_147156
	cisRED: ENSG00000198964
Context	iHOP: SGMS1
	cancer metabolism search in PubMed: SGMS1
	UCL Cancer Institute: SGMS1
Assigned class in ccmGDB	C

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Phenotypic Information for SGMS1(metabolism pathway, cancer, disease, phenome)

Cancer Description
Cancer	CGAP: SGMS1
	Familial Cancer Database: SGMS1

* 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/

Metabolic Pathway Description
KEGG_SPHINGOLIPID_METABOLISM REACTOME_PHOSPHOLIPID_METABOLISM REACTOME_SPHINGOLIPID_METABOLISM REACTOME_METABOLISM_OF_LIPIDS_AND_LIPOPROTEINS

Others
OMIM
Orphanet
Disease	KEGG Disease: SGMS1
	MedGen: SGMS1 (Human Medical Genetics with Condition)
	ClinVar: SGMS1
Phenotype	MGI: SGMS1 (International Mouse Phenotyping Consortium)
Phenotype	PhenomicDB: SGMS1

Mutations for SGMS1

* 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.

Structural Variants in COSMIC : go to COSMIC mutation histogram

- Statistics for Tissue and Mutation type

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- 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'.

Sample	Symbol_a	Chr_a	Start_a	End_a	Symbol_b	Chr_b	Start_b	End_b
breast	SGMS1	chr10	52149413	52149813	SGMS1	chr10	52151093	52151493
breast	SGMS1	chr10	52233801	52233801	SGMS1	chr10	52240097	52240097

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)

Related fusion transcripts : go to Chitars2.0

* From mRNA Sanger sequences, Chitars2.0 arranged chimeric transcripts. This table shows SGMS1 related fusion information.

ID	Head Gene						Tail Gene
Accession	Gene_a	qStart_a	qEnd_a	Chromosome_a	tStart_a	tEnd_a	Gene_a	qStart_a	qEnd_a	Chromosome_a	tStart_a	tEnd_a
BF836346	EPB41L5	42	427	2	120857824	120885494	SGMS1	419	532	10	52195666	52195779
BF917180	SGMS1	18	123	10	52066718	52066823	TUBGCP2	118	663	10	135098969	135103347
BF845226	MLLT10	16	447	10	22023141	22023574	SGMS1	436	696	10	52066624	52066888

Other DBs for Structural Variants

Structural Variants in Ensembl: go to Ensembl Structural variation

Structural Variants in dbVar: go to dbVar

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Copy Number Variations in COSMIC : go to COSMIC mutation CNV/Expr

Mutation type/ Tissue ID	brca	cns	cerv	endome	haematopo	kidn	Lintest	liver	lung	ns	ovary	pancre	prost	skin	stoma	thyro	urina
Total # sample	1	2	1			1			2		1		1		2
GAIN (# sample)	1								1
LOSS (# sample)		2	1			1			1		1		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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SNV 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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Somatic Mutation Counts per Tissue in COSMIC data

Stat. for Non-Synonymous SNVs (# total SNVs=28)	Stat. for Synonymous SNVs (# total SNVs=10)

Stat. for Deletions (# total SNVs=1)	Stat. for Insertions (# total SNVs=0)
	There's no inserted snv.

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Top 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 position	Mutation(aa)	Unique sampleID count
chr10:52103748-52103748	p.D43N	2
chr10:52103484-52103484	p.E131*	2
chr10:52103662-52103662	p.H71H	2
chr10:52103403-52103403	p.E158K	2
chr10:52103686-52103686	p.M63I	2
chr10:52103696-52103696	p.L60R	2
chr10:52066960-52066960	p.W395L	2
chr10:52103418-52103418	p.I153F	2
chr10:52103437-52103437	p.F146F	2
chr10:52087029-52087029	p.R226Q	2

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SNV 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 ID	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20
# sample		2		5			2			1		2	3	1			14	4		6
# mutation		2		6			2			1		2	3	1			19	4		6
nonsynonymous SNV		1		4			1			1		2	3				12	3		6
synonymous SNV		1		2			1							1			7	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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Top 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 Position	Mutation(aa)	Unique sampleID count
chr10:52103403	p.M63I	2
chr10:52103686	p.E158K	2
chr10:52071042	p.Y280C	1
chr10:52103623	p.Q201L	1
chr10:52087030	p.H71H	1
chr10:52103387	p.G278G	1
chr10:52071078	p.I193I	1
chr10:52103662	p.T271I	1
chr10:52087052	p.P168L	1
chr10:52071083	p.S53Y	1

Other 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

Copy Number for SGMS1 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 SGMS1

Gene 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.

Differential 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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CNV 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

Co-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


ANO6,CCDC186,CAB39,ERCC6,FAM160B1,HERC4,IPMK, MOB1A,NUMB,PARG,PPP2R5E,PRKAA1,REEP3,SEC24A, SGMS1,SLC10A7,SLC30A7,SLC35F5,TC2N,TRIP11,ZBTB21	ACTR2,AGPS,CCNYL1,CLIC4,CPNE8,CSGALNACT2,EIF5A2, EVI5,EXOC5,GNG12,RAB8B,RBMS1,RECQL,SDCBP, SEPT7,SGMS1,SGPP1,SGTB,TMEM167A,TMX3,VAMP7

GSKIP,CDC42EP1,DAPP1,FUT8,LGR4,LIMA1,LMO4, MBP,PDLIM5,RAB27B,REEP3,RNF19B,SGMS1,SGMS2, SLC41A2,SOCS6,SRD5A3,STS,TC2N,TNFAIP8,TNFRSF11A	ANKRD29,ANO6,B3GALT2,C4orf3,LINC00242,CYP2U1,KPNA5, KRT222,UBA6-AS1,MAGEH1,MCFD2,OSBPL8,SEC22C,SGMS1, SHF,SRR,ST7,STK3,TMX4,ZNF16,ZNF639

Co-Expressed gene's Protein-protein interaction Network Plot

: Open all plots for all cancer types

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Interacting 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 SGMS1

There's no related Drug.

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Cross referenced IDs for SGMS1

* 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