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 PTEN

Basic gene info.	Gene symbol	PTEN
	Gene name	phosphatase and tensin homolog
	Synonyms	10q23del\|BZS\|CWS1\|DEC\|GLM2\|MHAM\|MMAC1\|PTEN1\|TEP1
	Cytomap	UCSC genome browser: 10q23.3
	Genomic location	chr10 :89623194-89728532
	Type of gene	protein-coding
	RefGenes	NM_000314.4,
	Ensembl id	ENSG00000171862
	Description	MMAC1 phosphatase and tensin homolog deleted on chromosome 10mitochondrial PTENalphamitochondrial phosphatase and tensin protein alphamutated in multiple advanced cancers 1phosphatase and tensin-like proteinphosphatidylinositol 3,4,5-trisphosphate 3-
	Modification date	20141222
dbXrefs	MIM : 601728
	HGNC : HGNC
	HPRD : 03431
Protein	UniProt: P60484 go to UniProt's Cross Reference DB Table
Expression	CleanEX: HS_PTEN
	BioGPS: 5728
	Gene Expression Atlas: ENSG00000171862
	The Human Protein Atlas: ENSG00000171862
Pathway	NCI Pathway Interaction Database: PTEN
	KEGG: PTEN
	REACTOME: PTEN
	ConsensusPathDB
	Pathway Commons: PTEN
Metabolism	MetaCyc: PTEN
	HUMANCyc: PTEN
Regulation	Ensembl's Regulation: ENSG00000171862
	miRBase: chr10 :89,623,194-89,728,532
	TargetScan: NM_000314
	cisRED: ENSG00000171862
Context	iHOP: PTEN
	cancer metabolism search in PubMed: PTEN
	UCL Cancer Institute: PTEN
Assigned class in ccmGDB	A - This gene has a literature evidence and it belongs to cancer gene.
References showing role of PTEN in cancer cell metabolism	1. Liang H, He S, Yang J, Jia X, Wang P, et al. (2014) PTENα, a PTEN isoform translated through alternative initiation, regulates mitochondrial function and energy metabolism. Cell metabolism 19: 836-848. go to article 2. Vignarajan S, Xie C, Yao M, Sun Y, Simanainen U, et al. (2014) Loss of PTEN stabilizes the lipid modifying enzyme cytosolic phospholipase A2α via AKT in prostate cancer cells. Oncotarget 5: 6289. go to article 3. Ciuffreda L, Falcone I, Incani UC, Del Curatolo A, Conciatori F, et al. (2014) PTEN expression and function in adult cancer stem cells and prospects for therapeutic targeting. Advances in biological regulation 56: 66-80. go to article 4. Morani F, Phadngam S, Follo C, Titone R, Thongrakard V, et al. (2014) PTEN deficiency and mutant p53 confer glucose-addiction to thyroid cancer cells: impact of glucose depletion on cell proliferation, cell survival, autophagy and cell migration. Genes & cancer 5: 226. go to article

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

Cancer Description
Cancer	CGAP: PTEN
	Familial Cancer Database: PTEN

* 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 BRCA ⁶, GBM ⁷, HNSC ⁸, KIRC ⁹, LUSC ¹⁰, MEL ¹¹, UCEC ¹², STAD ¹³, SKCM ¹⁴, THCA ¹⁵, GBM ¹⁶,	Therapeutic Vulnerabilities in Cancer¹⁷

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,
6 http://www.nature.com/nature/journal/v490/n7418/full/nature11412.html,
7 http://www.sciencedirect.com/science/article/pii/S0092867413012087,
8 https://www.sciencemag.org/content/333/6046/1157,
9 http://www.nature.com/nature/journal/v499/n7456/full/nature12222.html,
10 http://www.nature.com/nature/journal/v489/n7417/full/nature11404.html,
11 http://www.nature.com/nature/journal/v505/n7484/full/nature12912.html,
12 http://www.nature.com/nature/journal/v497/n7447/full/nature12113.html,
13 http://www.nature.com/nature/journal/v513/n7517/full/nature13480.html,
14 http://www.sciencedirect.com/science/article/pii/S0092867415006340,
15 http://www.sciencedirect.com/science/article/pii/S0092867414012380,
16 http://www.nejm.org/doi/full/10.1056/NEJMoa1402121,
17Therapeutic Vulnerabilities in Cancer; http://cbio.mskcc.org/cancergenomics/statius/

Metabolic Pathway Description
KEGG_INOSITOL_PHOSPHATE_METABOLISM REACTOME_PHOSPHOLIPID_METABOLISM REACTOME_PI_METABOLISM REACTOME_METABOLISM_OF_LIPIDS_AND_LIPOPROTEINS

Others
OMIM	137800; phenotype. 153480; phenotype. 158350; phenotype. 176807; phenotype. 275355; phenotype. 276950; phenotype. 601728; gene. 605309; phenotype. 608089; phenotype. 612242; phenotype. 613028; phenotype.
Orphanet	109; Bannayan-Riley-Ruvalcaba syndrome. 137608; Segmental outgrowth - lipomatosis - arteriovenous malformation - epidermal nevus. 145; Hereditary breast and ovarian cancer syndrome. 201; Cowden syndrome. 210548; Macrocephaly-autism syndrome. 2969; Proteus-like syndrome. 65285; Lhermitte-Duclos disease. 67037; Squamous cell carcinoma of head and neck. 744; Proteus syndrome. 79076; Juvenile polyposis of infancy.
Disease	KEGG Disease: PTEN
	MedGen: PTEN (Human Medical Genetics with Condition)
	ClinVar: PTEN
Phenotype	MGI: PTEN (International Mouse Phenotyping Consortium)
Phenotype	PhenomicDB: PTEN

Mutations for PTEN

* 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

* 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'.

Sample	Symbol_a	Chr_a	Start_a	End_a	Symbol_b	Chr_b	Start_b	End_b
breast	PTEN	chr10	89674132	89674132	PTEN	chr10	89692150	89692150
central_nervous_system	PTEN	chr10	89632864	89632864	PTEN	chr10	89698055	89698055
large_intestine	PTEN	chr10	89652053	89652053		chr10	89742503	89742503
ovary	PTEN	chr10	89628896	89628916	RNLS	chr10	90086380	90086400
ovary	PTEN	chr10	89656370	89656390		chr8	137548339	137548359
ovary	PTEN	chr10	89680884	89680904	PTEN	chr10	89653540	89653560
ovary	PTEN	chr10	89702223	89702243	PTEN	chr10	89688327	89688347
pancreas	PTEN	chr10	89628315	89628335	PTEN	chr10	89630807	89630827
pancreas	PTEN	chr10	89675657	89675677	PTEN	chr10	89679930	89679950
pancreas	PTEN	chr10	89712749	89712769		chr10	90368868	90368888
prostate	PTEN	chr10	89625661	89627661	PCGF5	chr10	93000144	93002144
prostate	PTEN	chr10	89626272	89626272		chr10	91442825	91442825
prostate	PTEN	chr10	89627664	89629664		chr1	160692788	160694788
prostate	PTEN	chr10	89666290	89666290	PANK1	chr10	91339642	91339642
skin	PTEN	chr10	89700299	89700299	PTEN	chr10	89712341	89712341

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 PTEN 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
BI823499	SEC31A	1	459	4	83799881	83812291	PTEN	456	804	10	89725042	89725387
BG610830	PTEN	1	640	10	89725959	89726595	PEBP1	632	688	12	118582915	118582972

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	13	13		5		5	4		6		3		5	6	1
GAIN (# sample)				1		1	1
LOSS (# sample)	13	13		4		4	3		6		3		5	6	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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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=246

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Somatic Mutation Counts per Tissue in COSMIC data

Stat. for Non-Synonymous SNVs (# total SNVs=1833)	Stat. for Synonymous SNVs (# total SNVs=170)

Stat. for Deletions (# total SNVs=641)	Stat. for Insertions (# total SNVs=289)

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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
chr10:89692904-89692904	p.R130G	177
chr10:89692905-89692905	p.R130P	125
chr10:89717672-89717672	p.R233fs*25	98
chr10:89717775-89717775	p.K267fs*9	47
chr10:89711899-89711899	p.R173C	42
chr10:89720799-89720802	p.T319fs*1	37
chr10:89720817-89720817	p.N323fs*21	31
chr10:89624227-89725229	p.0?	28
chr10:89720817-89720818	p.N323fs*2	27
chr10:89720852-89720852	p.R335*	27

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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=60

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	8		207	51		3	2	8	1		7	6	2	1	2	8	12	1	88
# mutation	2	7		249	46		3	2	8	1		6	8	2	1	2	8	16	1	58
nonsynonymous SNV	2	7		174	46		3	2	8	1		6	8	2	1	2	8	12	1	55
synonymous SNV				77														4		3

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
chr10:89692905	p.R130Q	34
chr10:89692904	p.R130G	26
chr10:89725072	p.E352G	11
chr10:89692923	p.C136F	8
chr10:89720700	p.E284G	7
chr10:89692791	p.D116G	6
chr10:89692899	p.K128R	6
chr10:89692863	p.D92G	6
chr10:89692965	p.E150A	6
chr10:89653819	p.R161R	5

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 PTEN 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 PTEN

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.

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Protein Expression Plot (RPPA)

*RPPA protein expression data were extracted from TCPA (The Cancer Proteome Atlas). Normalized data based on replicated based normalization (RBN) was used to draw following figures.

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


ATAD1,ATF7,BMPR2,CREB1,DTWD2,FAM160B1,GNG12, KLLN,MFAP3,PJA2,PTEN,PTENP1,RFX7,SH3D19, SLK,SP1,TCF12,TM9SF3,WAPAL,ZEB1,ZNF484	ABHD5,ACER3,ACVR1C,ADH5,ADRBK2,AZI2,BNIP3L, CD302,CEPT1,COL4A3BP,EIF4EBP2,EPB41L4B,FAM13A,FOXN2, GNAI1,GPR180,KLLN,PTEN,PTENP1,SLC7A6,STON1

ATAD1,BTRC,WBP1L,CHUK,CPEB3,FAM160B1,FAM178A, GBF1,KLLN,PCGF5,PTEN,PTENP1,SEL1L,SH3PXD2A, SHOC2,SLK,SUFU,TCTN3,TNKS2,TRIM8,WAPAL	CNOT6L,COL4A3BP,CSNK2A1,CSNK2A3,HOXB5,LOC90110,METTL7A, NBR1,PHF3,PPP1R3D,PTEN,PTENP1,PTPRA,PUM2, RSBN1,RTN3,SATL1,SP3,STX6,TAB2,ZNF490

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 PTEN

Cross-referenced pharmacological DB IDs from Uniprot

DB Category	DB Name	DB's ID and Url link
Chemistry	BindingDB	P60484; -.
Chemistry	ChEMBL	CHEMBL2052032; -.
Organism-specific databases	PharmGKB	PA33942; -.
Organism-specific databases	CTD	5728; -.

Drug-Gene Interaction Network

* Gene Centered Interaction Network.

* Drug Centered Interaction Network.

DrugBank ID	Target Name	Drug Groups	Generic Name	Drug Centered Network	Drug Structure
DB00877	phosphatase and tensin homolog	approved; investigational	Sirolimus
DB00619	phosphatase and tensin homolog	approved	Imatinib
DB00201	phosphatase and tensin homolog	approved	Caffeine
DB00515	phosphatase and tensin homolog	approved	Cisplatin
DB01248	phosphatase and tensin homolog	approved; investigational	Docetaxel
DB00544	phosphatase and tensin homolog	approved	Fluorouracil
DB00650	phosphatase and tensin homolog	approved	Leucovorin
DB00848	phosphatase and tensin homolog	approved	Levamisole
DB01132	phosphatase and tensin homolog	approved; investigational	Pioglitazone
DB00412	phosphatase and tensin homolog	approved; investigational	Rosiglitazone

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Cross referenced IDs for PTEN

* 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