|
Phenotypic Information (metabolism pathway, cancer, disease, phenome) | |
Gene-Gene Network Information: Co-Expression Network, Interacting Genes & KEGG | |
Gene Summary for EPT1 |
Top |
Phenotypic Information for EPT1(metabolism pathway, cancer, disease, phenome) |
Cancer Description | |
Cancer | CGAP: EPT1 |
Familial Cancer Database: EPT1 |
* This gene is included in those cancer gene databases. |
Oncogene 1 | Significant driver gene in |
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 | |
REACTOME_PHOSPHOLIPID_METABOLISM REACTOME_METABOLISM_OF_LIPIDS_AND_LIPOPROTEINS |
Others | |
OMIM | |
Orphanet | |
Disease | KEGG Disease: EPT1 |
MedGen: EPT1 (Human Medical Genetics with Condition) | |
ClinVar: EPT1 | |
Phenotype | MGI: EPT1 (International Mouse Phenotyping Consortium) |
PhenomicDB: EPT1 |
Mutations for EPT1 |
* 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 | Top |
- 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 |
ovary | EPT1 | chr2 | 26592390 | 26592410 | EPT1 | chr2 | 26595809 | 26595829 |
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 EPT1 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 |
AW602498 | EPT1 | 5 | 85 | 2 | 26611887 | 26611968 | LARP1 | 81 | 233 | 5 | 154196053 | 154196205 |
Other DBs for Structural Variants |
Top |
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 |   |   |   |   |   |   |   |   | |||
GAIN (# sample) |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |||
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) |
Top |
SNV Counts per Each Loci in COSMIC data: go to COSMIC point mutation |
|
Top |
Somatic Mutation Counts per Tissue in COSMIC data |
Stat. for Non-Synonymous SNVs (# total SNVs=5) | (# total SNVs=0) |
(# total SNVs=0) | (# total SNVs=0) |
Top |
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 |
chr2:26590084-26590084 | p.T102T | 2 |
chr2:26587719-26587719 | p.A49V | 1 |
chr2:26587769-26587769 | p.L66M | 1 |
chr2:26596385-26596385 | p.F154S | 1 |
chr2:26597961-26597961 | p.Y209Y | 1 |
chr2:26606214-26606214 | p.R244G | 1 |
chr2:26607905-26607905 | p.F270F | 1 |
chr2:26609336-26609336 | p.E343Q | 1 |
chr2:26611949-26611949 | p.E391G | 1 |
Top |
SNV Counts per Each Loci in TCGA data |
|
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 |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |
# mutation |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |
nonsynonymous SNV |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |
synonymous SNV |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |
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]) |
Top |
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 |
Other DBs for Point Mutations |
Copy Number for EPT1 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] |
Top |
Gene Expression for EPT1 |
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)) |
Top |
CNV vs Gene Expression Plot |
* This plots show the correlation between CNV and gene expression. |
Top |
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 |
ASAP2,BIRC6,CEBPZ,CLOCK,EPT1,GMCL1,LRPPRC, MPHOSPH9,MRPL19,NAA25,PDS5A,PTPN11,PUM2,RAB10, SBNO1,SLC30A6,SMEK2,SPAST,STRN,WDR43,XPO1 | SPICE1,CNOT6,DHX15,EPT1,FNBP1L,GSTCD,HOOK1, KDM5B,LRBA,MARVELD2,OCLN,PIGN,PRLR,RCAN3, SLC9A7,SMARCC1,TEX9,NDC1,TMEM87B,TRPS1,ZSWIM5 |
ANAPC1,ATAD5,BUB1,CENPO,DDX1,DDX18,EPT1, HSPD1,LRPPRC,MRPL19,MRPL30,MTIF2,NCAPH,NCL, NOL10,NOLC1,PNPT1,POLR1B,PTCD3,WDR43,XPO1 | AGFG1,C11orf24,SUCO,CA13,CDHR2,CLCN5,ENTPD7, EPT1,RMDN3,FLVCR1,HNF4G,LPGAT1,MFSD2A,MOCOS, MYO1A,PITPNA,PLCB3,SEC24A,SLC25A44,TNFRSF10B,USP37 |
Co-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 |
Top |
Interacting Genes (from Pathway Commons) |
Top |
Pharmacological Information for EPT1 |
There's no related Drug. |
Top |
Cross referenced IDs for EPT1 |
* We obtained these cross-references from Uniprot database. It covers 150 different DBs, 18 categories. http://www.uniprot.org/help/cross_references_section |
Copyright © 2016-Present - The Univsersity of Texas Health Science Center at Houston @ |