Cancer Cell Metabolism Gene Database

  Cancer Cell Metabolism Gene DB

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Bioinformatics and Systems Medicine Laboratory Bioinformatics and Systems Medicine Laboratory

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 MED14
Basic gene info.Gene symbolMED14
Gene namemediator complex subunit 14
SynonymsCRSP150|CRSP2|CSRP|CXorf4|DRIP150|EXLM1|RGR1|TRAP170
CytomapUCSC genome browser: Xp11.4
Genomic locationchrX :40508794-40594804
Type of geneprotein-coding
RefGenesNM_004229.3,
Ensembl idENSG00000180182
DescriptionARC150CRSP complex subunit 2RGR1 homologactivator-recruited cofactor 150 kDa componentcofactor required for Sp1 transcriptional activation, subunit 2 (150kD)hRGR1human homolog of yeast RGR1mediator of RNA polymerase II transcription subunit 14thyr
Modification date20141207
dbXrefs MIM : 300182
HGNC : HGNC
Ensembl : ENSG00000180182
HPRD : 02172
Vega : OTTHUMG00000024107
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_MED14
BioGPS: 9282
Gene Expression Atlas: ENSG00000180182
The Human Protein Atlas: ENSG00000180182
PathwayNCI Pathway Interaction Database: MED14
KEGG: MED14
REACTOME: MED14
ConsensusPathDB
Pathway Commons: MED14
MetabolismMetaCyc: MED14
HUMANCyc: MED14
RegulationEnsembl's Regulation: ENSG00000180182
miRBase: chrX :40,508,794-40,594,804
TargetScan: NM_004229
cisRED: ENSG00000180182
ContextiHOP: MED14
cancer metabolism search in PubMed: MED14
UCL Cancer Institute: MED14
Assigned class in ccmGDBC

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Phenotypic Information for MED14(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: MED14
Familial Cancer Database: MED14
* 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
REACTOME_METABOLISM_OF_LIPIDS_AND_LIPOPROTEINS

check002.gifOthers
OMIM
Orphanet
DiseaseKEGG Disease: MED14
MedGen: MED14 (Human Medical Genetics with Condition)
ClinVar: MED14
PhenotypeMGI: MED14 (International Mouse Phenotyping Consortium)
PhenomicDB: MED14

Mutations for MED14
* 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
There's no structural variation information in COSMIC data for this gene.

check002.gifRelated fusion transcripts : go to Chitars2.0
* From mRNA Sanger sequences, Chitars2.0 arranged chimeric transcripts. This table shows MED14 related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
BM796903MED141264X4051879740522377CDR2L263465177300124673001448

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
There's no copy number variation information in COSMIC data for this gene.

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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=6

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=96)
Stat. for Synonymous SNVs
(# total SNVs=22)
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
chr23:40531148-40531148p.N1033S3
chr23:40514312-40514312p.F1325L2
chr23:40518692-40518692p.F1284L2
chr23:40551443-40551443p.R658W2
chr23:40551483-40551483p.F644F2
chr23:40556392-40556392p.L512L2
chr23:40573155-40573155p.K176T2
chr23:40560408-40560408p.?2
chr23:40560431-40560431p.W492C2
chr23:40514248-40514248p.A1346V2

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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
# sample23 151 5 4 1542 154 19
# mutation23 141 5 4 1542 154 26
nonsynonymous SNV 2 13  4 4 1322 123 22
synonymous SNV21 11 1    22   31 4
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
chrX:40573155p.F1325L2
chrX:40551443p.F1284L2
chrX:40514312p.R1222I2
chrX:40518692p.R225L2
chrX:40572273p.A1346V2
chrX:40514248p.K176R2
chrX:40522196p.R658W2
chrX:40541160p.A1018T1
chrX:40514249p.R614C1
chrX:40522214p.K384I1

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 MED14 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 MED14

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

ANKIB1,APOOL,BIRC6,CXorf38,DDX3X,HUWE1,ITCH,
KDM6A,LOC284441,LRRC58,MAP3K2,MED14,NCKAP1,RIF1,
SCYL2,SMC1A,STRN,TCEANC,TXLNG,USP9X,ZNF81
AHCYL2,C4orf29,CLASP2,CPEB3,CUL5,DENND2C,FSD1L,
GUF1,IBTK,IPO7,MED14,NEDD4,OTUD4,PYGO1,
TNKS2,TPP2,UBE3A,USP28,USP38,ZBTB43,ZNF41

ATP6AP2,CASK,CXorf38,DDX3X,DIAPH2,KDM5C,KDM6A,
MBTPS2,MED14,JADE3,PHF8,POLA1,RBBP7,SCML1,
SMC1A,SYAP1,TAB3,TCEANC,TXLNG,UBA1,USP9X
AP1G1,ARFGEF1,ARHGAP32,PRR14L,CDK13,CNOT1,DNAJC16,
DSP,FZD5,HIPK2,AREL1,LARP4B,MAGI3,MED14,
NBEAL1,PLCE1,PTPRK,RREB1,SPG11,TET3,TMEM131
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 MED14


There's no related Drug.
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Cross referenced IDs for MED14
* 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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