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 MED29
Basic gene info.Gene symbolMED29
Gene namemediator complex subunit 29
SynonymsIXL
CytomapUCSC genome browser: 19q13.2
Genomic locationchr19 :39881962-39891203
Type of geneprotein-coding
RefGenesNM_017592.1,
Ensembl idENSG00000063322
Descriptionintersex-like proteinmediator of RNA polymerase II transcription subunit 29
Modification date20141207
dbXrefs MIM : 612914
HGNC : HGNC
Ensembl : ENSG00000063322
HPRD : 13748
Vega : OTTHUMG00000182969
ProteinUniProt: Q9NX70
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_MED29
BioGPS: 55588
Gene Expression Atlas: ENSG00000063322
The Human Protein Atlas: ENSG00000063322
PathwayNCI Pathway Interaction Database: MED29
KEGG: MED29
REACTOME: MED29
ConsensusPathDB
Pathway Commons: MED29
MetabolismMetaCyc: MED29
HUMANCyc: MED29
RegulationEnsembl's Regulation: ENSG00000063322
miRBase: chr19 :39,881,962-39,891,203
TargetScan: NM_017592
cisRED: ENSG00000063322
ContextiHOP: MED29
cancer metabolism search in PubMed: MED29
UCL Cancer Institute: MED29
Assigned class in ccmGDBB - This gene belongs to cancer gene.

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Phenotypic Information for MED29(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: MED29
Familial Cancer Database: MED29
* 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 612914; gene.
Orphanet
DiseaseKEGG Disease: MED29
MedGen: MED29 (Human Medical Genetics with Condition)
ClinVar: MED29
PhenotypeMGI: MED29 (International Mouse Phenotyping Consortium)
PhenomicDB: MED29

Mutations for MED29
* 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
ovaryMED29chr193988869939888719TMEM56chr19557111695571136
pancreasMED29chr193988629639886316chr193992120739921227
pancreasMED29chr193988987339889873chr193989218039892180
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 MED29 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 # sample        1 1      
GAIN (# sample)        1 1      
LOSS (# sample)                 
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=2

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=12)
Stat. for Synonymous SNVs
(# total SNVs=1)
Stat. for Deletions
(# total SNVs=1)
Stat. for Insertions
(# total SNVs=3)

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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
chr19:39882267-39882267p.E90K2
chr19:39882165-39882165p.P56S1
chr19:39888221-39888221p.A183V1
chr19:39882025-39882025p.R9P1
chr19:39882225-39882225p.D76H1
chr19:39888332-39888332p.T220I1
chr19:39882026-39882026p.R9R1
chr19:39882040-39882040p.L14P1
chr19:39883109-39883109p.L95F1
chr19:39882043-39882043p.P15L1

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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=1

Point Mutation/ Tissue ID1234567891011121314151617181920
# sample2   1      1 3  13 1
# mutation2   1      1 3  13 1
nonsynonymous SNV1   1        2  13 1
synonymous SNV1          1 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
chr19:39888162p.L14P1
chr19:39882040p.P15L1
chr19:39888188p.A19A1
chr19:39882043p.P56S1
chr19:39882056p.D76H1
chr19:39882165p.L95F1
chr19:39882225p.A99V1
chr19:39883109p.D117N1
chr19:39883120p.F130L1
chr19:39884203p.H145H1

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 MED29 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 MED29

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

AKT2,ATP5SL,BCAM,DYRK1B,ECH1,EID2,EID2B,
FAM98C,MED29,PAF1,PAK4,PSMD8,SAMD4B,SARS2,
SERTAD3,SIPA1L3,SIRT2,SPINT2,SUPT5H,TIMM50,ZNF571
ARFIP2,ATF6B,DDX27,DGCR2,DNAL4,DVL2,FLJ90757,
GAS8,GGT7,IFT140,IQCC,LAS1L,MAPK13,MED29,
MRPL49,PRKCZ,RAB17,ZBTB42,ZNF324,ZNF687,ZNF821

ANKRD27,BLOC1S3,C19orf40,CEP89,CCDC97,DYRK1B,EID2,
GPATCH1,HNRNPUL1,KIAA0355,LSM14A,MED29,PAF1,RBM42,
SAMD4B,SHKBP1,SUPT5H,TSPY26P,USP11,ZNF526,ZNF574
AP1M1,CASQ1,CCDC92,CDC42EP4,CRY2,DBP,EXOC7,
FOXN3,GABARAPL1,GATS,HS1BP3,IDS,INPP5A,MED29,
PBXIP1,PER3,PRKAB2,RAB11FIP3,SNTA1,TEF,TSHZ1
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 MED29


There's no related Drug.
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Cross referenced IDs for MED29
* 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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