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 CA9
Basic gene info.Gene symbolCA9
Gene namecarbonic anhydrase IX
SynonymsCAIX|MN
CytomapUCSC genome browser: 9p13.3
Genomic locationchr9 :35673914-35681154
Type of geneprotein-coding
RefGenesNM_001216.2,
Ensembl idENSG00000107159
DescriptionCA-IXP54/58NRCC-associated antigen G250RCC-associated protein G250carbonate dehydratase IXcarbonic anhydrase 9carbonic dehydratasemembrane antigen MNpMW1renal cell carcinoma-associated antigen G250
Modification date20141222
dbXrefs MIM : 603179
HGNC : HGNC
Ensembl : ENSG00000107159
HPRD : 04417
Vega : OTTHUMG00000021029
ProteinUniProt: Q16790
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_CA9
BioGPS: 768
Gene Expression Atlas: ENSG00000107159
The Human Protein Atlas: ENSG00000107159
PathwayNCI Pathway Interaction Database: CA9
KEGG: CA9
REACTOME: CA9
ConsensusPathDB
Pathway Commons: CA9
MetabolismMetaCyc: CA9
HUMANCyc: CA9
RegulationEnsembl's Regulation: ENSG00000107159
miRBase: chr9 :35,673,914-35,681,154
TargetScan: NM_001216
cisRED: ENSG00000107159
ContextiHOP: CA9
cancer metabolism search in PubMed: CA9
UCL Cancer Institute: CA9
Assigned class in ccmGDBA - This gene has a literature evidence and it belongs to cancer gene.
References showing role of CA9 in cancer cell metabolism1. Motzer RJ, Hutson TE, Hudes GR, Figlin RA, Martini JF, et al. (2014) Investigation of novel circulating proteins, germ line single-nucleotide polymorphisms, and molecular tumor markers as potential efficacy biomarkers of first-line sunitinib therapy for advanced renal cell carcinoma. Cancer Chemother Pharmacol 74: 739-750. doi: 10.1007/s00280-014-2539-0. pmid: 4175044 go to article
2. Sheng W, Dong M, Zhou J, Li X, Dong Q (2013) Down regulation of CAII is associated with tumor differentiation and poor prognosis in patients with pancreatic cancer. J Surg Oncol 107: 536-543. doi: 10.1002/jso.23282. go to article
3. Zhou R, Huang W, Yao Y, Wang Y, Li Z, et al. (2013) CA II, a potential biomarker by proteomic analysis, exerts significant inhibitory effect on the growth of colorectal cancer cells. Int J Oncol 43: 611-621. doi: 10.3892/ijo.2013.1972. go to article
4. Riafrecha LE, Rodriguez OM, Vullo D, Supuran CT, Colinas PA (2014) Attachment of carbohydrates to methoxyaryl moieties leads to highly selective inhibitors of the cancer associated carbonic anhydrase isoforms IX and XII. Bioorg Med Chem 22: 5308-5314. doi: 10.1016/j.bmc.2014.07.052. go to article
5. Soltysova A, Breza J, Takacova M, Feruszova J, Hudecova S, et al. (2015) Deregulation of energetic metabolism in the clear cell renal cell carcinoma: A multiple pathway analysis based on microarray profiling. Int J Oncol 47: 287-295. doi: 10.3892/ijo.2015.3014. go to article

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Phenotypic Information for CA9(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: CA9
Familial Cancer Database: CA9
* 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
KEGG_NITROGEN_METABOLISM

check002.gifOthers
OMIM 603179; gene.
Orphanet
DiseaseKEGG Disease: CA9
MedGen: CA9 (Human Medical Genetics with Condition)
ClinVar: CA9
PhenotypeMGI: CA9 (International Mouse Phenotyping Consortium)
PhenomicDB: CA9

Mutations for CA9
* 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
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'.
SampleSymbol_aChr_aStart_aEnd_aSymbol_bChr_bStart_bEnd_b
ovaryCA9chr93567686135676881chr93567187935671899
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 CA9 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 # sample1     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=6

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=39)
Stat. for Synonymous SNVs
(# total SNVs=11)
Stat. for Deletions
(# total SNVs=5)
Stat. for Insertions
(# total SNVs=0)
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
chr9:35674208-35674208p.P84P6
chr9:35674191-35674208p.G79_P84delGEEDLP5
chr9:35674204-35674204p.L83P4
chr9:35674228-35674228p.G91E3
chr9:35674151-35674151p.L65L2
chr9:35674152-35674152p.P66S1
chr9:35676121-35676121p.A222D1
chr9:35680802-35680802p.A430A1
chr9:35674260-35674260p.S102A1
chr9:35679199-35679199p.P309S1

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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
# sample13 121   1  515 175 3
# mutation13 121   1  515 195 3
nonsynonymous SNV13 71   1  513 164 3
synonymous SNV   5         2  31  
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
chr9:35674151p.L65L2
chr9:35674152p.G91R1
chr9:35679874p.G215S1
chr9:35675793p.I386N1
chr9:35676372p.S102A1
chr9:35674217p.P216R1
chr9:35679916p.A392T1
chr9:35675809p.D112Y1
chr9:35676374p.E249K1
chr9:35674227p.E402K1

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 CA9 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 CA9

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

ADM,B3GNT4,BNC1,CA9,CSRP2,ENO1,FSCN1,
GAPDH,GJB5,GPI,KRT5,KRT75,NDRG1,NMB,
PFKP,PKM,S100A2,SLC2A1,TPI1,TUBA1C,TUBA4A
VRTN,C1QTNF8,C7orf33,CA9,CHD5,CLPS,COL9A1,
CPNE6,DRP2,HBG1,HBG2,ITLN1,KIF1A,MLC1,
NKX2-3,NOBOX,P2RX1,POU5F1B,SOST,WFDC1,ZFP42

ALDOA,CA9,EGLN3,ENO1,ENO2,ERO1L,GAPDH,
GBE1,GPI,LDHA,MUC1,P4HA1,PFKP,PGAM1,
PKM,PLA2G2A,PNPLA3,RNF183,SLC6A8,SYT8,TBC1D21
ASPDH,TMEM252,CA9,CLDN15,CPS1,DAK,DEFA5,
DEFA6,DPEP1,FBP1,GGN,KDM8,KHK,OTC,
PDZD7,PRSS1,REG3A,SLC10A2,SULT2B1,TBX3,TTC36
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 CA9
check002.gifCross-referenced pharmacological DB IDs from Uniprot
DB CategoryDB NameDB's ID and Url link
ChemistryBindingDB Q16790; -.
ChemistryChEMBL CHEMBL2095180; -.
Organism-specific databasesPharmGKB PA25998; -.
Organism-specific databasesCTD 768; -.

check002.gifDrug-Gene Interaction Network
* Gene Centered Interaction Network.
* Drug Centered Interaction Network.
DrugBank IDTarget NameDrug GroupsGeneric NameDrug Centered NetworkDrug Structure
DB00562carbonic anhydrase IXapprovedBenzthiazide
DB00774carbonic anhydrase IXapprovedHydroflumethiazide
DB00909carbonic anhydrase IXapproved; investigationalZonisamide
DB00999carbonic anhydrase IXapprovedHydrochlorothiazide


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Cross referenced IDs for CA9
* 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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