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 SEC23A
Basic gene info.Gene symbolSEC23A
Gene nameSec23 homolog A (S. cerevisiae)
SynonymsCLSD
CytomapUCSC genome browser: 14q21.1
Genomic locationchr14 :39501122-39572437
Type of geneprotein-coding
RefGenesNM_006364.2,
Ensembl idENSG00000100934
DescriptionSEC23-related protein Aprotein transport protein Sec23A
Modification date20141207
dbXrefs MIM : 610511
HGNC : HGNC
Ensembl : ENSG00000100934
HPRD : 06714
Vega : OTTHUMG00000028812
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_SEC23A
BioGPS: 10484
Gene Expression Atlas: ENSG00000100934
The Human Protein Atlas: ENSG00000100934
PathwayNCI Pathway Interaction Database: SEC23A
KEGG: SEC23A
REACTOME: SEC23A
ConsensusPathDB
Pathway Commons: SEC23A
MetabolismMetaCyc: SEC23A
HUMANCyc: SEC23A
RegulationEnsembl's Regulation: ENSG00000100934
miRBase: chr14 :39,501,122-39,572,437
TargetScan: NM_006364
cisRED: ENSG00000100934
ContextiHOP: SEC23A
cancer metabolism search in PubMed: SEC23A
UCL Cancer Institute: SEC23A
Assigned class in ccmGDBC

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Phenotypic Information for SEC23A(metabolism pathway, cancer, disease, phenome)
check002.gifCancer Description
Cancer CGAP: SEC23A
Familial Cancer Database: SEC23A
* 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_PROTEINS

check002.gifOthers
OMIM
Orphanet
DiseaseKEGG Disease: SEC23A
MedGen: SEC23A (Human Medical Genetics with Condition)
ClinVar: SEC23A
PhenotypeMGI: SEC23A (International Mouse Phenotyping Consortium)
PhenomicDB: SEC23A

Mutations for SEC23A
* 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
ovarySEC23Achr143955318539553205SEC23Achr143955294639552966
pancreasSEC23Achr143950283939502859SEC23Achr143950270839502728
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 SEC23A related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
AI445956SEC23A28117143956026539560358NUP107116140126908394169083966
AA057305SEC23A1154143953317939533332ARL11152335135020549850205681
AA774945STEAP2215978986360789863764SEC23A160324143952442239531055
F00808SEC23A106174143950198839502056SEC23A175318143952434739524489
BQ647036SEC23A163143957225239572314OSER158893204282615742839097
D44754SEC23A183143956027239560356SNRNP2007016529696510896966773
BE072523SEC23A1293143956135239561435NR6A1854359127366382127366732
D82153SEC23A2390143950226939509996SEC23A384452143950198839502056

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        2        
GAIN (# sample)        2        
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=4

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check002.gifSomatic Mutation Counts per Tissue in COSMIC data
Stat. for Non-Synonymous SNVs
(# total SNVs=57)		Stat. for Synonymous SNVs
(# total SNVs=13)
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
chr14:39514391-39514391p.A625A3
chr14:39512066-39512066p.L637P3
chr14:39517925-39517925p.K556K2
chr14:39565270-39565270p.R18Q2
chr14:39565272-39565272p.V17V2
chr14:39524447-39524447p.E520V2
chr14:39536469-39536469p.T379A2
chr14:39565308-39565308p.L5F2
chr14:39502513-39502513p.L743H2
chr14:39565189-39565189p.L45P1

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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=4

Point Mutation/ Tissue ID1234567891011121314151617181920
# sample12 12  2 21 824  6614
# mutation12 11  2 21 824  7817
nonsynonymous SNV12 6  1 21 724  64 7
synonymous SNV   5  1    1    141 
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
chr14:39512066p.L637P3
chr14:39536469p.L5L2
chr14:39565308p.T379A2
chr14:39514489p.E6K1
chr14:39560913p.T708I1
chr14:39532596p.I513T1
chr14:39509955p.P298L1
chr14:39545233p.L685L1
chr14:39517897p.T497I1
chr14:39565170p.A267T1

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 SEC23A 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 SEC23A

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

ADAM12,ADAMTS12,ANTXR1,BICC1,C14orf37,CDH11,COL5A2,
COL6A3,DACT1,FAM26E,FAP,FBN1,FERMT2,FSTL1,
LOX,MXRA5,NID2,SEC23A,THBS2,VCAN,ZEB1		ABCC9,ANKRD40,ASPA,BCAP29,CALM1,DIAPH2,FAM92A1,
FOXN3,QKI,RAD23B,RTN4,SEC23A,SETD7,SGCB,
SH3GLB1,TTC7B,UGP2,YPEL2,YWHAG,ZEB1,ZFPM2

BAZ1A,DPP8,EXOC5,GMFB,GNA13,GUCY1B3,HEATR5A,
ITGAV,ITGB3,KLHL28,LPP,MAP4K5,MGAT2,MPP5,
PCNX,SEC23A,SEL1L,SNX6,SOCS4,SRP54,TRAPPC6B		ACTB,ACTR1A,AKTIP,C6orf106,CALM1,CDC42EP4,EFR3A,
FEZ2,HNRNPH2,INPP5A,KPNA1,LARGE,MBNL1,MFN2,
NRBP1,PDK3,RPS6KA5,SEC23A,SERINC1,SLC9A6,UBE2G1
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 SEC23A


There's no related Drug.
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Cross referenced IDs for SEC23A
* 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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