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 LIPC
Basic gene info.Gene symbolLIPC
Gene namelipase, hepatic
SynonymsHDLCQ12|HL|HTGL|LIPH
CytomapUCSC genome browser: 15q21-q23
Genomic locationchr15 :58724174-58861073
Type of geneprotein-coding
RefGenesNM_000236.2,
Ensembl idENSG00000166035
Descriptionhepatic lipasehepatic triacylglycerol lipaselipase member C
Modification date20141211
dbXrefs MIM : 151670
HGNC : HGNC
Ensembl : ENSG00000166035
HPRD : 01058
Vega : OTTHUMG00000132632
ProteinUniProt:
go to UniProt's Cross Reference DB Table
ExpressionCleanEX: HS_LIPC
BioGPS: 3990
Gene Expression Atlas: ENSG00000166035
The Human Protein Atlas: ENSG00000166035
PathwayNCI Pathway Interaction Database: LIPC
KEGG: LIPC
REACTOME: LIPC
ConsensusPathDB
Pathway Commons: LIPC
MetabolismMetaCyc: LIPC
HUMANCyc: LIPC
RegulationEnsembl's Regulation: ENSG00000166035
miRBase: chr15 :58,724,174-58,861,073
TargetScan: NM_000236
cisRED: ENSG00000166035
ContextiHOP: LIPC
cancer metabolism search in PubMed: LIPC
UCL Cancer Institute: LIPC
Assigned class in ccmGDBC

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

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

Mutations for LIPC
* 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
NSLIPCchr155877982758779827chr157808728978087289
ovaryLIPCchr155876262658762646chr8131743487131743507
ovaryLIPCchr155880964958809669LIPCchr155880979258809812
ovaryLIPCchr155883315658833176LIPCchr155883362458833644
pancreasLIPCchr155881061858810638LIPCchr155878638858786408
pancreasLIPCchr155886011658860136ADAM10chr155895065458950674
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 LIPC related fusion information.
IDHead GeneTail Gene
AccessionGene_aqStart_aqEnd_aChromosome_atStart_atEnd_aGene_aqStart_aqEnd_aChromosome_atStart_atEnd_a
AI589684RPS1128113195000286150002946LIPC112334155880518558805407
T89564ATP8A115144243748942437539LIPC47333155885685758857141

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     2 1       1
GAIN (# sample)      1         1
LOSS (# sample)1     1 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)

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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=3

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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=18)
Stat. for Deletions
(# total SNVs=1)
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
chr15:58855879-58855879p.V449I2
chr15:58855922-58855922p.R463fs*22
chr15:58840565-58840565p.S282L2
chr15:58855764-58855764p.I410I2
chr15:58834792-58834792p.H172H2
chr15:58855765-58855765p.G411R2
chr15:58834808-58834808p.G178S2
chr15:58830636-58830636p.R65*2
chr15:58855785-58855785p.K417N2
chr15:58853108-58853108p.T366K1

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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=2

Point Mutation/ Tissue ID1234567891011121314151617181920
# sample4118  3 2  842  82 9
# mutation4119  3 2  1042  82 10
nonsynonymous SNV41 5  3 1  1021  72 6
synonymous SNV  14    1   21  1  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
chr15:58830668p.C75C2
chr15:58837994p.K335R1
chr15:58830586p.T493A1
chr15:58840598p.L54I1
chr15:58855765p.H185L1
chr15:58830684p.T343T1
chr15:58838000p.L54L1
chr15:58830595p.R189K1
chr15:58840680p.R344Q1
chr15:58855766p.E57K1

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 LIPC 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 LIPC

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

CATSPER1,CPN2,CT55,DEFB108B,DMRTC2,GAGE12D,GAGE2A,
GAGE2E,GBX1,GH1,LIPC,LOC146880,LYPD4,OR56A1,
PAGE1,PROCA1,PTH1R,SAMD7,SCN4A,SSX7,TMEM174
C11orf87,C1orf68,CNGA2,DEFB118,FAM180A,FBLN1,FGF14,
ITGBL1,KCNA6,LIPC,LTBP1,OGN,OLFML1,PROS1,
PTGIS,RECK,SHC3,SPOCK1,UST,XG,ZNF521

A4GNT,ACMSD,ACY3,ANXA10,BCAR4,BTBD16,CCER1,
CLTC,COX8C,CPS1,CYP2E1,DGCR9,GABRP,GATA4,
KY,LIPC,LOC100128239,PDZK1,RPS6KB1,SERPINA4,SLC16A2
AMACR,CACFD1,CAPN2,CCNJL,CLIP2,DTX4,ERBB3,
FAM134A,KCNJ2,LIPC,MMP24,MYO1D,NETO2,P2RX4,
TINCR,PLCL2,RMND5A,RNASEL,SLC26A2,TSPAN7,WDR78
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 LIPC
check002.gifCross-referenced pharmacological DB IDs from Uniprot
DB CategoryDB NameDB's ID and Url link

check002.gifDrug-Gene Interaction Network
* Gene Centered Interaction Network.
* Drug Centered Interaction Network.
DrugBank IDTarget NameDrug GroupsGeneric NameDrug Centered NetworkDrug Structure
DB00682lipase, hepaticapprovedWarfarin
DB01095lipase, hepaticapprovedFluvastatin
DB00375lipase, hepaticapprovedColestipol
DB00264lipase, hepaticapproved; investigationalMetoprolol


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Cross referenced IDs for LIPC
* 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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