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Phenotypic Information (metabolism pathway, cancer, disease, phenome) | |
Gene-Gene Network Information: Co-Expression Network, Interacting Genes & KEGG | |
Gene Summary for AMACR |
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Phenotypic Information for AMACR(metabolism pathway, cancer, disease, phenome) |
Cancer Description | |
Cancer | CGAP: AMACR |
Familial Cancer Database: AMACR |
* This gene is included in those cancer gene databases. |
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Oncogene 1 | Significant driver gene in |
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/ |
Metabolic Pathway Description | |
REACTOME_PEROXISOMAL_LIPID_METABOLISM REACTOME_METABOLISM_OF_LIPIDS_AND_LIPOPROTEINS |
Others | |
OMIM | |
Orphanet | |
Disease | KEGG Disease: AMACR |
MedGen: AMACR (Human Medical Genetics with Condition) | |
ClinVar: AMACR | |
Phenotype | MGI: AMACR (International Mouse Phenotyping Consortium) |
PhenomicDB: AMACR |
Mutations for AMACR |
* 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. |
Structural Variants in COSMIC: go to COSMIC mutation histogram |
There's no structural variation information in COSMIC data for this gene. |
Related fusion transcripts : go to Chitars2.0 |
* From mRNA Sanger sequences, Chitars2.0 arranged chimeric transcripts. This table shows AMACR related fusion information. |
ID | Head Gene | Tail Gene | Accession | Gene_a | qStart_a | qEnd_a | Chromosome_a | tStart_a | tEnd_a | Gene_a | qStart_a | qEnd_a | Chromosome_a | tStart_a | tEnd_a |
BE267449 | PSMG3 | 272 | 688 | 7 | 1607316 | 1608998 | AMACR | 686 | 707 | 5 | 34007940 | 34007962 |
Other DBs for Structural Variants |
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Copy Number Variations in COSMIC: go to COSMIC mutation CNV/Expr |
Mutation type/ Tissue ID | brca | cns | cerv | endome | haematopo | kidn | Lintest | liver | lung | ns | ovary | pancre | prost | skin | stoma | thyro | urina | |||
Total # sample |   |   |   | 1 |   |   |   |   |   |   |   |   |   | 2 |   |   |   | |||
GAIN (# sample) |   |   |   |   |   |   |   |   |   |   |   |   |   | 2 |   |   |   | |||
LOSS (# sample) |   |   |   | 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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SNV Counts per Each Loci in COSMIC data: go to COSMIC point mutation |
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Somatic Mutation Counts per Tissue in COSMIC data |
Stat. for Non-Synonymous SNVs (# total SNVs=36) | (# total SNVs=8) |
(# total SNVs=0) | (# total SNVs=0) |
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Top 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 position | Mutation(aa) | Unique sampleID count |
chr5:34008100-34008100 | p.V9M | 3 |
chr5:33989425-33989425 | p.H308Y | 2 |
chr5:33989263-33989263 | p.E362K | 2 |
chr5:34008107-34008107 | p.I6M | 2 |
chr5:34005863-34005863 | p.S130L | 2 |
chr5:33989575-33989575 | p.Q258E | 1 |
chr5:33989255-33989255 | p.I364I | 1 |
chr5:34004719-34004719 | p.R171H | 1 |
chr5:34005978-34005978 | p.P92S | 1 |
chr5:33989591-33989591 | p.S252S | 1 |
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SNV Counts per Each Loci in TCGA data |
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Point Mutation/ Tissue ID | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 |
# sample | 1 | 1 |   | 6 |   |   | 1 |   | 1 |   |   | 6 | 3 |   |   |   | 3 | 6 |   | 5 |
# mutation | 1 | 1 |   | 7 |   |   | 1 |   | 1 |   |   | 7 | 3 |   |   |   | 3 | 6 |   | 5 |
nonsynonymous SNV | 1 | 1 |   | 6 |   |   | 1 |   | 1 |   |   | 7 | 2 |   |   |   | 2 | 5 |   | 5 |
synonymous SNV |   |   |   | 1 |   |   |   |   |   |   |   |   | 1 |   |   |   | 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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Top 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 Position | Mutation(aa) | Unique sampleID count |
chr5:33989263 | p.E362K,AMACR | 2 |
chr5:34004719 | p.D322D,AMACR | 1 |
chr5:33989322 | p.S154W,AMACR | 1 |
chr5:34008111 | p.R312L,AMACR | 1 |
chr5:33989517 | p.T153I,AMACR | 1 |
chr5:34004754 | p.H308Y,AMACR | 1 |
chr5:33989379 | p.I147T | 1 |
chr5:33989521 | p.H305L,AMACR | 1 |
chr5:34004781 | p.R171H,AMACR | 1 |
chr5:33989381 | p.E301D,AMACR | 1 |
Other DBs for Point Mutations |
Copy Number for AMACR 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 AMACR |
Gene 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. |
Differential 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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CNV vs Gene Expression Plot |
* This plots show the correlation between CNV and gene expression. |
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Gene-Gene Network Information |
Co-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 |
AGGF1,ALCAM,AMACR,ATP7A,C5orf51,CMBL,DNAJC21, ELMOD2,ERGIC1,FOXA1,HERC3,IL13RA1,ISX,LMBRD2, REEP5,RETSAT,SAR1B,SC5D,SCP2,TMEM62,TMEM86A | AMACR,ARX,CMBL,CRAT,CUL4A,DNAJA4,DOPEY2, IDE,KPNA1,NDUFAF1,NDUFB3,NPEPPS,NUDT3,P4HA1, PANK1,ECI2,PHKB,SAR1B,SIX1,SPPL2A,TTL | ||||
ABAT,AMACR,CCDC170,CTTNBP2,LOC148709,LRRC2,NAALADL2, NUDT7,PAAF1,PIGU,PMFBP1,QPRT,REEP1,RPIA, SFXN5,SLC39A5,SLC5A6,STX3,TSPAN6,VAV3,ZNRF3 | AHCYL2,AMACR,APPL2,CA4,CAPN2,CDKN2B,CLCN2, ENPP1,HHLA2,LCMT1,MGLL,MKRN1,P2RX4,PEX26, TINCR,PPARG,PRDX6,SH3BGRL2,SLC26A2,SLC26A3,TSPAN7 |
Co-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 |
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Interacting Genes (from Pathway Commons) |
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Pharmacological Information for AMACR |
Cross-referenced pharmacological DB IDs from Uniprot |
DB Category | DB Name | DB's ID and Url link |
Drug-Gene Interaction Network |
* Gene Centered Interaction Network. |
* Drug Centered Interaction Network. |
DrugBank ID | Target Name | Drug Groups | Generic Name | Drug Centered Network | Drug Structure |
DB00145 | alpha-methylacyl-CoA racemase | approved; nutraceutical | Glycine |
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Cross referenced IDs for AMACR |
* We obtained these cross-references from Uniprot database. It covers 150 different DBs, 18 categories. http://www.uniprot.org/help/cross_references_section |
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