GRCh38 · COSMIC v92

Overview

This section shows a general overview of information for the selected study (COSU identifier) or publication (COSP identifier). Studies may have been performed by the Sanger Institute Cancer Genome Project, or imported from the ICGC/TCGA. You can see more information on the help pages.

Reference
Transforming somatic mutations of mTOR kinase in human cancer.
Paper ID
COSP40528
Authors
Yamaguchi H, Kawazu M, Yasuda T, Soda M, Ueno T, Kojima S, Yashiro M, Yoshino I, Ishikawa Y, Sai E and Mano H
Affiliation
Department of Cellular Signaling, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Journal
Cancer science, 2015;106(12):1687-92
ISSN: 1349-7006
PMID: 26432419 (view at PubMed or Europe PMC)
Abstract
Mammalian target of rapamycin (mTOR) is a serine-threonine kinase that acts downstream of the phosphatidylinositol 3-kinase signaling pathway and regulates a wide range of cellular functions including transcription, translation, proliferation, apoptosis, and autophagy. Whereas genetic alterations that result in mTOR activation are frequently present in human cancers, whether the mTOR gene itself becomes an oncogene through somatic mutation has remained unclear. We have now identified a somatic non-synonymous mutation of mTOR that results in a leucine-to-valine substitution at amino acid position 2209 in a specimen of large cell neuroendocrine carcinoma. The mTOR(L2209V) mutant manifested marked transforming potential in a focus formation assay with mouse 3T3 fibroblasts, and it induced the phosphorylation of p70 S6 kinase, S6 ribosomal protein, and eukaryotic translation initiation factor 4E-binding protein 1 in these cells. Examination of additional tumor specimens as well as public and in-house databases of cancer genome mutations identified another 28 independent non-synonymous mutations of mTOR in various cancer types, with 12 of these mutations also showing transforming ability. Most of these oncogenic mutations cluster at the interface between the kinase domain and the FAT (FRAP, ATM, TRRAP) domain in the 3-D structure of mTOR. Transforming mTOR mutants were also found to promote 3T3 cell survival, and their oncogenic activity was sensitive to rapamycin. Our data thus show that mTOR acquires transforming activity through genetic changes in cancer, and they suggest that such tumors may be candidates for molecularly targeted therapy with mTOR inhibitors.
Paper Status
Curated
Genes Analysed
560
Mutated Samples
4
Total No. of Samples
4

Mutation Matrix

This section shows the correlation plot between the top 20 genes and samples. There is more information in our help pages.

Genes

This table shows genes with mutations in the selected study/paper [more details]
Genes Mutated Samples
This table shows genes without mutations in the selected study/paper [more details]

Table Information

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The negatives shown on this page are only from targeted gene screens, but does not include negatives from whole exome/systematic screens( these negatives should be inferred ).

Non-Mutant Genes Gene Id (COSG)

Variants

This tab shows genes with mutations in the selected study/paper [more details]

Genes Samples CDS Mutation AA Mutation

This tab shows non coding variant in the selected study/paper [more details]

Sample ID Sample Name ID NCV Annotation Zygosity Chromosome Genome start Genome stop Genome version Strand WT seq Mut seq FATHMM-MKL

This tab shows the gene expression and copy number variation data for this study [more details]

Table Information

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The table currently shows only high value (numeric) copy number data. Copy number segments are excluded if the total copy number and minor allele values are unknown.

Click here to include all copy number data. For more detailed information about copy number data and gain/loss definitions click here.

Sample Gene Expression Expr Level (Z-Score)

Over Expressed; Z-Score > 2.0

Under Expressed; Z-Score < -2.0

Normal; Z-Score within the range -2.0 to 2.0

CN Type Minor Allele Copy Number CN Segment Posn. Average Ploidy

1. N/A represents cases where the average ploidy value is not available( mostly ICGC samples). For some TCGA samples where the minor allele information is not available the average ploidy value could not be calculated.

2. For TCGA samples, the ASCAT algorithm was used to calculate the average ploidy.

3. For CGP samples, the PICNIC algorithm was used to calculate the average ploidy.

CNV

This table lists the samples in the selected study which have low/high methylation for each gene. [more details]

No data

This tab shows the fusion mutations observed in this sample [more details]

Gene Sample Name Id Sample(COSS) CDS Mutation Somatic status Zygosity Validated Type

Samples

This table shows mutated samples in the selected study/paper.

Sample Name Mutation Count

This table shows samples without mutations in the selected study/paper.

Non-Mutant Samples Sample Id (COSS)