6 research outputs found
Cancer genome datamining and functional genetic analysis implicate mechanisms of ATM/ATR dysfunction underpinning carcinogenesis
Essential function of Mec1, the budding yeast ATM/ATR checkpoint-response kinase, in protein homeostasis
Genotype-phenotype analysis of the checkpoint kinase MEC1, the budding yeast homologue of human ATM/ ATR
The protein kinases ATR and ATM, and their Saccharomyces cerevisiae counterparts Mec1 and Tel1, are the apical kinases of the DNA damage response, a cellular response to potentially lethal DNA damage from both endogenous and exogenous sources. ATR/ATMMec1/Tel1 are part of the PIKK (PI3-kinase-like kinases) family of protein kinases; PIKK proteins are very large and contain a conserved C-terminal
kinase domain and a large number of N-terminal helical HEAT repeats, thought to be involved in target binding. Mutation of ATM leads to the developmental disorder Ataxia-Telangiectasia, and ATM and ATR have been found to be mutated in a large number of cancers.
Although much is known about the role of ATM/ATR in the DNA damage response, very little is known about the structure-function relationship of the proteins. ATM/ATR can phosphorylate around 700 different targets, yet how they bind and how target specificity is controlled remains largely unknown. In this study I have identified
23 randomly mutated Mec1ATR alleles to assess which region of the protein is important for the response to different stresses; particularly hydroxyurea (HU), which causes replication stress, and methyl-methansulphonate (MMS), which causes DNA damage. There were no mutations identified at the very N-terminal region of Mec1, the region where Ddc2ATRIP binds, suggesting that mutations in this region may effect
this essential interaction. The remaining mutations were spread over the length of the protein and many mutations were found in the kinase domain. The mutation E2130K in the kinase domain was found in two seperate strains.
In most instances a sensitivity to a certain stress correlated with a loss of Mec1s ability to phosphorylate Rad53, a major downstream effector kinase. Interestingly, in
some cases, combining two different mec1 alleles in the same strain rescued their respective phenotypes, indicating intramolecular complementation of the dimeric Mec1 kinase. A number of these alleles are also conserved in human ATM/ATR
and have been shown to be mutated in cancer
Genotype-phenotype analysis of the checkpoint kinase MEC1, the budding yeast homologue of human ATM/ ATR
The protein kinases ATR and ATM, and their Saccharomyces cerevisiae counterparts Mec1 and Tel1, are the apical kinases of the DNA damage response, a cellular response to potentially lethal DNA damage from both endogenous and exogenous sources. ATR/ATMMec1/Tel1 are part of the PIKK (PI3-kinase-like kinases) family of protein kinases; PIKK proteins are very large and contain a conserved C-terminal
kinase domain and a large number of N-terminal helical HEAT repeats, thought to be involved in target binding. Mutation of ATM leads to the developmental disorder Ataxia-Telangiectasia, and ATM and ATR have been found to be mutated in a large number of cancers.
Although much is known about the role of ATM/ATR in the DNA damage response, very little is known about the structure-function relationship of the proteins. ATM/ATR can phosphorylate around 700 different targets, yet how they bind and how target specificity is controlled remains largely unknown. In this study I have identified
23 randomly mutated Mec1ATR alleles to assess which region of the protein is important for the response to different stresses; particularly hydroxyurea (HU), which causes replication stress, and methyl-methansulphonate (MMS), which causes DNA damage. There were no mutations identified at the very N-terminal region of Mec1, the region where Ddc2ATRIP binds, suggesting that mutations in this region may effect
this essential interaction. The remaining mutations were spread over the length of the protein and many mutations were found in the kinase domain. The mutation E2130K in the kinase domain was found in two seperate strains.
In most instances a sensitivity to a certain stress correlated with a loss of Mec1s ability to phosphorylate Rad53, a major downstream effector kinase. Interestingly, in
some cases, combining two different mec1 alleles in the same strain rescued their respective phenotypes, indicating intramolecular complementation of the dimeric Mec1 kinase. A number of these alleles are also conserved in human ATM/ATR
and have been shown to be mutated in cancer
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Recommendations for laboratory workflow that better support centralised amalgamation of genomic variant data: findings from CanVIG-UK national molecular laboratory survey.
Peer reviewed: TrueBACKGROUND: National and international amalgamation of genomic data offers opportunity for research and audit, including analyses enabling improved classification of variants of uncertain significance. Review of individual-level data from National Health Service (NHS) testing of cancer susceptibility genes (2002-2023) submitted to the National Disease Registration Service revealed heterogeneity across participating laboratories regarding (1) the structure, quality and completeness of submitted data, and (2) the ease with which that data could be assembled locally for submission. METHODS: In May 2023, we undertook a closed online survey of 51 clinical scientists who provided consensus responses representing all 17 of 17 NHS molecular genetic laboratories in England and Wales which undertake NHS diagnostic analyses of cancer susceptibility genes. The survey included 18 questions relating to 'next-generation sequencing workflow' (11), 'variant classification' (3) and 'phenotypical context' (4). RESULTS: Widely differing processes were reported for transfer of variant data into their local LIMS (Laboratory Information Management System), for the formatting in which the variants are stored in the LIMS and which classes of variants are retained in the local LIMS. Differing local provisions and workflow for variant classifications were also reported, including the resources provided and the mechanisms by which classifications are stored. CONCLUSION: The survey responses illustrate heterogeneous laboratory workflow for preparation of genomic variant data from local LIMS for centralised submission. Workflow is often labour-intensive and inefficient, involving multiple manual steps which introduce opportunities for error. These survey findings and adoption of the concomitant recommendations may support improvement in laboratory dataflows, better facilitating submission of data for central amalgamation