Recommendations for laboratory workflow that better support centralised amalgamation of genomic variant data: findings from CanVIG-UK national molecular laboratory survey.

BACKGROUND: 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.

Cancer genome datamining and functional genetic analysis implicate mechanisms of ATM/ATR dysfunction underpinning carcinogenesis.

ATM and ATR are conserved regulators of the DNA damage response linked to cancer. Comprehensive DNA sequencing efforts identified ~4,000 cancer-associated mutations in ATM/ATR; however, their cancer implications remain largely unknown. To gain insights, we identify functionally important conserved residues in ATM, ATR and budding yeast Mec1ATR via cancer genome datamining and a functional genetic analysis, respectively. Surprisingly, only a small fraction of the critical residues is in the active site of the respective enzyme complexes, implying that loss of the intrinsic kinase activity is infrequent in carcinogenesis. A number of residues are solvent accessible, suggestive of their involvement in interacting with a protein-partner(s). The majority, buried inside the respective enzyme complexes, might play a structural or regulatory role. Together, these findings identify evolutionarily conserved ATM, ATR, and Mec1ATR residues involved in diverse aspects of the enzyme function and provide fresh insights into the elusive genotype-phenotype relationships in ATM/ATR and their cancer-associated variants.

Essential Function of Mec1, the Budding Yeast ATM/ATR Checkpoint-Response Kinase, in Protein Homeostasis.

Unlike most checkpoint proteins, Mec1, an ATM/ATR kinase, is essential. We utilized mec1-4, a missense allele (E2130K) that confers diminished kinase activity, to interrogate the question. Unbiased screen for genetic interactors of mec1-4 identified numerous genes involved in proteostasis. mec1-4 confers sensitivity to heat, an amino acid analog, and Htt103Q, an aggregation-prone model peptide of Huntingtin. Oppositely, mec1-4 confers resistance to cycloheximide, a translation inhibitor. In response to heat, mec1-4 leads to widespread protein aggregation and cell death. Key components of the Mec1 signaling network, Rad53CHK1, Dun1, and Sml1, also impact survival in response to proteotoxic stress. Activation of autophagy or sml1Δ promotes aggregate resolution and rescues mec1-4 lethality. These findings show that proteostasis is a fundamental function of Mec1 and that Mec1 is likely to utilize its checkpoint response network to mediate resistance to proteotoxic stress, a role that may be conserved from yeast to mammalian cells.