Genetic screens are now being performed for a variety of diseases, ranging from connective tissue diseases and metabolic syndromes to cancer. But the utility of these screens depends on being able to interpret the clinical significance of the variants that are identified. In particular, it is frequently difficult to determine the significance of missense variants, which are often rare. For rare variants, co-segregation studies are frequently underpowered to be useful for variant classification. Functional assays provide the most promising alternative for classifying variants of uncertain significance (VUS). Our goal, beginning with ATM, since there are >2,480 missense VUS listed for it in ClinVar, is to establish an accurate and high capacity system to functionally classify VUS. Missense variants of ATM have been identified in ataxia-telangiectasia (A-T), which is a recessive disease, and in patients predisposed to a hereditary cancer syndrome by germline mutations in ATM. ATM has a central role in regulating the cellular response to DNA double-strand breaks (DSBs), including mediating DNA damage signaling, the G2 checkpoint and cellular resistance to ionizing radiation. ATM protein expression has been problematic, in part due to large gene size and poor mRNA quality. This has greatly restricted studies to characterize the effects of ATM variants and the roles of different regions of ATM. In fact, no rigorously validated system, nor one calibrated for sensitivity and specificity, has previously been established to classify ATM VUS. We will surmount these obstacles by employing an innovative strategy for the rapid and efficient expression of full-length human ATM in ATM-deficient cells using a lentiviral vector and a codon-optimized cDNA. Importantly, by synthesizing variants in fragments of ATM which are then inserted into the expression vector, we have developed a modular approach rapid enough to evaluate ATM VUS on a large scale.
In Aim 1, we will validate our novel system for characterizing ATM VUS using DSB-related assays by testing benign and pathogenic standards that have previously been defined based on clinical and genetic criteria. We will also initiate our system by characterizing 300 missense ATM VUS of the C-terminal FATKIN region, which contains the kinase domain and key regulatory elements, and which is where the most known pathogenic missense ATM variants reside. Further, we will incorporate the results of functional assays into a multifactorial analysis, along with clinical and genetic data, for robust predictions of cancer risk associated with missense ATM variants. Another important limitation to understanding the effects of variants, and the role of ATM in preventing disease, is a need to better define the roles of distinct regions of ATM, which is largely unknown. This will be addressed in Aim 2 by expressing mutants that delete regions throughout the protein. We will also test the effects of pathogenic variants on binding to the NBS1 activator and will interpret the 3-dimensional structural effects of pathogenic variants in the FATKIN region. We expect that the work proposed here will have a major clinical impact by characterizing VUS and will dramatically improve understanding of ATM function.
Due to variants of uncertain significance, information about ATM alterations, as identified in genetic screens, is greatly underutilized for guiding clinical care. To classify variants, and to improve understanding of ATM function in DNA damage responses, we have developed a rapid system to express ATM variants and deletion mutants in ATM-deficient cells for accurate functional tests. Importantly, this system should have a major clinical impact, since a validated and calibrated system to classify ATM variants is currently lacking.
