Introduction
Measuring somatic mutations in humans provides an invaluable tool for identifying exogenous mutagenic sources, allowing us to make better informed public health choices to avoid harmful exposures and to introduce regulatory approaches to reduce these adverse exposures. As cancer is driven by DNA mutations, an accumulation of somatic mutations is known to increase an individual’s cancer risk (Hanahan & Weinberg, 2011). Hence monitoring individuals for the number and types of somatic DNA mutations will allow the identification of those who may be at increased risk of cancer development which may allow for early intervention and perhaps even cancer prevention. Environmental exposures that can induce mutation include dietary, lifestyle, accidental and occupational exposures. Developing tools that allow us to measure such mutations will aid in the identification of new mutagenic and/or carcinogenic exposures (Loomis, Guha, Hall, & Straif, 2018). Knowledge of the lifestyle factors associated with increased mutation levels could be used to tailor advice to members of the public in relation to avoiding risky behaviours (e.g., smoking) through public health measures. Everyday exposures may conversely reduce our mutational risk, e.g., diets containing anti-mutagenic compounds. Chemo-preventative, or anti-genotoxicity lifestyle factors could be specifically identified through large-scale human biomonitoring studies (e.g., dietary compounds and medications) using high-throughput approaches needed to unpick the multi-faceted exposures we face daily.
In addition, genetic polymorphisms may modulate an individual’s risk of mutation (and hence cancer), either by increasing or decreasing the likelihood of mutational events. For example, if a certain exposure to a genotoxin induces DNA damage which cannot be efficiently repaired due to polymorphisms in genes such as OGG1 (Jensen et al., 2012) orXRCC1 (Monteiro, Vilas Boas, Gigliotti, & Salvadori, 2014) (involved in base excision repair), this may increase an individual’s sensitivity to DNA damage. In addition, germline mutations in DNA polymerases increases somatic mutational burden in normal tissues (Robinson et al., 2022), and somatic mutation rates are increased in the normal tissues of patients with MUTYH-associated polyposis (MAP) (Robinson et al., 2021). Therefore, a personalised approach to precision exposure monitoring may be most beneficial with the inclusion of these biomarkers of susceptibility.
There are a handful of cytogenetic techniques that can detect DNA abnormalities in human cells. Currently available genotoxicity tests suitable for measuring DNA damage and mutation include the lymphocyte cytokinesis-block micronucleus test (CBMN) (Fenech et al., 2011), the lymphocyte COMET assay (Fenech et al., 2011) and the hypoxanthine-guanine phosphoribosyl transferase (hprt ) test (Townsend, Robison, & O’Neill, 2018) as well as approaches measuring sister chromatid exchanges (Sunada, Haskins, & Kato, 2019) and chromosomal abnormalities (Sunada et al., 2019). Recently, increased accessibility to DNA sequencing technologies able to overcome difficulties associated with background mutation rates, have identified DNA mutational signatures (Alexandrov et al., 2020; Alexandrov et al., 2013), particularly those that correlate with certain human exposures including Aflatoxin B1 and ultraviolet irradiation (Phillips, 2018). Whilst whole genome/exome sequencing allows us to measure mutations across the whole genome, and not just those produced in reporter genes such as hprt or phosphatidylinositol glycan class A(PIG-A) , the technology is still relatively expensive and not therefore suitable for wide-scale roll out in population-based biomonitoring studies. Moreover, not all exposures have known mutational profiles or signatures at this stage and therefore it is not informative to measure de novo mutational signatures if we do not know the cause.
The PIG-A assay measures de novo somatic mutations in thePIG-A gene. The test measures the steady state accumulation of mutations in blood cells, to provide a snapshot of mutant cell levels at any given point in time relative to the lifespan of erythrocytes (approximately 115-120 days) (Franco, 2012; Thiagarajan, Parker, & Prchal, 2021). The PIG-A gene is located at Xp22.2 in humans. The protein product of the gene is responsible for the production of a catalytic subunit of N-acetylglucosamine transferase, an enzyme involved in one of the early steps of glycosyl phosphatidylinositol (GPI)-anchor biosynthesis (Takeda et al., 1993). Although there are over 20 genes involved in GPI-anchor production, only one mutation in the PIG-Agene is required to inactivate the gene and result in a GPI deficient phenotype (Miyata et al., 1993). As shown in Figure 1, PIG-Awild-type cells present many GPI-anchors and their corresponding GPI-anchored proteins (GPI-AP) on the cell surface which can subsequently be detected using fluorescently labelled antibodies targeting the GPI-AP of choice through flow cytometry. PIG-Amutant cells lack these GPI anchors and crucially lack the GPI-APs and therefore GPI-AP targeted antibodies are unable to bind to the extracellular surface.