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.