Toxicology Letters 207 (2011) 42–52
Contents lists available at SciVerse ScienceDirect
Toxicology Letters
journal homepage: www.elsevier.com/locate/toxlet
Mini review
Biomarkers of occupational exposure do anticancer agents: A minireview
A. Suspiro ∗ , J. Prista
ENSP – UNL, Escola Nacional de Saúde Pública Universidade Nova de Lisboa, UNL, Avenida Padre Cruz, 1600-560 Lisboa, Portugal
a r t i c l e
i n f o
Article history:
Received 16 July 2011
Received in revised form 27 August 2011
Accepted 29 August 2011
Available online 3 September 2011
Keywords:
Anticancer agents
Occupational exposure
Biomarkers
a b s t r a c t
The majority of anticancer agents has in common DNA-damaging properties and affects not only targetcells but also non-tumour cells. Its genotoxicity has been demonstrated in experimental models and
in cancer patients treated with chemotherapy. Health care personnel involved in the preparation and
administration of chemotherapy is therefore at risk for adverse health effects, since most environmental
sampling studies demonstrated that there is widespread contamination of work surfaces and equipments
with anticancer drugs. Adherence to safety guidelines and proper use of personal protective equipment
are insufficient to prevent significant absorption, as evidenced by the presence of detectable amounts
of drugs in urine samples and increased frequency of genotoxicity biomarkers. In this minireview, a
critical appraisal of the most important biomarkers used for the evaluation of occupational exposure to
anticancer agents as well as a summary of the key findings from several studies published in this field is
performed.
© 2011 Elsevier Ireland Ltd. All rights reserved.
Contents
1.
2.
3.
4.
Biomarkers of exposure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Biomarkers of effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.1.
Chromosomal aberrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.2.
Sister chromatid exchanges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.3.
The micronuclei test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.4.
In vivo comet assay or single cell gel electrophoresis (SCGE) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.5.
Mutation tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Biomarkers of susceptibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1.
GSTs polymorphisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.
DNA repair enzymes polymorphisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Final comments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Conflict of interest statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Anticancer agents have a widespread and increasing use in the
treatment of cancer as well as of some nonmalignant diseases.
These agents encompass several unrelated chemical compounds
having in common the ability to inhibit tumour growth. Genetic
damage plays an important role in most mechanisms underlying the action of anticancer drugs, since the biological activity of
the majority of these agents is due to their ability to affect the
DNA. The DNA-damaging properties of anticancer drugs towards
non-tumour cells (genotoxicity) are major drawbacks of cancer
∗ Corresponding author. Tel.: +351 217 512 100; fax: +351 217 582 754.
E-mail addresses: [email protected] (A. Suspiro), [email protected]
(J. Prista).
0378-4274/$ – see front matter © 2011 Elsevier Ireland Ltd. All rights reserved.
doi:10.1016/j.toxlet.2011.08.022
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chemotherapy and are related to serious adverse health effects
in treated patients. Beyond patient safety concerns, an increased
number of health care workers are potentially exposed to these
drugs, namely the pharmacists preparing and the nurses administering chemotherapy.
Several in vitro model systems have identified anticancer agents
as genotoxic for mammalian cells. Topoisomerase II inhibiting
drugs, for example, were demonstrated to induce multiple types
of genetic damage in mouse lymphoma cells (Boos and Stopper,
2000). Chromosomal aberrations and gene mutations induced by
several different anticancer agents were also evidenced in human
lymphoid cell lines (Yamada et al., 2000; Aydemir et al., 2005).
Genotoxicity was equally verified in in vivo rodent models – genotoxic as well as cytotoxic effects were demonstrated in mouse
A. Suspiro, J. Prista / Toxicology Letters 207 (2011) 42–52
bone marrow cells exposed to gemcitabine, topotecan and etoposide (Aydemir and Bilaloglu, 2003; Choudhury et al., 2004) while
chromosomal damage was evidenced in mouse male germ cells
exposed to etoposide (Marchetti et al., 2006). Human studies in
cancer patients treated with chemotherapy furthermore demonstrated DNA-damaging effects on normal non-target tissues such
as peripheral blood lymphocytes (Acar et al., 2001; Elsendoorn
et al., 2001; Torres-Bugarin et al., 2003; Padjas et al., 2005; Kopjar
et al., 2006). Occupational exposure to these drugs consequently
raises concerns regarding possible genotoxic effects on health care
professionals.
The dermal route of exposure is considered to have the predominant role in the uptake of anticancer agents by health care workers
(Sessink and Bos, 1999; Fransman et al., 2004) Multiple environmental wipe sampling studies have documented widespread
contamination of work surfaces, including the outer surface of
vertical laminar air flow cabinets, walls, floors, shelves, workbenches and equipments such as drug vials, syringes and control
pads of infusion pumps, in both preparation and administration
areas (Sessink et al., 1992; Nygren and Lundgren, 1997; Minoia
et al., 1998; Favier et al., 2005; Mason et al., 2005; Fransman
et al., 2007a; Touzin et al., 2008; Schierl et al., 2009; Connor
et al., 2010; Yoshida et al., 2011). Compliance with current safety
guidelines and correct use of personal protective equipment seems
to be insufficient to prevent some degree of dermal exposure.
Permeation of chemotherapy drugs through glove materials was
demonstrated in several experimental studies (Connor et al., 1984;
Laidlaw et al., 1984; Stoikes et al., 1984; Colligan and Horstman,
1990; Wallemacq et al., 2006) and is supported by the frequent
detection of cytostatics in the internal surface of the gloves used by
the workers while manipulating these drugs as well as on cotton
pads directly attached to the skin (Fransman et al., 2004; Minoia
et al., 1998; Mason et al., 2005; Ursini et al., 2006). The inhalation
route, although less well documented, may represent a supplementary route of exposure in some work conditions (Sessink and Bos,
1999).
In addition to studies assessing environmental contamination, biomonitoring studies using various available biomarkers are
increasingly used in order to demonstrate whether exposure is
associated with significant drug uptake and/or measurable biological effects. A critical appraisal of the more relevant of these
biomarkers is briefly presented in the following sections.
1. Biomarkers of exposure
A biomarker of exposure is defined as an exogenous substance
or its metabolite or the product of an interaction between a xenobiotic agent and some target molecule or cell that is measured in a
compartment within an organism (IPCS, 1993). In the case of anticancer agents, the intact drug or a derivative metabolite resultant
from biotransformation are measured, usually in urine samples.
The most extensively used biomarkers of exposure include urinary
cyclophosphamide and ifosfamide (detected by the same analytic
method), urinary platinum (indicative of exposure to platinum
compounds), urinary methotrexate and the urinary metabolite
of 5-fluoruracil, ␣-fluoro-␤-alanine. Some relevant studies using
these biomarkers are summarized in Table 1 (Sessink et al., 1992;
Nygren and Lundgren, 1997; Minoia et al., 1998; Mason et al.,
2005; Connor et al., 2010; Yoshida et al., 2011; Ursini et al., 2006;
Ensslin et al., 1994; Sessink et al., 1995; Ensslin et al., 1997; Burgaz
et al., 2002; Turci et al., 2002; Pethran et al., 2003; Cavallo et
al., 2005; Rekhadevi et al., 2007; Hedmer et al., 2008; Pieri et
al., 2010; Villarini et al., 2010; Maeda et al., 2010; Ndaw et al.,
2010). Most studies have relatively small sample sizes (14/20 with
up to 35 workers and only two studies including 100 or more
workers). Eleven studies used urinary samples, eight studies a 24 h
43
urine collection and one study an 8 h (last 4 h of shift and first 4 h
after shift) collection. The results appear to be similar for these
different sampling strategies in terms of percentage of positive
samples. Cyclophosphamide and ifosfamide are clearly the most
studied cytostatics (in 15 out of the 20 studies), but additional drugs
were also evaluated in several of them (including methotrexate,
doxorubicin, epirrubicin, paclitaxel, cytarabine and gemcytabine).
Globally, in the majority of the studies measurable levels of the
cytostatic drugs or their metabolites were detected in urine samples from exposed workers, indicating that significant absorption
occurs in most work situations. These results imply that, in spite
of the special guidelines and improved protective measures introduced in most countries during the last 2–3 decades, a significant
uptake of anticancer agents still occurs in most workplaces. At this
respect, in the 1990s Sessink reported the results of two evaluations on environmental contamination and biomarkers of exposure
5 years apart, before and after the implementation of additional
protective measures, including vertical laminar flow safety hoods,
special masks, double gloves and protected vials (Sessink et al.,
1997). In spite of the significant reduction achieved in the levels of
environmental contamination, urinary cyclophosphamide exhibited not only a similar proportion of positivity (8/25 versus 6/25)
but also an increase in the levels measures (0.01–0.5 ␮g versus
0.16–1.44 ␮g), suggesting that the interventions were ineffective
in preventing significant uptake of this drug by the workers. An
analogous conclusion was accomplished in a very complete review
published in 1996 and including all the studies available at that
time (Baker and Connor, 1996).
The two largest studies (published by Pethran in 2003 and
by Connor in 2010) are separated by a seven year time gap and
were performed in different countries (Germany and the USA,
respectively) and consequently do not allow a direct comparison
of results. Even so, it is undeniable that the results of the various
studies presented, which span from the 1970s until the present
time, show a progressive trend towards decreasing proportions of
positive biological samples. Negative biological samples, however,
should not be assumed to represent an absence of risk. Since even a
very low exposure level can theoretically be associated with genotoxic effects, the sensitivity of the analytical methods used from
measurement is a critical issue to be considered. Most studies use
gas chromatography–mass spectrometry (GC–MS) based techniques,
but there is some evidence that these may lack enough sensitivity
to detect low levels of cytostatics in urine samples, possibly due
to the fact that most of these compounds are relatively nonvolatile
(Sottani et al., 2010). Ndaw et al. (2010), for example, demonstrated
using a highly sensitive measuring method (high-performance liquid chromatography with tandem mass spectrometry – HPLC–MS/MS)
that the majority of the samples negative with GC–MS techniques
still had detectable levels of cytotoxic drugs. Mason et al. (2005)
refer similar findings, demonstrating that urine samples negative
by GC–MS conventional measuring techniques contained levels
of platinum detectable by the more sensitive inductively coupled
plasma-mass spectrometry. So, a negative urinary sample, especially
with conventional measuring techniques, does not imply absence
of risk. At this purpose, Ziegler et al. (2002) estimated that, assuming a linear dose–response, a level of urinary cyclophosphamide
below the detection threshold of conventional methods could still
correspond to an annual risk of cancer of 3–20/1,000,000.
Furthermore, one has also to consider that the adoption of
safety procedures has progressed heterogeneously across the various workplaces. These may thus differ widely regarding the level of
protective measures implementation as well as staff adherence to
these measures, explaining some divergent results. Rekhadevi et al.
(2007), for example, recently reported a study conducted on India,
where a high frequency of positive urinary samples was observed
(70%), ascribed by the authors to a lack of adequate protective
44
A. Suspiro, J. Prista / Toxicology Letters 207 (2011) 42–52
Table 1
Selected studies with biomarkers of exposure in health care personnel (nurses and pharmacists) handling anticancer drugs.
Authors
Number of
workers
Type of health care
personnel included
Biomarkers evaluated
(urine)
Method of urine
sampling
Results
Sessink 1992; Netherlands
25
Nurses and pharmacists
24 h collection
8+/25
32%
Ensslin 1994; Germany
21
Nurses and pharmacists
24 h collection
12+/21
57%
Sessink 1995; Netherlands
Ensslin 1997; Germany
28
13
Nurses
Pharmacists
24 h collection
24 h collection
11+/28
3+/13
39%
23%
Nygren 1997; Sweden
31
Nurses and pharmacists
Cyclophosphamide,
ifosfamide
Cyclophosphamide,
ifosfamide
Cyclophosphamide
Cyclophosphamide,
ifosfamide, platinum
Platinum
31+/31a
Minoia 1998; Italy
24
Nurses and pharmacists
Burgaz 1999; Turkey
Turci 2002; Italy
25
16 (62
samples)
Nurses
Nurses and pharmacists
Pethran 2003; Germany
100
Nurses and pharmacists
Pre and post-shift
samples
Pre and post-shift
samples
24 h collection
Pre-, post- and
middle of the shift
samples
24 h collection
Mason 2005; United Kingdom
50
Pharmacists
Cavallo 2005; Italy
Ursini 2006; Italy
Rekhadevi 2007; India
Hedmer 2008; Sweden
25
30
60
22
Nurses and pharmacists
Nurses and pharmacists
Nurses
Nurses and pharmacists
Connor 2010; USA
119
Nurses and pharmacists
Pieri 2010; Italy
Villarini 2010: Italy
Maeda 2010; Japan
56
40
8
Nurses and pharmacists
Nurses and pharmacists
Nurses and pharmacists
Ndaw 2010; France
Yoshida 2011; Japan
19
17
Nurses and pharmacists
Nurses
a
Cyclophosphamide,
ifosfamide
Cyclophosphamide
Cyclophosphamide,
ifosfamide, methotrexate,
platinum
Cyclophosphamide,
ifosfamide, doxorubicin,
epirrubicin, platinum
Cyclophosphamide,
ifosfamide, methotrexate,
platinum
␣-Fluoro-␤-alanine
␣-Fluoro-␤-alanine
Cyclophosphamide
Cyclophosphamide,
ifosfamide
Cyclophosphamide,
ifosfamide, paclitaxel,
cytarabine.,
␣-fluoro-␤-alanine
Doxorubicin, epirrubicin
Cyclophosphamide
Cyclophosphamide,
ifosfamide
␣-Fluoro-␤-alanine
Cyclophosphamide,
gemcytabine, platinum
100%
12+/24
50%
20+/25
22+/62
80%
36%
40+/100
40%
Pre and post-shift
samples
–/50
0
Pre-shift samples
Pre-shift samples
Pre-shift samples
Pre and post-shift
samples
8 h collection (last
4 h of shift and first
4 h after shift)
3+/30
3+/30
42+/60
–/22
3+/119
2.5%
Post-shift samples
Post-shift samples
24 h collection
10+/56
7+/40
–/8
18%
17.5%
0
Pre-shift samples
24 h collection
14+/19a
3+/17
74%
18%
10%
10%
70%
0
Ultra-sensitive measuring method.
measures. Consequently, data obtained in a particular occupational
setting cannot be easily transposed to different settings.
Therefore, when evaluating the results of studies using exposure
biomarkers, crucial factors such as the sensitivity of the analytical methods used and the specific characteristics of the workplace
studied must be taken in consideration and carefully scrutinized.
biomarkers used are relatively nonspecific, reflecting the influence
of multiple omnipresent and unavoidable environmental genotoxic
insults (Baker and Connor, 1996), an increased frequency of these
markers in exposed workers is a rather consistent finding in the
majority of the studies.
2.1. Chromosomal aberrations
2. Biomarkers of effect
A biomarker of effect is defined as a measurable biochemical,
physiological, behavioral or other alteration within an organism
that, depending upon the magnitude, can be recognized as associated with an established or possible health impairment of disease
(IPCS, 1993). When evaluating occupational exposure to anticancer
agents, the biomarkers of effect used for biomonitoring purposes
are mostly related to the genotoxic properties of these drugs. The
first study showing evidence of genotoxicity in healthcare workers
exposed do anticancer drugs was conducted on nurses in the 1970s
by Falck et al. (1979) using the urine genotoxicity or Ames test. In
the subsequent years, several studies using diverse genotoxicity
biomarkers have been published, some of which are summarized
in Table 2. Overall, only two out of the 29 studies are negative
(some studies using more than one biomarker, are negative for
one of them but positive for the other), supporting the hypothesis that occupational exposure to these drugs is associated with
some kind of biological impact, even if short-lived. The largest
study, published by Tompa et al. (2006), included 500 workers
and was positive for the two biomarkers analysed. Although all the
Chromosomal aberrations include changes in chromosome
numbers (numerical aberrations) as well as changes in chromosome structure (structural aberrations). They are evaluated in
cultured peripheral blood lymphocytes arrested at metaphase and
stained, usually by the G (Giemsa) band technique. Lymphocytes
are widely used for this purpose since they are easy to sample,
have a reasonably long life span and circulate throughout the
body possibly accumulating genetic damage as they pass through
specific target tissues. The additional use of fluorescence in situ
hybridization (FISH) with specific chromosomal probes enable a
greater sensitivity in the detection of subtle aberrations, unapparent by conventional G-banding, while allowing the depiction of the
precise chromosomes or chromosomal fragments involved in the
aberrations. Based on morphology and mechanism, chromosomal
aberrations are usually classified in two subgroups (Mateuca and
Kirsch-Volders, 2011):
• Chromosome-type aberrations involve the same locus on both
sister chromatids on one or multiple chromosomes. They usually reflect unrepaired double strand breaks occurring in resting
A. Suspiro, J. Prista / Toxicology Letters 207 (2011) 42–52
45
Table 2
Selected studies using genotoxicity biomarkers in workers exposed to anticancer agents.
Study
Number of workers
Global result
Values measured
Chromosomal aberrations
Nikula 1984
Burgaz 2002
Musak 2006
Tompa 2006
Testa 2007
Kopjar 2009
McDiarmid 2010
11
20
72
500
76
50
63
+
+
+
+
+
+
+
Sister chromatid exchange (SCE)
Norppa 1980
Thiringer 1991
Pilger 2000
Jakab 2001
Tompa 2006
Kopjar 2009
20
60
39
95
500
50
+
+
+
+
+
+
Micronuclei (MN)
Thiringer 1991
Maluf 2000
Pilger 2000
Hessel 2001
Cavallo 2007
60
10
39
100
23
−
−
−
−
+
Rekhadevi 2007
60
+
Cornetta 2008
Cavallo 2009
83
30
+
+
Rombaldi 2009
20
+
Comet assay
Underger 1999
Maluf 2000
Kopjar 2001
30
10
50
+
+
+
Ursini 2006
Yoshida 2006
Rekhadevi 2007
25
19
60
−
+
+
121
+
Cornetta 2008
Izdes 2009
Cavallo 2009
83
19
30
+
+
−
Rombaldi 2009
Connor 2010
20
68
+
−
Villarini 2010
52
+
Visual scores: 8.1 vs. 2.1 p = 0.0000; 4.7 vs. 2.3 p = 0.0000
Visual score: 20.83 ± 10.19 vs. 8.08 ± 5.16, p = 0.0006
Tail length 17.46 ± 1.9 vs. 12.5 ± 0.8, p < 0.05
% tail DNA 81.5 ± 4.3 vs. 70.0 ± 10.3, p < 0.05
Tail moment 43.2 vs. 28.6, p = NS
Tail length 8.5 vs. 5.1 p = 0.004
Mean TL 1.72 ± 0.15 vs. 0.71 ± 0.01, p < 0.05
Mean TM 0.29 ± 0.03 vs. 0.17 ± 0.05, p = NS
Tail length 0.76 ± 0.12 vs. 0.71 ± 0.09, p = 0.02
Tail moment 0.31 ± 0.25 vs. 0.25 ± 0.24, p = NS
Tail DNA 1.16 ± 0.78 vs. 0.73 ± 0.48, p < 0.001
Total comet score 21.0 ± 4.83 vs. 6.71 ± 2.81, p < 0.001
Tail DNA 12.0 ± 6.1 vs. 13.8 ± 9.8, p = NS
TM 34.6 ± 26.0 vs. 32.3 ± 12.8, p = NS
Damage index 18.86 ± 8.62 vs. 6.21 ± 2.78, p < 0.01
% tail DNA 53.0 vs. 53.12, p = NS
Tail moment 2.5 vs. 2.5, p = NS
% tail DNA 2.73 ± 0.28 vs. 1.76 ± 0.14, p = 0.001
HPRT mutation test
Deng 2005 (exposure to methotrexate)
Deng 2006 (exposure to vincristine)
21
15
+
+
% of mutant cells
1 ± 0.02 vs. 0.86 ± 0.01, p < 0.01
1.03 ± 0.02 vs. 0.87 ± 0.01, p < 0.05
Sasaki 2008
G0–G1 lymphocytes. During replication, chromosome duplication originates symmetric lesions on both sister chromatids.
Ionizing radiation, for example, produces mostly this type of aberrations.
• Chromatid-type aberrations affect only one of the sister chromatids on one or more chromosomes. They originate from several
types of lesions (base alterations, crosslinks, single strand breaks)
induced by S-phase-dependent agents like the majority of chemical mutagens.
Some relevant studies using chromosomal aberrations in health
care workers occupationally exposed to anticancer agents are summarized in Table 2 (Burgaz et al., 2002; Nikula et al., 1984; Musak
et al., 2006; Tompa et al., 2006; Testa et al., 2007; Kopjar et al.,
2009; McDiarmid et al., 2010). All of them demonstrated increased
% of cells with aberrations
6.3 ± 0.7 vs. 4.6 ± 0.9, p ≤ 0.05
2.55 ± 1.63 vs. 1.01 ± 0.97, p < 0.01
1.90 ± 1.34 vs. 1.26 ± 0.93, p = 0.01
2.32 ± 0.10 vs. 1.72 ± 0.25, p < 0.05
11.2 vs. 3.04, p < 0.0001
4.48 ± 0.33 vs. 0.86 ± 0.09, p < 0.001
Chromosome 5: 0.29 vs. 0.04, p = 0.01
Chromosome 7: 0.18 vs. 0.09, p = NS
Chromosome 11: 0.24 vs. 0.15, p = NS
% of cells with SCE
9.4 ± 0.3 vs. 8.1 ± 0.3, p < 0.05
6.4 vs. 6.0, p < 0.05
10.1 ± 1.2 vs. 9.9 ± 1.4, p = 0.03
HFC1 : 12.0 ± 1.77 vs. 3.72 ± 0.84, p < 0.05
6.57 ± 0.06 vs. 6.44 ± 0.14, p < 0.05
5.63 ± 2.28 vs. 4.42 ± 1.32
HFC1 : 9.65 vs. 5.46%, p < 0.01
Number of MN/1000 binucleated cells
3.0 vs. 2.9, p = NS
13.5 ± 6.05 vs. 11.5 ± 5.2, p = NS
21.2 ± 7.2 vs. 23.3 ± 7.5, p = NS
0.01 vs. 0.009, p = NS
PBL2 : 8.15 ± 3.6/10.9 ± 4.7 vs. 7.55 ± 2.4, p = NS
EBC3 : 0.92/0.94 ± 0.7 vs. 0.45 ± 0.4, p = 0.051
PBL1 : 17.8 ± 1.88% vs. 3.73 ± 0.8%, p < 0.05
EBC2 : 2.66 ± 0.83 vs. 1.86 ± 0.62, p < 0.05
13.81 ± 6.94% vs. 8.12 ± 4.10%, p < 0.0001
PBL1 : 8.73 vs. 8.04, p = NS
EBC2 : 0.85 vs. 0.48, p = 0.042
4.94 ± 1.95 vs. 2.88 ± 0.78, p = 0.01
frequencies of aberrations in exposed workers, supporting the
excellent sensitivity of this biomarker for the detection of low levels
of DNA damage such as the ones presumed to occur in the occupational setting. The magnitude of the observed increase, however, is
relatively small (1.5–3.5× in most studies).
The majority of the studies examined the global frequency of
chromosomal aberrations, involving all chromosomes. An interesting exception is the study by McDiarmid et al. (2010), in which
specific chromosome abnormalities, associated with therapyrelated hematological malignancies, were analysed by FISH. In
effect, anticancer treatment is associated with an increased incidence of secondary therapy related acute myeloid leukemia
and myelodysplastic syndrome (Rowley et al., 1977; Sandoval
et al., 1993; Smith et al., 1994). These hematological malignancies are associated with characteristic nonrandom chromosomal
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A. Suspiro, J. Prista / Toxicology Letters 207 (2011) 42–52
aberrations with two main patterns: loss of all or part of chromosomes 5 and 7, after therapy with alkylating agents, and balanced
translocations of the long arm of chromosome 11, after therapy
with topoisomerase II inhibitors (Pedersen-Bjegaard et al., 2002). In
McDiarmid study an increased frequency of chromosomal aberrations involving chromosomes 5 and 7, similar to those described in
therapy-related hematological malignancies, was demonstrated in
workers exposed to anticancer drugs. The results from McDiarmid
report also suggest that the analysis of specific chromosomal aberrations may be associated with a more pronounced effect than the
study of global abnormalities, potentially increasing the sensitivity
of the test – an increase of approximately 7× in the anomalies on
chromosome 5 was detected as compared to the control group.
Chromosomal aberrations represent the most extensively used
and validated biomarker in populations exposed to genotoxic
agents (Albertini et al., 2000), based on the assumption that the
genetic damage detected in these cells reflects a similar degree of
damage in target cells undergoing carcinogenesis (Boffetta et al.,
2007). Its association with cancer risk was demonstrated by several independent prospective cohort studies published in the last
two decades. In the beginning of the 1990s, two large independent
studies confirmed for the first time an association between an elevated frequency of chromosomal aberrations in peripheral blood
lymphocytes and an increased incidence of cancer. The results
from the Nordic Study Group on the Health Risk of Chromosome
Damage refer to the prospective follow up of a cohort with 2.969
individuals from several Nordic countries, tested between 1970
and 1988 (Brogger et al., 1990; Hagmar et al., 1994). A significant
association was verified between the frequency of chromosomal
aberrations in peripheral blood lymphocytes and an increased cancer incidence (Standardized Incidence Ratio = 2.1). The second report
refers to an Italian cohort with 1.455 individuals with a follow
up time of 16.190 person-years; a significant increase in the incidence of multiple cancer types was observed in individuals with a
medium and high frequency of chromosomal aberrations (Bonassi
et al., 1995). These early reports were confirmed by a later publication with the combined results of both cohorts, demonstrating
an increased cancer incidence in healthy individuals with an elevated frequency of chromosomal aberrations in peripheral blood
lymphocytes (Standardized Incidence Ratio = 1.53 for the Nordic
cohort and Standardized Mortality Ratio = 2.01 for the Italian cohort)
(Bonassi et al., 2000). The increased risk was related to the frequency of chromosomal aberrations per se, being independent of
age, sex, smoking habits and occupational exposure to carcinogenic agents. A subsequent study suggested that both subclasses of
chromosomal aberrations (chromosome-type and chromatid-type)
have similar predictive values (Hagmar et al., 2004). A recent publication study by Boffetta et al. (2007), spanning a time period of
25 years, reported a cumulative cancer incidence of 3.1% and a relative risk of 1.78 with a cancer type distribution similar to the one
observed in the general population (the most common neoplasms
being from the lung, breast, colon and rectum, stomach, hematologic system and head and neck). Chromosomal aberrations were
also validated as a biomarker in occupational settings other than
exposure to anticancer agents. For instance, a significant association was found between the frequency of chromosomal aberrations
in peripheral blood lymphocytes and cancer incidence in a group of
miners exposed to radon – the authors estimated that an increase
of 1% in the frequency of chromosomal aberrations was associated
with an increased cancer incidence of 64% (Smerhovsky et al., 2001).
In spite of its excellent sensibility and comproved predictive
value regarding cancer risk, the detection of chromosomal aberrations is a tedious, technically demanding and morose process,
requiring relatively large quantities of biological material. For these
reasons, alternative biomarkers have been developed and are progressively being tested on occupational biomonitoring studies.
2.2. Sister chromatid exchanges
Sister chromatid exchanges (SCE) result from symmetrical
exchange of DNA replication products between sister chromatides
at a given locus and do not result in any alteration in chromosome number or structure. They can be visualized in cultured cells
when division is induced in the presence of 5-bromodeoxyuridine
(BRDU). The frequency of SCE has been suggested as a very sensitive
test, being able to detect genotoxic effects at much lower concentrations than those required to produce chromosomal aberrations
(Chia and Lee, 2001). The concept of high frequency cells (HFCs) was
introduced in order to further increase the sensitivity of the assay
– instead of measuring the global frequency of SCE, only the percentage of cells with an increase of SCE above the 95th percentile
(the HFCs) is considered. These cells are postulated to represent a
subgroup of long-lived lymphocytes that have accumulated several
SCE-inducing lesions over time (Testa et al., 2007). Analyzing the six
studies using SCE as a biomarker included in Table 2 (Tompa et al.,
2006; Kopjar et al., 2009; Norppa et al., 1980; Thiringer et al., 1991;
Pilger et al., 2000; Jakab et al., 2011) we verify that the magnitude
of the increase observed in the exposed group when considering
global SCE is indeed very small; when HFCs are considered instead
of global SCE, this magnitude reaches 1.8–3.2×.
There is some degree of uncertainty regarding the significance
of increased SCE frequency. The biological mechanism underlying
SCE is still unknown and the predictive value of increased SCE frequency with regard to cancer risk is far from established. The initial
reports from the Nordic Study Group on the Health Risk of Chromosome Damage referred a lack of correlation between the frequency
of SCE and cancer incidence (Brogger et al., 1990; Hagmar et al.,
1994). These results were subsequently confirmed by the combined Central Europe cohort study (Hagmar et al., 1998) and more
recently by a specific study conducted by Bonassi et al. (2004).
The later is a prospective cohort study including 1.621 individuals tested between 1991 and 1993 and analysed not only the global
frequency of SCE, but also the frequency of HFCs. No association
was found between increased levels of HFCs and risk of cancer. The
use of SCE as a biomarker has thus been declining, in favor of more
recent and promising methods such as the micronuclei test and the
comet assay.
2.3. The micronuclei test
Micronuclei are small collections of enveloped nuclear material
present in the cytoplasm that separate from the main nucleus during cellular division. The formation of micronuclei in dividing cells
results either from chromosome breakage (clastogenesis) or from
chromosome malsegregation due to mitotic malfunction (aneugenesis). Consequently, micronuclei content may correspond to whole
chromosomes with a centromere or to acentric chromosomal fragments. The most widely used test for the detection of micronuclei
is based on stimulation of a culture of sample cells in the presence
of a chemical agent which inhibits cellular division while enabling
nuclear division and for this reason is also known as the cytokinesisblock micronucleus (CBMN) test. Micronuclei are counted on the
binucleated cells formed and expressed as number of micronuclei
per 1000 binucleated cells. The micronuclei count should include
only binucleated cells in order maximize the sensitivity and specificity of the test, avoiding the confounding influence of alterations
in the cellular division kinetics (Fenech, 2002; Norppa and Falck,
2003). The CBMN test is usually performed in peripheral blood
lymphocytes, although other cells types (for example, exfoliated
epithelial cells from nasal or buccal mucosa) can also be used.
As pointed out, the CBMN test detects two different kinds of
genetic damage, which can be differentiated using FISH with pancentromeric DNA probes: (a) Chromosome fragmentation resulting
A. Suspiro, J. Prista / Toxicology Letters 207 (2011) 42–52
from the action of clastogenic agents. The acentric chromosome
fragments cannot be incorporated in the main nucleus after cellular
division and thus are retained in the cytoplasm as micronuclei. The
micronuclei content is thus centromere negative. (b) Abnormalities
affecting chromosome segregation and migration during mitosis.
These abnormalities are associated with alterations in chromosome
numbers in the two resultant daughter nuclei and thus reflect the
action of aneugenic agents. The micronuclei content is centromere
positive.
Besides this application using pancentromeric probes, FISH with
chromosome-specific probes can reveal precisely which chromosomes or chromosomic fragments are present in the micronuclei.
The use of probes specific for sex chromosomes, for example,
demonstrated that the increase in micronuclei frequency observed
in females is related to a raised number of centromeric positive micronuclei containing X chromosomes (Norppa and Falck,
2003). The number of Y chromosome positive micronuclei also rises
with advancing age. Therefore, the positive correlation observed
between micronuclei and age seems to be related with the sex
chromosomes in both genders (Norppa and Falck, 2003). Besides
age and gender, the results of the CBMN are influenced by the seric
levels of folate and vitamin B12, and, in some studies, by the body
mass index and the physical activity (Battershill et al., 2008).
The CBMN has several advantages, such as the speed and ease
of analysis, the fact that requires small amount of sample material
and the ability to be performed in almost all cell types. Furthermore, the large number of cells analysed (1000–3000 per sample
as compared, for instance, to 100 in the comet assay) confers this
test substantial statistical power (Pedersen-Bjegaard et al., 2002).
Some relevant studies using CBMN in workers exposed to anticancer drugs are presented in Table 2 (Rekhadevi et al., 2007;
Thiringer et al., 1991; Pilger et al., 2000; Maluf and Erdtmann, 2000;
Hessel et al., 2001; Cavallo et al., 2007, 2009; Cornetta et al., 2008;
Rombaldi et al., 2009). Positive studies usually show a magnitude
of effect around 2×. Interestingly, the study with the greater magnitude of effect (4.7×) is reported by Rekhadevi et al. (2007), and
was accompanied by a high level of exposure and drug uptake. In
the studies where FISH was used in addition to CBMN, the majority of micronuclei are centromere negative, in accordance with the
clastogenic properties of most chemical mutagens. In some individual cases, however, a significant proportion (up to 50%) of the
micronuclei were centromere positive, a finding correlated by the
authors with the manipulation of the anticancer agent vinorrelbin, a potentially aneugenic mitotic spindle inhibitor (Cavallo et al.,
2007).
Several lines of evidence support an association between
micronuclei induction and cancer development. An increased frequency of micronuclei has been described as a consequence
of the genotoxic effects of anticancer drugs such as etoposide
(Choudhury et al., 2004) and cytosine–arabinoside (Palo et al.,
2009). An augmented micronuclei frequency was also described
in patients affected by congenital cancer syndromes such as the
chromosomal-breakage syndromes. These rare cancer-prone disorders are characterized by an increased frequency of chromosome
breakage and rearrangement, evidenced when cells from affected
patients are stimulated in vitro and include Bloom syndrome,
Fanconi anemia, ataxia-telangiectasia and xeroderma pigmentosum
(Rosin and German, 1985). An increased frequency of micronuclei was described in buccal and urinary tract exfoliated epithelial
cells from patients with Bloom syndrome (Rosin and German,
1985). In addition, Gisselson et al. (2001) demonstrated the presence of micronuclei in the majority (71–86%) of cancer cells
from several types of tumour. Micronuclei are also present with
augmented frequency in peripheral blood lymphocytes from cancer patients. Duffaud et al. (1997), for example, studied 198
patients with several types of cancer before therapy and found a
47
significantly increased basal frequency of micronuclei in circulating peripheral blood lymphocytes as compared to matched healthy
individuals (21.1 ± 15.3 versus 9.7 ± 2.8 in males and 19.1 ± 11.2
versus 9.8 ± 3.1 in females). This augmented basal level further
increased after exposure to genotoxic insult as a consequence of
chemotherapy (Acar et al., 2001; Elsendoorn et al., 2001; TorresBugarin et al., 2003; Padjas et al., 2005).
The first prospective studies supporting an association between
micronuclei frequency and cancer risk are now beginning to
emerge. Bonassi reported the results from a cohort of 6.718
individuals tested between 1980 and 2002: an increased cancer
incidence was demonstrated in healthy individuals with an elevated micronuclei frequency (relative risk = 1.84) (Bonassi et al.,
2007). Subsequently, a nested case–control study from the same
cohort confirmed an association between increased frequency of
micronuclei in peripheral blood lymphocytes (superior to 2.5 per
1000 binucleated cells) and cancer incidence (4.7 ± 3.4 versus
1.5 ± 1.7, p < 0.0001) (Murgia et al., 2008).
As mentioned, the CBMN can be used to study cells other than
peripheral blood lymphocytes. A series of studies from Cavallo
et al. (2007, 2009) evaluated, in addition do peripheral lymphocytes, exfoliated epithelial cells from the buccal mucosa. The
difference in the frequency of micronuclei between two groups
of exposed individuals and nonexposed controls was more pronounced in buccal epithelial cells (0.92 and 0.94 versus 0.45,
p = 0.051) than in peripheral blood lymphocytes, where the difference failed to reach statistical significance (8.15 and 10.9 versus
7.5). The application of the CBMN to other cell populations, however, presents some potential shortcomings that must be carefully
addressed. Even assuming a closer proximity to the exposition
source, micronuclei frequency in epithelial cells is lower and consequently more difficult to detect. Effectively, peripheral blood
lymphocytes are cultured and stimulated to divide and therefore the micronuclei counted are formed in vitro during this
mitosis. In terminally differentiated epithelial cells, on the other
hand, only the micronuclei formed in vivo are counted (Albertini
et al., 2000; Norppa and Falck, 2003). Furthermore, the association between increased micronuclei frequency and cancer risk was
established for peripheral blood lymphocytes and cannot be readily extrapolated to other cell types. It is conceivable to extend it
to target cells directly involved in carcinogenesis (for example,
exfoliated cells from the urinary tract in individuals exposed to
cyclophosphamide) but not to non-target cells such as epithelial
buccal or nasal cells. Accordingly, peripheral blood lymphocytes
should currently continue to be the favored cells for the CBMN
assay.
2.4. In vivo comet assay or single cell gel electrophoresis (SCGE)
The comet assay consists, in the classical and still most widely
used technique described by Singh et al. (1988), of a single cell
suspension embedded in agarose and layered onto a microscope
slide, after lyse to liberate DNA content and electrophoresis under
alkaline conditions (pH > 13). The resultant product can be visualized after staining with a suitable dye or using fluorescence.
Cells with increased levels of damaged and fragmented DNA
show increased migration. The comet assay detects an admixture of primary DNA strand breaks, alkali-labile sites (secondary
strand breaks generated during alkaline treatment) and incomplete excision repair sites (Moller et al., 2000). For an adequate
evaluation, at least 100 cells per individual must be analysed
(Albertini et al., 2000). There are several scoring systems to measure the degree of DNA damage detected by the comet assay,
including either visual scores as well as quantitative parameters
such as tail length (maximum length of DNA migration measured
from the estimated leading edge), percentage of migrated DNA
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A. Suspiro, J. Prista / Toxicology Letters 207 (2011) 42–52
(fraction of total DNA present in the tail) and tail moment (tail
length multiplied by the fraction of tail DNA) (Albertini et al.,
2000). The results of the comet assay do not seem to be significantly affected by age or gender; possible confounding factors
include body mass index, physical activity, environmental pollution and sunlight exposure (Battershill et al., 2008; Moller et al.,
2000).
The comet assay has a number of advantages, namely a high
sensitivity for detecting low levels of DNA damage, the requirement for small numbers of viable cells per sample, the simplicity
and short time of test performance and the relatively low cost. In
addition, it can be performed in various types of cells and tissues
(Moller et al., 2000; Brendler-Schwaab et al., 2005). The interpretation of the results obtained, however, must be addressed with some
precautions. The DNA damage detected by the comet assay can be
originated not only from genotoxic insults but also by DNA degradation related to necrosis and apoptosis resulting from cytotoxic
effects (Anderson and Plewa, 1998). The frequency of these events
in peripheral blood is expected to be extremely low, so this probably
does not represent an issue when evaluating peripheral blood lymphocytes. However, in terminally differentiated cell populations
such as epithelial buccal cells, these are frequent events (Albertini
et al., 2000). In this setting false positive results from cytotoxic
effects must be excluded, for instance with the concurrent use of a
vital dye such as trypan blue to assure a cellular viability level > 70%
(Anderson and Plewa, 1998). The strand breaks detected by the
comet assay may also correspond to normal responses to DNA damage, either in the form of repair mechanisms or in the form of
apoptosis. Ongoing excision repair, for example, may increase DNA
migration due to incision-related strand breaks while the apoptotic
process is associated with enzymatic cleavage of nuclear DNA by
specific endonucleases, originating an extremely fragmented product, which tends to accumulate in the comet tail (Moller et al.,
2000). Another aspect to consider is that the presence of a crosslinking agent (like most alkylating agents) can retard DNA migration
and thus obscure the increased migration related with damage
(Albertini et al., 2000). The primary lesions detected by the comet
assay may be correctly repaired and not result in permanent genetic
alterations. This transitory nature of some of the damage detected
makes sampling time a critical issue – short-lived primary DNA
injury such as single strand breaks, which undergo rapid repair, can
be missed when sampling times are inadequate (more than 2–6 h
after exposure) (Brendler-Schwaab et al., 2005).
The results of several studies using the comet assay in health
care workers handling anticancer agents are summarized in Table 2
(Connor et al., 2010; Ursini et al., 2006; Rekhadevi et al., 2007;
Villarini et al., 2010; Maluf and Erdtmann, 2000; Cornetta et al.,
2008; Cavallo et al., 2009; Rombaldi et al., 2009; Undeger et al.,
1999; Kopjar and Garaj-Vrohac, 2001; Yoshida et al., 2006; Sasaki
et al., 2008; Izdes et al., 2009). They vary widely in results, although
the majority (6 out of 8) report detectable levels of DNA damage.
The parameters chosen and the methods used to assess this damage
differ from study to study which, added to the large inter-individual
variability intrinsic to the comet assay, renders inter-study comparison somehow difficult. Surprisingly, the intensity of damage in
healthy individuals with occupational exposure to genotoxic agents
(characterized by a low intensity and a long duration) seems to
be equivalent to the one measured in cancer patients undergoing
chemotherapy (a high dose and short duration exposure), suggesting that the intensity of the effect measured by the comet assay
cannot be used as an indicator of the intensity of exposure (Moller,
2006).
Given the short-lived quality of the DNA damage detected
by this assay, its significance as a marker of increased cancer
risk remains uncertain. In the absence of prospective studies
demonstrating an increased cancer risk, the comet assay must be
considered, for the time being, as a biomarker of exposure rather
than a biomarker of effect (Moller, 2006).
2.5. Mutation tests
Cytostatics induced mutagenesis has been less studied than
other aspects of genotoxicity, although these agents are demonstrated chemical mutagens in experimental models (Yamada et al.,
2000) and in human studies (Salas et al., 2011). At the present
moment, the HPRT assay, performed in peripheral blood lymphocytes, is considered by the International Program on Chemical
Safety as the only mutation test with sufficient standardization
for widespread use as a biomarker (Albertini et al., 2000). The
HPRT gene codifies for the enzyme hypoxanthine–guanine phosphoribosyltransferase, involved in purine metabolism. In addition,
this enzyme catalyses the conversion of purine analogues such
as 6-thioguanine into toxic cellular compounds. When mutation
occurs, mutant cells are deficient in HPRT enzymatic activity and
thus survive treatment with 6-thioguanine. The most widely used
HPRT mutation test identifies the presence of gene mutations based
on the phenotype expressed when cells are incubated with 6thioguanine. An increase in HPRT deficient cells in an exposed
population relative to an appropriate control indicates a mutagenic effect (Albertini et al., 2000). Deng and co-workers recently
published two studies analysing HPRT mutations in manufacturing workers exposed to two anticancer agents (methotrexate and
vincristine). In both a significant increase in the frequency of HPRT
mutants was found in the exposed group (Deng et al., 2005, 2006).
The implications of a positive mutation test have not been evaluated yet by prospective human studies, although some evidence
suggests a possible association with cancer. Similar mutations are
induced in animal models by known carcinogens (Albertini et al.,
2000). Additionally, the type of mutations induced by cytotoxic
agents (large deletions involving topoisomerase II binding regions
or originating fusion genes) are equivalent to those described in
cancer-related genes, and substantially different of the point mutations that arise spontaneously (Albertini et al., 2000).
Table 3 summarizes the main characteristics of the more relevant biomarkers of effect, according to the issues discussed
throughout this section.
3. Biomarkers of susceptibility
A biomarker of susceptibility is defined as an indicator of an
inherent or acquired ability of an organism to respond to the challenge of exposure to a specific xenobiotic substance (IPCS, 1993).
Genetic polymorphisms represent a substantial component of individual susceptibility to chemical agents. With regard to anticancer
drugs, two types of genetic polymorphisms have been studied: (a)
in genes whose products are involved in xenobiotic metabolism,
mostly members of glutathione S-transferases (GSTs) superfamily
of phase II enzymes; (b) in genes whose products are involved in
DNA repair.
3.1. GSTs polymorphisms
Several polymorphisms have been described in the GSTs, many
of them with an unknown impact on enzyme activity. Two members of the GST family (GSTM1 and GSTT1) are homozygously
absent (null genotype) in a substantial fraction of the general population (approximately 50% for GSTM1 and 20% for GSTT1) (Smith
et al., 1995). Musak et al. (2006) described an increased frequency of
chromosomal aberrations in workers exposed to anticancer agents
and carrying the null genotype of these two enzymes. Villarini et al.
(2010), on the other hand, found no correlation between genotoxic effects (DNA damage measured by the comet assay) and the
A. Suspiro, J. Prista / Toxicology Letters 207 (2011) 42–52
49
Table 3
Comparative appraisal of the most important biomarkers of effect.
Biomarker
Type of sample
Technical characteristics
Demonstrated association
with increased cancer risk
Applicability to large scale
monitoring
Chromosomal aberrations
• Peripheral blood
• Relatively large sample
required
• Demanding
• Morose
Yes
Difficult
No
Difficult
Emerging
Yes
No
Yes
No
Difficult
Sister chromatid exchange
Micronuclei
• Peripheral blood
• Relatively large sample
required
• Mostly peripheral blood
• Applicable to almost all
cell types (e.g. Exfoliated
epithelial cells)
• Small sample size
Comet assay
• Any type of cell
• Small sample size
Mutation tests
• Peripheral blood
• Relatively large sample
required
• Requires high degree of
technical expertise
• Demanding
• Requires some technical
expertise
• Undemanding
• Fast
• Easy and relatively
standardized
interpretation
• Undemanding
• Fast
• Easy but less
standardized and more
heterogeneous
interpretation
• Demanding
• Requires some technical
expertise
GSTM1/GSTT1 null genotype. Likewise, Testa et al. (2007) were
unable to demonstrate an association between genotoxicity (frequency of chromosomal aberrations) and the polymorphisms of
four GSTs (GSTM1, GSTT1, GSTP1 and GSTA1). Due to the relatively small number of individuals included in these studies (72
in Musak study, 76 in Testa’s and 52 in the Villarini one) no definite
conclusion can presently be retrieved.
3.2. DNA repair enzymes polymorphisms
The individual response to the DNA damage induced by xenobiotics depends largely on the efficiency of DNA repair mechanisms.
The base excision repair (BER) system is responsible for the removal
of small DNA adducts that do not significantly distort the double helix structure and for the repair of single-strand breaks. The
gene XRCC1 (X-ray cross-complementing group 1) codifies one of
the BER enzymes and has 3 known polymorphisms. One of them,
399Gln (a G → A transition at codon 299 of exon 10), affects the
PARP (poly ADP ribose polymerase) binding region and is associated with a significant reduction in enzymatic activity (Cheng et al.,
2009). Cornetta et al. (2008) reported an increased genotoxic effect
(increase frequency of micronuclei in peripheral blood lymphocytes) in nurses exposed to anticancer agents and carrying at least
one variant allele with the 399Gln polymorphism. Similar findings
were reported by Laffon et al. (2005), also using the micronuclei
test.
The DNA homologous recombination repair system is responsible for the repair of double-strand breaks and is essential
for maintaining genomic stability. The XRCC3 (X-ray crosscomplementing group 3) gene is a member of the Rad51 family
which codifies for an enzyme involved in homologous recombination repair and has a common polymorphism (a C → T transition)
at codon 241 of exon 7. Musak et al. (2006) describe an association between this polymorphic variant and increased frequency of
chromosomal aberrations in workers exposed to anticancer drugs,
while Cornetta et al. (2008) and Laffon et al. (2005) were unable
to correlate this polymorphism with the frequency of peripheral
blood lymphocytes micronuclei in the same occupational setting.
Further larger scale studies are necessary to establish if any
correlation exists between these genetic polymorphisms and the
intensity of frequency of genotoxic effects and whether this translates in an increased cancer risk.
4. Final comments
Widespread environmental contamination with anticancer
agents is a recognized and universal finding in the healthcare setting. Consequently, occupational exposure to these drugs is an
obligatory hazard for an increasing number of health care workers, mostly nurses and pharmacists. Current safety guidelines and
personal protective equipment are insufficient to prevent significant uptake, as evidenced by detectable levels of cytostatic
drugs or its metabolites present in urine samples from exposed
workers. Furthermore, the results of the majority of the studies
using effect biomarkers, persistently demonstrate an increased frequency of genotoxicity indicators in exposed workers as compared
to controls. Some of these biomarkers, namely peripheral blood
lymphocytes chromosomal aberrations and micronuclei, have an
established association with an increased cancer incidence and
therefore justify some concern.
It is acknowledged that, in most workplaces, there is a clear
trend towards a progressive decline in the levels of exposure,
probably related to safer handling practices and the improved personal protective equipments introduced. Fransman, for instance,
reported a combined analysis of 3 cross-sectional studies evaluating occupational exposure to anticancer agents conducted in
the Netherlands over a 5-year period (1997, 2000 and 2002). A
significant decrease in the levels of environmental contamination and a parallel decrease in the percentage of workers with
detectable urinary cyclophosphamide, either in outpatient clinics
(6.6–1.7%) as well as in oncology wards (12.4–2.9%) were demonstrated (Fransman et al., 2007b). Similar results were reported by
Sottani et al. (2010), which observed a significant decline in surface
contamination and in the percentage of positive biological samples
(from 30% in 1990 to 2% in 2010) in 5 Italian pharmacies. However, based on current scientific knowledge, it is impossible to set a
level of exposure that, beyond doubt, will not cause adverse effects,
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A. Suspiro, J. Prista / Toxicology Letters 207 (2011) 42–52
since most genotoxic responses do not have a threshold (Henderson
et al., 2000). Accordingly, the goal should be to aim for the lowest
environmental contamination as is reasonably achievable (as low as
reasonably achievable – ALARA) (Uva, 2006) and for zero positive biological samples. Taking into consideration this purpose, additional
improvements are clearly required in most workplaces and should
be regarded as a main concern in the prevention of occupational
exposure to anticancer drugs. A similar inference can be taken from
a previous review on this same subject, were the authors concluded that preventive efforts should be focused on wide-spread
implementation of improved handling practices (Baker and Connor,
1996).
The quantification of genotoxicity biomarkers reflects the global
impact of genotoxic insults, rather than the effect of specific
anticancer agents and therefore is particularly suitable for the
assessment of multiple and complex exposures such as the occupational handling of chemotherapy drugs. Chromosomal aberrations
are presently the most validated biomarker and must be considered as the gold standard for comparison with more recent
tests. Nonetheless, the CBMN assay is a very promising alternative, more appropriate for large scale biomonitoring, providing
further prospective studies confirm its association with cancer risk.
The CBMN test and the comet assay present some degree of complementarity. They detect different although overlapping types of
genetic damage and represent distinctive kinds of biomarker: the
CBMN is deemed an effect biomarker while the comet assay should
be considered an exposure biomarker. Furthermore, the CBMN
detects permanent genetic damage, expressed when cells divide,
and thus reflect cumulative events that may have occurred long
before the biological sample was collected. The comet assay, on the
other hand, detects transitory short-lived DNA damage which may
have originated minutes or hours after sample collection and thus
reflects short-term exposure effects. The combinations of these 2
markers therefore represents a promising and attractive approach,
increasingly adopted by several studies (Rekhadevi et al., 2007;
Battershill et al., 2008; Cavallo et al., 2007, 2009; Cornetta et al.,
2008).
The application of selected biomarkers has the potential to offer
additional and valuable information regarding the effectiveness
of the protective measures and safety guidelines implemented in
order to prevent a negative health impact on the workers exposed
to these necessary but still hazardous drugs.
Conflict of interest statement
None.
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