Biomarkers for early diagnosis of malignant mesothelioma: Do we need another moonshot?

Abstract

Early diagnosis of malignant pleural mesothelioma (MPM) is a challenge for clinicians. The disease is usually detected in an advanced stage which precludes curative treatment. We assume that only new and non-invasive biomarkers allowing earlier detection will result in better patient management and outcome. Many efforts have already been made to find suitable biomarkers in blood and pleural effusions, but have not yet resulted in a valid and reproducible diagnostic one. In this review, we will highlight the strengths and shortcomings of blood and fluid based biomarkers and highlight the potential of breath analysis as a non-invasive screening tool for MPM. This method seems very promising in the early detection of diverse malignancies, because exhaled breath contains valuable information on cell and tissue metabolism. Research that focuses on breath biomarkers in MPM is in its early days, but the few studies that have been performed show promising results. We believe a breathomics-based biomarker approach should be further explored to improve the follow-up and management of asbestos exposed individuals.

Full text

Oncotarget1
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www.impactjournals.com/oncotarget/ Oncotarget, Advance Publications 2017
Biomarkers for early diagnosis of malignant mesothelioma: Do
we need another moonshot?
Sabrina Lagniau1,2, Kevin Lamote1,2, Jan P. van Meerbeeck2,3,* and Karim Y.
Vermaelen1,2,*
1Tumor Immunology Laboratory, Department of Respiratory Medicine, Ghent University Hospital, 9000 Ghent, Belgium
2Department of Internal Medicine, Ghent University, 9000 Ghent, Belgium
³Thoracic Oncology/MOCA, Antwerp University Hospital, 2650 Edegem, Belgium
*Joint senior authors
Correspondence to: Karim Y. Vermaelen, email: Karim.vermaelen@ugent.be
Keywords: mesothelioma, biomarkers
Received: November 24, 2016 Accepted: May 01, 2017 Published: May 16, 2017
Copyright: Lagniau et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC-BY),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
ABSTRACT
Early diagnosis of malignant pleural mesothelioma (MPM) is a challenge for
clinicians. The disease is usually detected in an advanced stage which precludes
curative treatment. We assume that only new and non-invasive biomarkers allowing
earlier detection will result in better patient management and outcome. Many efforts
have already been made to nd suitable biomarkers in blood and pleural effusions, but
have not yet resulted in a valid and reproducible diagnostic one. In this review, we
will highlight the strengths and shortcomings of blood and uid based biomarkers and
highlight the potential of breath analysis as a non-invasive screening tool for MPM.
This method seems very promising in the early detection of diverse malignancies,
because exhaled breath contains valuable information on cell and tissue metabolism.
Research that focuses on breath biomarkers in MPM is in its early days, but the few
studies that have been performed show promising results. We believe a breathomics-
based biomarker approach should be further explored to improve the follow-up and
management of asbestos exposed individuals.
INTRODUCTION
Malignant pleural mesothelioma (MPM) is a rare
and aggressive cancer originating from the mesothelial
cells of the pleura. MPM is mostly an occupational disease,
affecting more men than women [1]. Although the causal
link to asbestos exposure is well documented, and the latter’s
industrial use has been fully banned in Europe, asbestos is
still being processed in large parts of the developing world
[2]. Asbestos is a general name for naturally occurring
mineral silicate bers (e.g. serpentine and amphiboles),
popular for industrial usage because of their high tensile
strength and resistance to thermal and chemical degradation
[3]. In 1960 already, Wagner et al. reported that asbestos had
genotoxic and carcinogenic properties [4]. When asbestos
bers are inhaled in the lungs, they cause oxidative stress
and chronic inammation. Because of the high iron content
of these bers, Fenton-like reactions take place, resulting in
the constant generation of reactive oxygen species (ROS).
Furthermore, chronic inammation is due to the prolonged
phagocytic activity of macrophages engulng the inhaled
asbestos bers [5]. This process generates both ROS and
reactive nitrogen species (RNS), which both cause DNA
damage, resulting in large-scale alterations in chromosomal
loci harboring tumor-suppressor genes such as NF2
and BAP1 [6]. Hence, mesothelioma is the prototypical
illustration of the genotoxic effects of protracted tissue
inammation, culminating in carcinogenesis with a long
latency period after initial asbestos exposure.
There are 3 major histological subtypes of MPM [7]:
epithelioid mesothelioma is the most common one and has
the best prognosis, and sarcomatoid mesothelioma showing
the worst. Biphasic mesothelioma has both epithelioid and
sarcomatoid subtypes combined in various proportions.

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The prognosis of MPM is poor due to its non-
specic clinical manifestations, responsible for a diagnosis
in an advanced stage. Currently, diagnostic procedures
for MPM involve imaging tests and a biopsy. However,
there is an unmet need of sensitive and non-invasive
screening tools that allow an early detection of the disease,
considered a precondition for the improvement of the
presently low 5 year survival rate of less than 5% [8].
Therefore, biomarkers can be explored and can be
useful within three aspects of the clinical management
of MPM: early diagnosis (diagnostic biomarkers),
prognosis (prognostic biomarkers) and prediction of
treatment outcome (predictive biomarkers) [9]. This
review will focus on diagnostic biomarkers. The required
characteristics of this type of biomarkers depend on
whether they will be used for diagnosis or screening. In
case of using the biomarker for diagnosis, the specicity
and positive predictive value (PPV) should be high enough
in order to conrm the disease in a true positive population.
In a screening setting however, the sensitivity and negative
predictive value (NPV) of the biomarker are important for
ruling out the disease in a true negative population.
This review will highlight the ndings of current
research efforts concerning the use of several biomarkers
for early diagnosis of MPM, and focus on the potential of
breath analysis within this scope.
Diagnostic biomarkers in mesothelioma: An
overview of current research
Methods
We searched for relevant studies concerning
biomarkers in mesothelioma through MEDLINE (PubMed
Database) and Web of Science using the following
keywords and their combinations: “mesothelioma”,
“biomarker”, “diagnosis”, “tumor marker”, “mesothelin”,
“bulin-3”, “osteopontin”, “megakaryocyte potentiating
factor”, “galectin-3”, “thioredoxin” and “HMGB-1”,
“RNA”, “lung cancer”, “volatile organic compounds”,
“electronic nose”, “ion mobility spectrometry”, “GC-MS”,
“headspace”, “cell line”, “asbestos”, “exhaled breath”,
“breath analysis” and “metabolomics”.
Table 1 summarizes the results from 14 articles
describing different biomarkers found in blood and/or
pleural effusions. In this table, we only included the data
involving the differentiation between individuals who
have been diagnosed with MPM and the at-risk group
of people exposed to asbestos: healthy asbestos-exposed
individuals and/or patients with benign asbestos-related
pleura-pulmonary conditions e.g. asbestosis, pleural
plaques and brosis.
Protein biomarkers in blood and/or pleural effusions
One of the most extensively evaluated serum
biomarkers is soluble mesothelin-related peptide (SMRP), also
known as soluble mesothelin. SMRP is a protein derived from
the MSLN gene, that is initially translated into a precursor
protein of ~69 kDa. This protein is processed by proteolytic
reactions, resulting in a cell-surface bound polypeptide of
~40 kDa named mesothelin, and a soluble polypeptide of
~30 kDa named megakaryocyte potentiating factor (MPF).
Mesothelin and SMRP have an identical NH2-terminus, but
a unique COOH-terminus [10]. Mesothelin is expressed on
the mesothelium of the pleural, pericardial and peritoneal
membrane and plays an important role in cell adhesion and
both cell-to-cell recognition and signaling by interaction with
Cancer Antigen (CA) 125 [11]. MPF in itself has oncogenic
potential by its ability to suppress cell death [12].
Both the diagnostic and prognostic value of SMRP
as a potential stand-alone marker have been extensively
studied, with reports showing that MPM patients have
signicantly higher levels of SMRP, which makes this
biomarker interesting as a diagnostic tool [13–25].
Asbestos-exposed individuals seem to have higher SMRP
concentrations than individuals who haven’t been exposed
to asbestos, regardless of the presence of pleural disease.
Therefore, serum SMRP levels can also be a marker of
asbestos exposure [26]. SMRP levels have been studied in
both serum (S-SMRP) and pleural effusions (PE-SMRP)
[27]. PE-SMRP has a better diagnostic performance
in differentiating MPM from other malignancies and
asbestos-related benign diseases. Despite of its high
specicity, S-SMRP shows a lack of sensitivity. Therefore,
further research has focused on the combination of serum
mesothelin with several other biomarkers in panels in
order to improve their respective diagnostic accuracy. An
interesting combination is that of SMRP with CA125.
However, combining these biomarkers did not improve
sensitivity for detecting MPM over SMRP alone [28].
CA125 is a large transmembrane mucin protein found on
the cell surface of mesothelial cells, and is routinely used
as tumor marker in ovarian carcinoma. Evidence shows that
CA125 is involved in cell-mediated immune response [11].
A correlation has been shown between the serum
mesothelin levels and the histological subtype of the
tumor. More specically, patients with epithelioid
mesothelioma show higher levels of serum mesothelin
than those with sarcomatoid mesothelioma. The same
correlation has been observed for MPF [29].
Osteopontin (OPN) and MPF are also biomarkers that
show increased levels in patients with established MPM.
The diagnostic performance of these markers was evaluated
in multiple studies [13, 30–33], but both glycoproteins lack
sensitivity as stand-alone biomarkers. OPN is a secreted
glycoprotein that facilitates recovery of the organism after
injury or infection. It regulates cell migration and stimulates
cellular signaling pathways via diverse receptors that can be
found on most cell types. OPN also plays an important role
in modulating immune and inammatory responses [34].
It appears that OPN can be useful in the differentiation
between asbestos-exposed persons who do not have cancer
and mesothelioma patients who have been exposed to

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asbestos [35]. One study has shown that combining SMRP
and OPN improves the diagnostic accuracy over SMRP
alone [33]. However, another comparative study did not
conrm this result [31]. The same has been observed for
the combination of SMRP and MPF [31].
The diagnostic accuracy of SMRP and MPF have
been examined and compared with each other in both
serum and pleural effusions [36]. Both biomarkers
seem to have an equivalent diagnostic accuracy in these
biological samples.
Table 1: A summary of the results for diagnostic studies on different biomarkers in blood and/or
pleural effusions
Studied groups Studied
marker(s)
Number of
patients ROC-AUC Threshold SE SP Ref.
MPM vs. healthy AE
SMRP (S) 88 vs. 61 0.806 0.8–1.9 nM 75%–43.2% 68.9%–100% [15]
OPN (S) 96 vs. 112 0.724 NA NA NA [23]
SMPR (S) 96 vs. 112 0.866 NA NA NA [23]
MPM vs. diseased AE
SMRP (S) 74 vs. 28 0.872 0.93nM 80% 82.6% [19]
SMRP (PE) 74 vs. 28 0.831 10.4 nM 76.7% 76.2% [19]
OPN (P) 96 vs. 33 0.677 NA NA NA [23]
SMRP (S) 96 vs. 33 0.834 NA NA NA [23]
SMRP (S) 129 vs. 75 NA 1.6 nM 42% 95% [25]
SMRP (S) 129 vs. 75 NA 1.35 nM 53% 88% [25]
MPM vs. AE (healthy +
diseased)
SMRP (S) 117 vs. 86 0.790 1.4–2.5 nM 67%–49% 80%–98% [28]
CA125 (S) 117 vs. 86 0.687 6–25 U/ml 52%–9% 80%–98% [28]
SMRP+CA125 117 vs. 86 0.801 NA 68%–42% 80%–98% [28]
SMRP (S) 85 vs. 212 0.859 2 nM 62% 95% [30]
MPF (S) 85 vs. 212 0.847 12.38 ng/ml 68% 95% [30]
TRX (S) 57 vs. 34 0.8178 60 ng/ml 71.9% 85% [40]
Fibulin-3 (PL) 92 vs. 132 0.99 52.8 ng/ml 71.32%–100% 100%–69.57% [41]
SMRP (S) 90 vs. 66 0.810 1.9 nM 60% 89.2% [17]
SMRP (S) 31 vs. 204 0.762 0.555–1.56 nM 45.2%–95% 95%–36.8% [33]
OPN (PL) 31 vs. 204 0.795 334.5–1423.9
ng/ml 29.5%–95% 95%–31.4% [33]
SMRP + OPN 31 vs. 204 0.873 NA NA NA [33]
SMRP (S) 24 vs. 172 0.725 16.06 nM 64.5%–95% 95%–37.7% [32]
OPN (PL) 32 vs. 207 0.780 878.65 ng/ml 62.5% 87.3% [32]
Total HMGB1 (S) 22 vs. 20 0.830 15.75 ng/ml 68.8% 84.5% [42]
HA HMGB1 (S) 22 vs. 20 1 2 ng/ml 100%–72.73% 5%–100% [42]
Fibulin-3 (PL) 22 vs. 20 0.959 NA NA NA [42]
SMRP (PL) 22 vs. 20 0.934 NA NA NA [42]
OPN (PL) 22 vs. 20 0.961 NA NA NA [42]
OPN (S) 76 vs. 69 0.888 48.3 ng/ml 77.6% 85.5% [35]
SMRP (S) 24 vs. 92 0.817 1.5 nM 67% 92.5% [20]
SMRP (S) 42 vs. 48 0.86 0.62 nM 97.6% 68.9% [44]
TRX (S) 42 vs. 48 0.72 156.67 ng/ml 92.9% 77.6% [44]
EGFR (S) 42 vs. 48 NA+ 19.96 ng/ml 90.5% 64.4% [44]
Fibulin-3 (S) 42 vs. 48 NA 51.41 ng/ml 88.1% 66.7% [44]
SDC-1 (S) 42 vs. 48 NA 3.77 ng/ml 90.0% 61.9% [44]
AE vs. healthy non-AE
Fibulin-3 (PL) 136 vs. 43 0.64 21.1 ng/ml 11%–100% 100%–9.30% [41]
Total HMGB1(S) 22 vs. 20 0.964 3.05 ng/ml NA NA [42]
HA HMGB1 (S) 22 vs. 20 0.574 0.45 ng/ml NA NA [42]
“Early-stage” MPM vs.
AE (healthy + diseased)
SMRP (S) 12 vs. 66 0.741 2 nM 58% 91% [17]
OPN (S) 13 vs. 69 0.906 62.4 ng/ml 84.6% 88.4% [35]
SMRP (PE) 74 vs. 63 0.809 11.4–20.8 nM 76.7%–65.1% 69.4%–83.7% [19]
ROC= Receiver Operating Characteristics curve, AUC = Area under the curve, SE = sensitivity, SP = specicity, MPM = malignant pleural mesothelioma, AE = asbestos-exposed,
NA = not available, diseased AE = people with benign asbestos-related conditions (e.g. pleural plaques, asbestosis or pleural effusions), S = serum, PL = plasma, PE = pleural
effusions.

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Other interesting biomarkers that have been
investigated, are C-C chemokine ligand 2 (CCL2)
and galectin-3 (LGALS3), both measured in patients
with pleural effusions[37, 38]. This restricts their use
to a group of patients with an already higher a priori
likelihood of mesothelioma than asymptomatic asbestos-
exposed individuals. CCL2 is a chemokine involved in
the recruitment of mononuclear phagocytes into inamed
and/or neoplastic tissues. LGALS3 is a lectin protein
that is abundantly secreted by tumor cells and tumor-
associated macrophages. It chemo-attracts macrophages,
suppresses T-cell function, and directly supports tumor
cell invasion [39]. CCL2 levels follow the same trend
as the aforementioned biomarkers and are increased in
MPM patients, but unexpectedly, circulating galectin-3
concentrations are decreased in the case of MPM [38].
The diagnostic accuracy of a panel consisting of SMRP,
CCL2 and LGALS3 was investigated, and compared with
that of SMRP alone [37], with the biomarker combination
resulting in a better diagnostic performance. Secretory
leukocyte peptidase inhibitor (SLPI), which has versatile
tissue-protective functions, has been studied as a potential
biomarker in MPM as well, but results showed that
this protein does not outperform the abovementioned
biomarkers [37].
Cellular pathways involved in redox processes would
be expected to produce potential biomarkers in MPM as
well. Accordingly, a study showed that thioredoxin-1
(TRX-1), a protein with anti-oxidative activity, is elevated
in MPM patients in comparison with asbestos-exposed
individuals that did not develop MPM [40].
Fibulin-3 is a member of the extracellular
glycoprotein bulin family and plays an important role
in skeletal development [41–43]. Plasma bulin-3 is able
to distinguish MPM patients from controls [41]. SMRP,
Fibulin-3 and TRX-1 have also been investigated in a
study that also studied the potential of syndecan-1 (SDC-
1) and epidermal growth factor receptor (EGFR) [44].
This study showed that SMRP and TRX-1 are the most
valuable serum biomarkers for early detection of MPM.
SDC-1 is a transmembrane heparan sulphate proteoglycan,
which functions as an extracellular matrix receptor and is
involved with modulation of neovascularization. EGFR is
a member of the receptor tyrosine kinase family that plays
an important role in tumorigenesis [44].
HMGB-1, also known as high-mobility group box
1 protein, is found in the nucleus of healthy mesothelial
cells, but once these cells are exposed to asbestos, HMGB-
1 is translocated to the cytoplasm and into the extracellular
space. The release of HMGB-1 induces the secretion of
TNF-α by macrophages, resulting in the protection of the
asbestos-exposed mesothelial cells against asbestos-related
cell death and in chronic inammatory response [45]. Total
serum HMGB-1 levels have been shown to differentiate
asbestos-exposed individuals from non-exposed healthy
subjects [42]. A specic HMGB-1 isoform, namely
hyper-acetylated HMGB-1, even outperforms previously
described biomarkers. Hyperacetylation of HMGB-1
translocates this damage-associated molecular pattern
to the cytosolic and subsequent extracellular space,
promoting inammation. This marker was able to
discriminate between MPM patients and asbestos-exposed
individuals without MPM or non-exposed individuals with
100% sensitivity and specicity. Combining bulin-3 with
either total or hyper-acetylated HMGB-1 improved both
sensitivity and specicity for differentiating MPM patients
from individuals with non-MPM pleural effusions.
Nevertheless, there are some limitations that have to be
considered with regard to HMGB-1. The sample size in
this study was small and the different patient groups were
not matched for factors such as age, sex and smoking
status, which could lead to confounding effects. In order
to use this interesting biomarker in a clinical setting, these
results require validation in an independent cohort.
In conclusion, there is a plethora of blood and
pleural uid biomarkers that can potentially be used
for early-stage diagnosis of MPM, mostly measured by
ELISA-based immuno-enzymatic assays. Nevertheless,
most of these components lack sufcient sensitivity and/
or specicity in distinguishing MPM patients from healthy
asbestos-exposed individuals and persons with asbestos-
related benign diseases. In order to clear the way for
clinical implementation, certain pitfalls should be taken
into account. The study population has to be chosen very
carefully as there are confounding variables that inuence
biomarker levels [46]. For instance, our group described
the association of levels of SMRP and MPF with age,
glomerular ltration rate (GFR), disease stage and body
mass index (BMI) [14].
Circulating non-coding RNAs
Non-coding RNAs (ncRNAs) are nucleic acids
that lack protein-coding potential and contain two major
classes: microRNAs (miRNAs) and long non-coding
RNAs (lncRNAs).
MiRNA’s are small ncRNAs of 17 to 22 nucleotides
long, regulating protein translation through several well-
characterized mechanisms [47]. MiRNA signatures in
tissue and blood have been extensively investigated as
diagnostic and prognostic biomarkers in different types of
cancers.
Evidence has shown that miRNAs are dysregulated
in malignant pleural mesothelioma and that specic
miRNAs seem to play a key role in MPM development
and progression. Therefore, these miRNAs could be useful
as MPM markers [48]. Benjamin et al. identied miRNA
biomarkers that allow differential diagnosis of MPM
[49]. They developed a diagnostic assay that is based on
miRNA expression in tissue. This assay is based on hsa-
miR-200c and hsa-miR-192 that both show overexpression
in lung adenocarcinoma and carcinomas that frequently

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metastasize to the pleura and on hsa-miR-193-3p that is
overexpressed in MPM.
Ak et al. found that certain microRNAs in tissue
are signicantly upregulated in MPM compared to benign
asbestos-related pleural effusions [50]. More specically,
the following microRNAs allowed differentiation between
malignant and benign disease: hsa-miR-484, hsa-miR-320,
hsa-let-7a and hsa-miR-125a-5p.
As miRNAs are in large part packaged within
circulating exosomes, they are protected from degradation
by circulating enzymes and can be robustly proled in
blood samples. Bononi et al. recently showed that several
circulating miRNAs in serum, namely miR-197-3p, miR-
1281 and miR-32-3p are potential new MPM biomarkers
[51]. These miRNAs were upregulated in MPM patients
compared to healthy individuals. Intriguingly, upregulated
miR-1281 was not only found in MPM patients, but also
in non-MPM subjects who had been exposed to asbestos
in the past. Based on these ndings, further work is
necessary to establish the value of circulating miRNAs as
reproducible MPM biomarkers.
LncRNAs are non-protein coding RNAs of more
than 200 nucleotides long. They play an important role
in regulating transcription and there is rising evidence
that their aberrant expression plays a role in cancer
biology [52], while being very specic for the tissue of
origin. Long non-coding RNAs are reported to serve as
biomarkers in MPM [53]. Wright et al. demonstrated that
lncRNA expression tissue proles allow differentiation
between malignant mesothelium and benign pleura [53].
LncRNAs can also be reliably detected in plasma samples,
offering the possibility to explore these molecules as
biomarkers for MPM.
Breath analysis: An alternative for blood
biomarkers
The search for new and non-invasive biomarkers is
currently shifting towards the eld of breathomics [54].
Analysis of the exhaled breath of an at-risk population can
provide valuable information on the metabolic status of
the patient. Breath contains volatile organic compounds
(VOCs) arising from endogenous biochemical pathways
or from inhaled/absorbed exogenous sources. The
concentration of these VOCs usually ranges from the low
part per billion (ppb) to the part per trillion (ppt) level.
Changes in the VOC-prole reect changes in processes
related to metabolism (host and microbiome-derived),
inammation or tumoral development [54]. Therefore, a
selection of VOCs can potentially be used as a diagnostic
biomarker to screen for certain diseases such as MPM
[55]. To date, researchers have mainly focused on lung
cancer within this research eld. Nevertheless, there
are also a number of studies which investigated the
potential of breath analysis as diagnostic tool for pleural
mesothelioma.
There are different technologies available that are
well suited for breath analysis [56]. The gold standard is
gas chromatography-mass spectrometry (GC-MS). This
technique allows both identication and quantication of
individual compounds with very high sensitivity, and is
usually combined with thermal desorption or solid-phase
micro extraction (SPME). The downside of this method is
its long time-to-result, relative cost and requirement for
expert operator staff.
Selected ion ow tube mass spectrometry (SIFT-
MS) and proton transfer reaction mass spectrometry
(PTR-MS) are both techniques which allow real-time and
on-line measurements of VOCs in breath [57, 58]. These
methods are both based on chemical ionization of the
trace compounds by well-dened reagent ions, resulting
in product ions that can be detected and quantied, based
on their mass-to-charge ratio (m/z). The sensitivity of
SIFT-MS is higher than for PTR-MS, but GC-MS still has
the highest sensitivity. Furthermore, PTR-MS and SIFT-
MS generate large fragmentation of the compounds in the
entire sample at once, limiting their use for unsupervised
biomarker detection. Another analytical technique that can
be used for breath analysis, is ion mobility spectrometry
(IMS). This involves the movement of gas-phase ions that
are exposed to an electric eld in a drift tube, where they
counteract with a drift gas (nitrogen or synthetic air). The
product ions gain a constant velocity through the inuence
of an electrical eld and by collision with the drift gas
molecules [59]. This velocity depends on the size, mass
and shape of the concerning product ions. The advantages
of this technique are speed and user-friendliness, allowing
low-cost, online sampling.
Recently, sensor technologies based upon pattern
recognition like electronic noses (e-noses) have been
developed allowing a fast and non-invasive analysis
of exhaled breath. These devices are inspired by the
mammalian olfactory system and are also known as
biomimetic cross-reactive sensor arrays [60]. In contrast
to the abovementioned techniques, an e-nose does
not allow the identication of individual VOCs as the
sensors only recognize a bulk of VOCs giving a breath
signature as output. In principle, a standard e-nose has a
lower sensitivity and limit of detection compared to other
mentioned techniques, which is not an issue as such as
long as the technology allows accurate discrimination
between certain groups. If, using different methods,
cancer-specic VOCs can be dened, then an array of
e-nose sensors can be designed that specically recognizes
these cancer-related compounds. With this strategy, the
specicity of an e-nose will be higher than that of the
standard, more complex technologies.
Dragonieri et al. investigated whether an e-nose
would allow to distinguish MPM patients from asbestos-
exposed individuals without MPM and from healthy
controls [61]. They included 13 subjects in each group.
Their attempt to separate the breathprints of patients with

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MPM from those of individuals with similar professional
asbestos exposure showed promising results. They were
also able to differentiate between the MPM patients and
healthy controls based on their breathprint.
The diagnostic potential of these breathprints
has been conrmed by Chapman et al., who correctly
identied patients with MPM, patients with benign
asbestos-related diseases and healthy individuals in 88% of
cases [62]. De Gennaro et al., developed a method based
on GC-MS in order to determine discriminatory VOCs
among patients with MPM, individuals with long-term
occupational exposure to asbestos and healthy controls
without asbestos exposure [63]. They demonstrated that
cyclohexane and cyclopentane are the dominant VOCs for
discriminating between the abovementioned groups.
The potential of IMS for diagnostic purposes was
investigated by Cakir et al. Discrimination between
healthy controls and patients with asbestos-related
diseases was possible based on a combination of two
VOCs in the IMS chromatogram representing α-pinene
and 4-ethyltoluol [64]. Recently, our group published
the results of the detection of MPM in exhaled breath by
IMS [65]. In contrast to Cakir et al., we included MPM
patients and were able to discriminate these patients from
both healthy non-asbestos exposed individuals as well as
asymptomatic asbestos-exposed subjects with a sensitivity
and specicity of respectively 87% and 70%.
Despite these promising results, conclusions from
these studies cannot be generalized due to the rather limited
number of individuals included in each cohort. None of
these studies have externally validated their ndings, which
is a necessary step towards clinical implementation. In
addition, further renements in the reported VOC signatures
could lead to substantial increases in diagnostic accuracy.
One way to achieve this goal is to investigate which VOCs
are originating from the cancer cells themselves rather
than from the inamed stromal environment (the latter
being shared between mesothelioma patients and asbestos-
exposed individuals without evidence of tumor).
Searching for mesothelioma cancer cell-specic
VOCs
A way to directly home-in on cancer cell-specic
VOCs, is to analyze the so-called “headspace” air of in
vitro cell cultures containing only cancer cells of interest.
Different experimental set-ups have been investigated to
that end, with most published research focusing on lung
cancer. Different methods have been used to analyze the
VOCs in the headspace of different cancer cell lines, lung
cancer tissue and pleural effusions. The VOCs that have
been detected, are very divergent among different reports.
To date, the only study that included a MPM cell
line, was performed by Gendron et al. They were able to
differentiate between different cancer cell lines consisting
of adenocarcinoma, squamous cell carcinoma, and
mesothelioma using an electronic nose [66]. Distinguishing
between the studied cancer cell lines, including a MPM cell
line, and normal cells was possible based on the difference
in composition of the headspace air over the cells. The
degree of discrimination between the different samples
was indicated by the Mahalanobis distances (MD). In most
cases, the MD between the tumor cell lines and the normal
controls was greater than 3 which is the threshold indicating
that the e-nose signatures are signicantly discriminative.
In some cases, the MD was even higher than 5, meaning
that the e-nose not just distinguishes the tumor cell lines
from other cell types, but also would allow identication
of these cell lines. A caveat is that the e-nose platform used
in these studies is subjected to drift between sampling sets
which jeopardizes reproducibility.
Supplementary Table 1 gives an comparative
overview of compounds that were found via both breath
analysis (subjects) and headspace analysis (in vitro cell
cultures). While the only data available relates to lung
cancer, it clearly shows that there is some degree of
overlap between in vitro and in vivo detected compounds.
Precisely these “shared” VOCs could serve as superior
biomarkers for early detection of malignancy. As can be
seen in Supplementary Table 1, in headspace of cancerous
cell lines it is mainly the concentration of certain aldehydes
(acetaldehyde), ketones (2-butanone, cyclohexanon)
and alkanes that is signicantly decreased or increased
compared to the headspace of non-cancerous cell lines or
medium only. Conicting ndings have been reported for
a few compounds mentioned in Supplementary Table 1.
For hexanal, one study involving breath analysis showed
an increased concentration for lung cancer, while the
in vitro results from another study showed a decrease in
concentration. As for acetone and 2-butanone, most studies
are concordant (i.e. increased concentration in cancer cell
lines), but for each of these compounds there is also one
study with opposite results.
We plan to perform a similar approach for pleural
mesothelioma, i.e. comparing the results from breath
analysis with in vitro studies on different MPM cell
lines in order to see which VOCs are related to aspecic
inammation and which VOCs originate from the
cancerous cells themselves.
Drawbacks involving breath-based biomarkers
As mentioned, VOCs in breath originate from both
exogenous and endogenous sources. Nevertheless, only
endogenous VOCs can be considered as biomarkers.
The fact that VOCs originate from oxidative stress and
upregulated metabolism, it could be that it is hard to
discriminate between different cancer types. The big
challenge in breath testing is to get a better understanding
of the biochemical pathways in which cancer-related
endogenous VOCs are generated in order to know their
origin. Presently, with an exception of acetone and

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isoprene, little is known about the metabolic processes
underlying production of VOC-biomarkers. This shows
the importance of in vitro experiments, which can provide
us with better insights on this matter. When in vitro
experiments are performed, the cell culture conditions
inuence the cell culture metabolomics. It will be
important for future experiments to closely mimic the
physiological conditions in the body instead of working
under standard culture conditions. Several studies also
showed that the VOC prole can differ among different
cell lines of the same cancer [67–70].
Furthermore, studies have shown that the VOC prole
in breath shows variability between and within individuals
[71, 72]. Although studies are contradictive, it seems that
the important factors inuencing the breath prole are
smoking behavior, body mass index (BMI), gender, age
and medication use. Hence it is worthwile to take these into
account when studies involving breath testing are performed.
However, this is much challenging when it comes to
correcting for the contribution of the gut microbiome to the
individual VOC spectrum. An additional layer of complexity
is generated by the host immune status. Although most
available data in that subject pertains to inammatory/innate
immune responses, less is known about the VOCs generated
from components of the adaptive immune system. There is
one report using in vitro experiments revealing that human
B-cells also generate a distinct VOC prole [73]. Either way,
it is very likely that the immune system may contribute to
the VOC prole in breath when the patient is suffering from
cancer, infection or other diseases.
Finally, there are also differences in the applied
techniques for breath analysis, with their own specic
advantages and drawbacks. Furthermore, there is a lack
of standardization in analytical technology which makes
interpretation of results between different studies difcult.
Conclusions and future perspectives
The increasing incidence of malignant pleural
mesothelioma is not only a problem of the present, but
is also a challenge for years to come. Asbestos, the main
etiological agent of MPM, is still being processed in
developing regions and therefore, its incidence will continue
to rise. The early detection of malignancy, including MPM,
seems very important in order to improve survival rates.
Because current screening tools for MPM generally detect
the disease in an advanced stage, there is an ongoing search
for new biomarkers that allow the early detection of MPM.
As described in this review, many efforts have already
been done within this scope, but the search continues as
there is still no validated ‘gold standard’. Ideally, potential
biomarkers should be non-invasive, robust and easy-to-use.
Test-related costs should be minimal and time to analytical
result should be sufciently short.
We aim to develop breath analysis as a point-of care
biomarker test that meets these requirements. Breathomics
is an increasingly investigated research eld showing
promising results for early stage diagnosis of MPM.
Rigorous studies on large patient cohorts and appropriate
controls will determine the clinical validity and utility of
breathomics in the diagnosis of mesothelioma. Studies
addressing the accuracy in mesothelioma patients versus
healthy controls are redundant, as are studies restricted to
pleural effusions, as the latter are obtained in patients who
have already a high likelihood of MPM.
President Obama introduced the “National Cancer
Moonshot” initiative which should accelerate research efforts
on prevention, (early) diagnosis and treatment of cancer.
Our search for the ‘ideal’ biomarker in malignant pleural
mesothelioma ts within the scope of this initiative. Cancer is
a disease that affects people in every layer of society and we,
scientists, have the obligation to use our knowledge on human
health in exploring new ways to improve cancer management.
Therefore, future studies should focus on the at-risk population,
consisting of people being professionally exposed to asbestos
with a latency time of at least 20 years after exposure.
Box 1: General aspects on biomarker
development
In general, a biomarker gives an indication of the
biological state of an organism. More specically, a
diagnostic biomarker should indicate whether a disease
is present [74]. In the development of a (diagnostic)
biomarker, methodological validation is an important step
towards clinical implementation [75, 76]. The aims are
to assess the test’s reproducibility, repeatability, accuracy
and sensitivity/specicity. In the rst part of biomarker
development, an internal validation is performed. This
involves the inclusion of a test set in order to build
up a diagnostic model, and subsequent validation of
the ndings using a validation set. In the next phase,
an external validation should be performed, using a
separate, prospectively recruited set of test subjects. This
essential step yields a better picture of the robustness of
the proposed model [77, 78]. Although these validation
steps can establish the analytical and clinical validity of
the test, it is still essential to ascertain clinical utility:
does early detection of disease effectively correlate with
better outcome? Can a negative test spare subjects from
unnecessary and potentially harmful invasive diagnostic
procedures?
CONFLICTS OF INTEREST
None.
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