This
is the first report of the use of laser ablation–inductively
coupled plasma time-of-flight mass spectrometry (LA–ICP–TOFMS)
to analyze human malignant pleural mesothelioma (MPM) samples at the
cellular level. MPM is an aggressive, incurable cancer associated
with asbestos exposure, with a long latency and poor overall survival.
Following careful optimization of the laser fluence, the simultaneous
ablation of soft biological tissue and hard mineral fibers was possible,
allowing the spatial detection of elements such as Si, Mg, Ca, and
Fe, which are also present in the glass substrate. A low-dispersion
LA setup was employed, which provided the high spatial resolution
necessary to identify the asbestos fibers and fiber fragments in the
tissue and to characterize the metallome at the cellular level (a
pixel size of 2 μm), with a high speed (at 250 Hz). The multielement
LA–ICP–TOFMS imaging approach enabled (i) the detection
of asbestos fibers/mineral impurities within the MPM tissue samples
of patients, (ii) the visualization of the tissue structure with the
endogenous elemental pattern at high spatial resolution, and (iii)
obtaining insights into the metallome of MPM patients with different
pathologies in a single analysis run. Asbestos and other mineral fibers
were detected in the lung and pleura tissue of MPM patients, respectively,
based on their multielement pattern (Si, Mg, Ca, Fe, and Sr). Interestingly,
strontium was detected in asbestos fibers, suggesting a link between
this potential toxic element and MPM pathogenesis. Furthermore, monitoring
the metallome around the talc deposit regions (characterized by elevated
levels of Al, Mg, and Si) revealed significant tissue damage and inflammation
caused by talc pleurodesis. LA–ICP–TOFMS results correlated
to Perls’ Prussian blue and histological staining of the corresponding
serial sections. Ultimately, the ultra-high-speed and high-spatial-resolution
capabilities of this novel LA–ICP–TOFMS setup may become
an important clinical tool for simultaneous asbestos detection, metallome
monitoring, and biomarker identification.