A further, and very interesting, potential implication of mesothelioma biomarkers is the identification of therapy targets.
Candidate biomarkers can be molecules with different characteristics, such as proteins or their fragments, nucleic acids, lipids, and metabolites. As a result, methods for their identification vary greatly. Most protein studies have used enzyme-linked immunosorbent assays (ELISAs).
Proteomics-based approaches, such as those based on mass spectrometry, are promising tools and have been increasingly implemented to identify and quantify biomolecules in a variety of biological samples. They require three essential steps: protein extraction and separation, protein identification, and protein verification.
The evaluation of nucleic acids is more complex, as it requires the extraction, quantification, and purification of RNA, with the samples stored at very low temperatures (−80 °C). The purified RNA is then reverse-transcribed into cDNA, which, in turn, is amplified by a polymerase chain reaction (PCR).
The evaluation of nucleic acids and, even more so, proteomics has high costs and poses accessibility problems in low-income countries.
2. Pleural Fluid Biomarkers of PM
2.1. Mesothelin
Mesothelin is a protein that is normally present on the mesothelial cells of the pleura, peritoneum, and pericardium. It appears to play a role in cell adhesion, but is likely a nonessential component in normal cells. Mesothelin is overexpressed in some malignancies, such as PM, but also in pancreatic, ovarian, and lung adenocarcinomas
[23].
This fact has made it an attractive candidate as a biomarker for the diagnosis of PM, for screening people exposed to asbestos, for monitoring the progression of the disease, and as a potential target for cancer therapy
[24].
The full-length human mesothelin gene (Full-ERC/mesothelin) encodes a 71-kDa precursor protein, which is cleaved into two products, a 40-kDa C-terminal fragment (C-ERC/mesothelin) and a 31-kDa N-terminal fragment (N-ERC/mesothelin, also known as megakaryocyte potentiating factor, MPF). Both mesothelin and related peptides (SMRPs), including MPF, have been found in human serum and pleural effusion. As a result, assays have been developed to determine their pleural and blood levels (see also the next section on “Serum biomarkers of PM”)
[25].
Mesothelin was originally known as the CAK1 antigen. It was identified by the murine monoclonal antibody K1, and can now be identified by “second generation” anti-mesothelin antibodies such as the 5B2 clone.
A pioneering study of mesothelin using K1 found that, among 23 patients with PM, all 15 individuals with the epithelioid subtype had mesothelin expression; the 4 with the sarcomatous subtype were all negative; and in the 4 patients with biphasic PM, only the epithelial component stained for mesothelin. In the same study, none of 23 lung adenocarcinomas with different degrees of histologic differentiation demonstrated reactivity with the K1 antibody
[26].
Similar results were subsequently found using the antimesothelin antibody 5B2 in paraffin-embedded PM tissue samples
[27]. Out of the 55 mesothelioma specimens which were studied, mesothelin reactivity was observed in all 44 epithelioid PM and in the 3 epithelial components of biphasic PM. Conversely, none of the 8 sarcomatous mesotheliomas expressed mesothelin. Despite the limited case studies, the results provide further evidence that mesothelin is present in all epithelial mesotheliomas and is absent in the sarcomatous type. Consequently, a positive mesothelin immunostain suggests an epithelioid PM, although not absolutely specific, whereas a negative mesothelin immunostain strongly argues against the diagnosis of epithelioid PM
[28].
The meta-analyses by Gao et al.
[29] and Cui et al.
[30] evaluated the diagnostic accuracy of SRMPs on pleural fluid for the diagnosis of PM. They analyzed the SMRP concentrations in 13 and 11 studies, respectively, and all of them reported higher levels of mesothelin in PM patients compared to controls. As meta-analyses, the cutoff values in the included articles were quite different, ranging from a minimum of 8 nmol/L to a maximum of 24.1 nmol/L. Therefore, Gao et al. divided the studies into two groups, with 15 nmol/L as the boundary, but this did not significantly reduce the heterogeneity. In the two meta-analyses, the summary estimates of sensitivity were 0.68 and 0.79, the specificity values were 0.91 and 0.85, the positive likelihood ratios were 7.8 and 4.78, the negative likelihood ratios were 0.35 and 0.30, and the diagnostic odds ratios were 22 and 19.50, respectively. As expected, the specificity with a cut-off value of 20 ± 0.4 nmol/L was higher than with a cut-off value of 12 ± 0.6 nmol/L and 8 ± 0.6 nmol/L, and had a range of 83.7% to 97.1%. Altogether, the authors concluded that PM can be suspected when the SMRPs in pleural effusion are higher than 8 nmol/L, whereas values higher than 20 nmol/L, are strongly suggestive.
A more recent meta-analysis by Schillebeeckx et al.
[31] included 19 studies evaluating the diagnostic effectiveness of pleural effusion mesothelin. The cut-off values which were ranged from 6 nM (where sensitivity and specificity were, respectively, 72% and 46%) to 50 nM (with sensitivity and specificity of 44% and 100%). The most commonly used cut-off values fell around 20 nM, with sensitivities ranging from 44% to 100% and specificities from 46% to 100%, while the overall AUC
ROC was 0.83 (95% CI: 0.81–0.85).
2.2. Fibulin-3
Fibulin-3 is a glycoprotein encoded by the epidermal growth factor-containing fibulin-like extracellular matrix protein 1 gene. It plays a role in cell proliferation and migration
[32][33].
Fibulin-3 has low expression in normal tissues, but it is overexpressed in several cancers, including PM, and is also secreted in body fluids. It accumulates in the pleural effusions of PM patients and has been proposed to distinguish these patients from individuals who have non-malignant pleural inflammation. An AUC
ROC of 0.93 was found when pleural fibulin-3 values were evaluated to discriminate mesothelioma from both benign and malignant effusions, with cutoffs for maximum sensitivity and specificity between 378 ng per milliliter and 346 ng per milliliter
[34]. These results were not confirmed by other studies that found similar fibulin values in effusions from mesothelioma and other diseases
[35]. The overall AUC
ROC found in the meta-analysis by Schillebeeckx et al. was 0.68 (95% CI: 0.50–0.87)
[31].
A comparative analysis has suggested that fibulin-3 correlates less accurately than mesothelin with PM diagnosis, whether measured in plasma or pleural effusion; thus, mesothelin has been recognized as the best pleural marker that is usable for routine diagnostic purposes
[36][37].
Conversely, fibulin-3 has been proposed as a better prognostic factor of PM, since recent evidence suggests that fibulin-3 promotes the malignant behavior of mesothelial cells, whereas fibulin-3 knockdown decreases viability, clonogenic capacity, and invasion, as well as chemoresistance, in PM cells.
2.3. Hyaluronic Acid
Hyaluronan, or hyaluronic acid (HA), is a large polysaccharide that contributes to the progression of several types of cancer
[38]. It has been shown to be elevated in mesothelioma-associated pleural effusions
[39], although several studies have suggested that its increase is mostly due to the release of growth factors from tumor cells that may stimulate other cells to produce HA
[40]. HA is rapidly removed from circulation by the clearance receptor stabilin-2, and has a plasma half-life of 2.5–5 min.
A cutoff of 100,000 ng/mL showed a sensitivity of 44.0% and a specificity of 96.5% for differentiating effusions due to mesothelioma from those induced by other causes, with an AUC
ROC curve of 0.832
[39].
In the past, high technical expertise was required to measure hyaluronic acid by high-performance liquid chromatography, and this has limited the number of studies on this biomarker. More recent studies using more intuitive test systems have demonstrated that the mesothelin and hyaluronic acid levels in pleural effusion have similar levels of diagnostic accuracy, and that combining the two markers in a two-step model improves diagnostic accuracy
[41].
2.4. Cell-Free microRNAs
MicroRNAs are short, noncoding, single-stranded RNA molecules that regulate gene expression at the post-transcriptional level.
MicroRNAs affect the courses of many important processes of the human organism, including cell division, proliferation, differentiation, apoptosis, and the formation of blood vessels. Altered expression of microRNAs has been shown in several cancers, which suggests a potential oncogenic or suppressor role
[42].
Some studies have evaluated the serum levels of different microRNAs as markers of malignant mesothelioma, while only the study by Birnie et al. has analyzed them in pleural fluid
[43]. The authors analyzed microRNAs in the pleural effusion cells and supernatants from 26 patients with PM and 21 with pleural effusion due to non-PM conditions. They found that four microRNAs (miR-944, miR-139-5p, miR-210, and miR-320) found in pleural effusion were upregulated, and seven (miR-200b, miR-200c, miR-143, miR-200a, miR-203, miR-31, and miR-874) were downregulated. A combination of miR-143, miR-210, and miR-200c was able to differentiate PM from non-PM with an AUC
ROC of 0.92.
2.5. CYFRA-21-1 and CEA
CYFRA-21-1 is the soluble fragment of cytokeratin 19. It can be released into circulation after cell death, thus exhibiting a close relationship with tumor cell necrosis and apoptosis. CYFRA-21-1 is found in the blood of patients with different epithelial malignancies, including non-small-cell lung cancer (NSCLC), and has been used to predict diagnosis and prognosis
[44]. Although CYFRA-21-1 has not been extensively investigated in PM, all studies measuring it in pleural effusion found higher levels in PM patients compared to controls
[45][46][47]. However, the diagnostic accuracy was modest, with AUC
ROC values ranging from 0.65 to 0.76.
CEA is a glycoprotein involved in cell adhesion. In healthy individuals, very low levels of CEA are detectable in the bloodstream and body fluids, while its increase has been reported in several cancers and non-cancerous conditions. Two studies measuring CEA in pleural fluid reported its increase in PM
[45][48], while another study demonstrated that pleural CEA in PM was less elevated than in other cancer types, suggesting that CEA levels above 3 ng/mL in pleural fluid may exclude the diagnosis of PM
[47]. The overall AUC
ROC is 0.55; therefore, CEA is currently of poor diagnostic accuracy and is not recommended as a differential diagnostic biomarker for PM
[31].
2.6. Combined Markers Panels
In a study aiming to establish a predictive model using biomarkers from pleural effusions, samples from 190 consecutive patients were collected
[49]. The biomarkers significantly associated with PM were hyaluronan, N-ERC/mesothelin, C-ERC/mesothelin, and syndecan-1. A two-step model using hyaluronan and N-ERC/mesothelin yielded good discrimination, with an AUC
ROC of 0.99 (95%CI: 0.97–1.00) in the model generation dataset and 0.83 (0.74–0.91) in the validation dataset, respectively.
Recently, a novel affinity-enrichment mass spectrometry-based proteomics method was applied for the explorative analysis of pleural effusions from a prospective cohort of 84 individuals who underwent thoracoscopy due to suspected PM
[50]. The immunohistology of the pleural biopsies confirmed PM in 40 patients and ruled out PM in 44. The authors identified protein biomarkers with a high capability to discriminate PM from non-PM patients and applied a random forest algorithm for the purpose of building classification models. Depending on the specific protein combination, the proteomic analysis of pleural effusions identified panels of proteins with excellent diagnostic properties (90–100% sensitivities, 89–98% specificities, and AUC
ROC 0.97–0.99). Proteins associated with cancer diagnosis included galactin-3 binding protein, testican-2, haptoglobin, Beta ig-h3, and protein AMBP. Furthermore, the study confirmed the previously reported diagnostic accuracies of the PM markers fibulin-3 and mesothelin. Subsequent studies should validate these findings in separate cohorts of patients and investigate the possible impact of PM subtypes on biomarker selection, as well as the implementation of machine learning in the mass-spectrometry-based diagnosis of PM.
2.7. Cytology
The detection of neoplastic invasion has always been a key element in diagnosing PM with certainty, but diagnosis based solely on pleural effusion cytology is controversial, mainly due to poor sensitivity. When a large amount of pleural fluid is submitted for cytological evaluation, the pathologist can prepare cell-block sections for immunohistochemical investigation and obtain a high level of specificity
[51].
The best interpretative yield derives from the correlation of the cytological results with the imaging, which can provide information on the anatomical distribution of the lesion, evidence of the nodularity of the pleural disease, and, sometimes, tissue invasion.
Although “positive” and “negative” immunohistochemical markers have been shown to be remarkably effective in distinguishing between epithelioid mesothelioma and other secondary malignancies, no biomarker has 100% sensitivity or specificity for diagnosing mesothelioma.
The 2021 WHO classification of tumors of the pleura recommends specifying the specimen type in diffuse PM reports (e.g., extended pleurectomy/decortication; extrapleural pneumonectomy; and other smaller specimens, including small biopsy specimens and cytology). Regarding histology, PM can be determined directly by morphology through hematoxylin–eosin staining. Nonetheless, pathologists usually recommend confirmation through immunohistochemistry. Calretinin, Wilms tumor 1 (WT-1), cytokeratin 5 (CK5), podoplanin, mesothelin, and heart development protein with EGF-like domains 1 (HEG1) are immunohistochemical biomarkers of mesothelial differentiation, whereas carcinoembryonic antigen (CEA), B72.3, Ber-EP4, Lewisy blood group (BG8), MOC-31, CD15, mucin-4 (MUC4), and claudin-4 are markers suggestive of epithelial metastasis
[2].
The loss of BAP1 protein expression by immunohistochemistry has recently been suggested as a potential marker for identifying MM, as it has been observed in more than half of PM, either epithelioid, biphasic, or sarcomatoid
[52].
Recent advances in cytological analysis promise diagnostic advances for PM. Biancosino et al. The study cited in
[53] analyzed 5731 specimens of pleural effusions from 4552 patients, of which 444 were diagnosed as PM. Cytological evaluation achieved a sensitivity of 0.50 and specificity of 0.99 for PM diagnosis. The supplemental assessments of HA (above 30 mg/L) raised the sensitivity to 0.70 without affecting the specificity. The authors concluded that the cytological evaluation of pleural effusions aided by the assessment of HA has a diagnostic accuracy for PM that is no less than that of the standard histological evaluation, and may be considered in difficult or doubtful diagnostic cases.
Similarly, a large monocentric database was retrospectively explored in order to clarify the value of cytology in distinguishing malignant mesothelioma according to the International System for Reporting Serous Fluid Cytopathology (ISRSFC)
[54]. Cytological samples were available for analysis in 210 patients with malignant mesothelioma (164 pleural and 46 peritoneal effusions). All cases were reviewed and reclassified according to the proposed ISRSFC scheme. The final histological diagnosis consisted of epithelioid mesothelioma in 192 (91.4%) patients, and sarcomatoid type in the remaining 18 (8.6%). The cytological cases were reclassified as follows: 2 (0.9%) as non-diagnostic, 81 (38.6%) as negative for malignancy, 4 (1.9%) as atypia of undetermined significance, 11 (5.2%) as suspicious for malignancy, and 112 (53.4%) as malignant. Sarcomatoid cells in the malignant category appeared solitary, with moderate or marked nuclear pleomorphisms and irregular chromatin if compared with the epithelioid subtype. The authors concluded that morphological features, coupled with clinical–radiological data, may help clinicians to adequately manage the patients.