Number of mutations in each gene in the two studies.
Malignant pleural mesothelioma (MPM) is a highly aggressive tumor that arises from the mesothelial cells lining the pleural cavity. Asbestos is considered the major factor in the pathogenesis of this malignancy, with more than 80% of patients with a history of asbestos exposure. MPM is characterized by a long latency period, typically 20–40 years from the time of asbestos exposure to diagnosis, suggesting that multiple somatic genetic alterations are required for the tumorigenic conversion of a mesothelial cell. In the last few years, advancements in next-generation sequencing and “–omics” technologies have revolutionized the field of genomics and medical diagnosis. The focus of this chapter is to summarize recent studies which explore the molecular mechanisms underlying this disease and identify potential therapeutic targets in MPM.
- pleural mesothelioma
- next-generation sequencing
- exome sequencing
- tumor suppressor gene
Malignant pleural mesothelioma (MPM) is a lethal cancer of the mesothelial cells lining the pleural cavity and, less frequently, the pericardium, peritoneum, and tunica vaginalis . Many years after the peak of asbestos use in United States, 3200 cases of MPM continue to be diagnosed annually, indicating that the U.S. population remains at risk of exposure to asbestos and development of mesothelioma . There are two major histological variants: epithelioid, which accounts for about 60% of cases and has the more favorable prognosis, and sarcomatoid, whose incidence is 10%. The remaining cases demonstrate histologic characteristics of both types and are classified as biphasic . The prognosis for patients with MPM is poor, with a median survival of 5–15 months . However, some patients with early MPM who undergo multimodality therapy including surgical resection and chemotherapy demonstrate longer-term survival of up to 25% at 5 years .
Many studies have shown a causal relationship between exposure to asbestos and mesothelioma (reviewed by Bianche et al. ). Although it has been suggested that brief asbestos exposure is sufficient to induce disease, MPM is the consequence of prolonged exposure in most cases. However, only a small percentage of individuals exposed to asbestos develop MPM, suggesting that genetic predisposition may modulate the effect of exposure to asbestos. In addition, 20% of MPM cases with unknown asbestos exposure have been related to other risk factors such as radiation therapy and thorotrast .
Studies conducted on large numbers of patients indicate that the time between asbestos exposure and diagnosis of MPM is generally more than 20 years. The molecular mechanisms for the transformation of mesothelial cells are unknown; it has been suggested that asbestos induces multiple chromosomal aberrations, particularly deletions, facilitating oncogenesis .
Investigations prior to the advent of next-generation sequencing (NGS) revealed the complexity of the genetic alterations observed in MPM tumors by using karyotypic and comparative genomic hybridization (CGH) analyses [8, 9]. Chromosomal losses were found to be more frequent than gains and particular chromosomal regions (1p22, 3p21, 4q, 6q, 9p21, 13q13–14, 15q11–15, and 22q12) were deleted at higher frequency in MPM tissues and cell lines [10, 11, 12]. Two tumor suppressor genes (TSGs) were identified by positional cloning approaches:
2. Exome sequencing studies
NGS technologies have allowed the sequencing of DNA and RNA at unprecedented speed, uncovering potential driver genes and creating novel biological applications . In the last decade, NGS has been used to detect driver genetic mutations in cancer and provide new insights into tumorigenesis.
Shotgun pyrosequencing was used to characterize RNA expression levels and mutations of four patients in the first effort to investigate MPM by NGS. Several different mutations were found in the four transcriptomes. In addition, RNA editing gene deletions and gene silencing were identified .
In 2010, the first whole genome sequence of one MPM tumor and matching normal tissue was conducted using a combination of sequencing-by-synthesis and pyrosequencing methodologies . This study showed that aneuploidy and chromosomal rearrangements were more numerous than point mutations in this tumor. One large deletion in the dipeptidyl peptidase like 10 (
In 2016, Bueno et al. conducted an extensive analysis of the mutational landscape of MPM. Ninety-nine MPM tumors were examined by whole exome sequencing, whereas additional 103 samples were characterized by targeted exome sequencing .
In 2018, The Cancer Genome Atlas (TCGA) program performed a comprehensive molecular profiling of 74 primary MPM samples including exome sequencing, copy-number arrays, mRNA sequencing, noncoding RNA profiling, DNA methylation, and reverse-phase protein arrays . The significantly mutated genes in this study were
The TCGA study performed a comparison of the significantly mutated genes between the Bueno and TCGA cohorts . This analysis identified five genes that were frequently mutated in both studies: BRCA1-associated protein-1 (
|Gene symbol||Gene ID||Chromosomal location||Number of mutations in Bueno’s cohort||Number of mutations in Hmeljak’s cohort||Total|
In 2009, a study suggested that
Located at 17p31.1,
Targeted deep sequencing has revealed somatic
Several investigations have linked
3. Transcriptome sequencing studies
Since gene expression is linked to tumor behavior, bulk expression profiling of tumors has revolutionized our understanding of cancer by giving insight into the expression levels of thousands of genes measured at once. In addition, the allocation of cancer specimens into molecular clusters having similar biological and clinical characteristics has improved the understanding of the molecular biology of tumors and identified both actionable targets for therapies as well as biomarkers for prediction of response .
In 2005, Gordon et al. profiled 40 MPM tumors using microarray technologies . Four normal pleura specimens and four normal lung tissues were included in the analysis as controls because MPM arises from mesothelial cells of the pleura and often involves the lung parenchyma . Unsupervised cluster analysis revealed four distinct subclasses with two, named C1 and C2, consisting only of MPM samples. These two clusters had epithelial (88%) and mixed (78%) subtypes, respectively, showing a partial correlation with tumor histology. Differential gene expression analysis demonstrated genes related to cytoskeletal/support, such as keratins, cadherins, and other proteoglycans, were over-expressed in cluster C1, whereas genes associated with extracellular matrix and structural proteins such as collagen, actin, biglycan, and fibronectin were highly expressed in subclass C2 .
In 2014, a study from de Reynies et al. generated a transcriptomic classification of MPM using 38 primary cultures . Consensus clustering of the expression profiles identified two groups of MPM, C1 and C2, which are partially related to histology. Epithelioid MPM were found in both clusters, whereas sarcomatoid tumors clustered only in C2. In addition, tumor samples in C1 tended to have more frequent mutations in
In 2016, a seminal publication on genomics in MPM described unsupervised consensus clustering of RNA sequencing data from 211 MPM tumors. This analysis classified the samples into four distinct molecular clusters: epithelioid, biphasic-epithelioid (biphasic-E), biphasic-sarcomatoid (biphasic-S), and sarcomatoid . The clusters were loosely associated with the spectrum from epithelioid to sarcomatoid histology. Epithelioid and biphasic samples were distributed in all four subgroups, whereas sarcomatoid tumors were only in one cluster. Biphasic samples clustered according to the proportion of epithelioid and sarcomatoid cells contained in the specimen; biphasic tumors with the highest portion of sarcomatoid cells grouped with the sarcomatoid samples. Notably, patients in the epithelioid cluster had longer overall survival compared to the survival of patients in the other three groups. Differential expression analysis of the sarcomatoid and epithelioid clusters revealed that genes related to the EMT process were differently expressed between the two groups, and that ratio of two genes
A different approach to classify MPM tumors was used by Hmeljak et al. . To determine whether a multi-platform molecular profiling may offer additional power to identify subsets of MPM, two clustering algorithms, iCluster  and PARADIGM  were used to integrate somatic copy-number alteration, gene expression, and epigenetic data from 74 MPM samples. Both algorithms grouped the samples into four distinct clusters with high concordance between the two methods in the assignment of the sample into the groups. Survival analyses showed significant differences in survival across the four groups. In addition, the four clusters were significantly associated with histology: cluster 1 contained many epithelioid samples, whereas cluster 4 was enriched for sarcomatoid tumors as found in previous studies [13, 71, 72]. This study, using a small number of samples, mostly epithelial, confirmed that genes related to the EMT process were differentially expressed between the two most extreme clusters .
In 2019, unsupervised clustering of microarray profiles assigned 63 primary MPMs into four groups (C1A, C1B, C2A, and C2B) . Then, a meta-analysis of mesothelioma expression profiles was conducted to compare these clusters with the groups from previous classifications [13, 15, 71, 72, 75, 76]. This analysis identified two highly correlated MPM clusters present in all expression profiles, which corresponded to the extreme epithelioid and the sarcomatoid phenotypes. The remaining groups did not associate closely suggesting that they may represent different points of a continuum or “histo-molecular gradient” of epithelioid and sarcomatoid components. A deconvolution approach was used to identify novel insights into the intra-tumor heterogeneity of MPM by dissecting whole tissue RNA-sequencing signatures into biologically relevant components. This analysis produced two molecular signatures of 150 genes, E-score and S-score, which were related to histology and recapitulated the molecular classification. These signatures reflected the proportion of epithelioid-like and sarcomatoid-like components within each MPM tumor. In addition, the proportions of these cellular components were significantly associated with prognosis .
Regardless of the metric used, the whole transcriptome studies indicate that MPM is characterized by a molecular gradient associated with the EMT process. Most recently, the relationship between the C/V score  and other published metrics [75, 77] associated with the EMT process has been investigated  demonstrating a significant correlation of the C/V score with other molecular signatures. These results indicate that the ratio of just two genes can be sufficient to determine the “EMT-component” in each MPM .
4. Clinical significance
While further work is needed before these data can be applied directly to patient care, an understanding of the molecular heterogeneity of MPM and the mutations that contribute to different subtypes can have a meaningful impact on the direction of clinical research in this field. In 2014,
Knowledge of key mutations in MPM has guided investigations into other forms of targeted therapy, although many are still at the preclinical stage. For example, LaFave and colleagues found evidence that loss of Bap1 expression increases Ezh2 expression in xenograft and
Beyond identifying therapeutic targets, multi-omic data have enhanced the understanding of tumor biology, providing novel ways to stratify patients, determining prognosis and predicting sensitivity to existing treatments (reviewed in ).
We have developed a gene expression ratio-based method to translate expression profiling data into clinical tests based on the expression levels of a small number of genes . This method uses standard supervised methods for microarray analysis to compare gene expression in two types of tissues differing by a single clinical parameter such as histology or outcome. Genes with the most significant difference in expression are selected and used in combination to calculate ratios of gene expression able to predict the clinical parameter associated with a random patient sample.
Using this method, a 6-gene 3-ratio test has been developed to distinguish MPM from adenocarcinoma using resection specimens and fine needle biopsies [81, 82]. A similar approach was used to generate a 4-gene 3-ratio prognostic test to identify patients likely to benefit from tumor resection in the preoperative setting [83, 84], as well as a 4-gene 3-ratio signature to distinguish the epithelioid from the sarcomatoid MPM subtype .
Despite rapidly decreasing sequencing costs , there remain several barriers to introducing the use of NGS technology in clinical practice, especially in MPM. In many solid tumors, the development of targeted sequencing panels has led to targeted therapies and prediction of survival of cancer patients. MPM is rare, making large-scale validation studies difficult to perform, and heterogeneous, characterized by mutations highly variable among tumors. In addition, loss of TSGs is a common feature of MPM making potential treatments associated with these genes difficult to be applied to real life treatment. Clinical trials focused on specific mutated genes [29, 37] have been infrequent and the results never translated to practice. Transcriptome analyses have classified MPM patients into several groups stratifying patients into categories of risk; however, a substantial margin of error in these predictions persists because the sensitivity and specificity of these tests are difficult to define . Precision medicine based on cancer genomics is still far from being applied in clinical practice in MPM. Nevertheless, we are confident in the value of NGS for personalized medicine and believe additional efforts are needed for the implementation of NGS in identifying patients who might benefit from targeted treatments.
NGS has revolutionized the study of human genetics by transforming our ability to analyze the causes of disease, develop new diagnostics, and identify potential therapeutic targets. NGS studies have led to the discovery of several commonly mutated genes in MPM [13, 15]. Although analyses of transcriptome data have contributed to the understanding of the molecular biology of MPM subtypes, these studies were based on bulk profiling where tumors were profiled as a single entity averaging the gene expression of all the cells in the specimen and ignoring the intra-tumor heterogeneity that regulates many critical aspects of tumor biology . The importance of intra-tumor heterogeneity in MPM is becoming evident. Future single-cell RNA sequencing work will be able to elucidate molecular roles of immune infiltrates and stroma in MPM as well as to clarify whether the molecular mechanisms associated with the genetic heterogeneity are due to subclonal mutations, epigenetic programs, or other environmental factors such as cell-cell interaction or nutrient availability.
This work was supported by grants to RB from the National Cancer Institute (NCI 2 R01 CA120528-11A1) and the International Mesothelioma Program at Brigham and Women’s Hospital. The study sponsors played no role in the study design, collection, analysis, interpretation of data, writing of the report, or decision to submit the chapter for publication.
Conflict of interest
The authors disclose no potential conflicts of interest. Dr. Bueno reports grants from Medgenome, grants from Roche, grants from Verastem, grants from Merck, grants from Gristone, grants from Epizyme, grants from Siemens, grants from NCI, grants from DoD, and grants from NIH. In addition, Dr. Bueno has a patent 7,622,260 licensed to BWH, a patent 8,450,057 licensed to BWH, a patent 8,551,700 licensed to BWH, and a patent 9,446,050 licensed to BWH, and Patents/Equity in Navigation Sciences.