Genomic Landscape of Pleural Mesothelioma and Therapeutic Aftermaths.

PURPOSE OF REVIEW: In this article, we provide a comprehensive analysis of recent progress in the genetic characterisation of pleural mesothelioma, and the translation of these findings to clinical practice. RECENT FINDINGS: Advancements in sequencing technology have allowed the identification of driver mutations and improved our understanding of how these mutations may shape the mesothelioma tumour microenvironment. However, the identification of frequently mutated regions including CDKN2A, BAP1 and NF2 have, to date, not yet yielded targeted therapy options that outperform standard chemo- and immunotherapies. Similarly, the association between mutational profile and the immune microenvironment or immunotherapy response is not well characterised. Further research into the link between tumour mutational profile and response to therapy is critical for identifying targetable vulnerabilities and stratifying patients for therapy.

New Markers for Management of Mesothelioma.

In this review, we provide an update on the status of cancer biomarkers for the clinical management of pleural mesothelioma, an aggressive cancer associated with asbestos exposure. Mesothelioma can be difficult to diagnose, and response to treatment is transient, even with recently adopted immune checkpoint inhibitor (ICI) combinations. Identification of mesothelioma-specific biomarkers could facilitate early diagnosis and tailor treatment strategies. Mesothelioma is characterized by frequent loss or alteration of the tumor suppressor genes cyclin-dependent kinase inhibitor 2A (CDKN2A) and BRCA1-associated protein-1 (BAP1). Accumulating data show these genes and/or their related protein products will be valuable tissue-based biomarkers for mesothelioma. Loss of BAP1, CDKN2A, p16, or methylthioadenosine phosphorylase provide pathologists with a reliable means of differentiating between mesothelioma and reactive mesothelial cell proliferations. This can aid diagnosis in difficult cases and is requisite for the identification of the new pathological entity malignant mesothelioma in situ. However, limited progress in identifying clinically useful soluble biomarkers in this cancer type has been made, with mesothelin remaining the benchmark. To date, results from studies to identify predictive biomarkers for ICI response have been disappointing. A recent retrospective study demonstrated BAP1 loss was predictive of improved survival following combination pemetrexed- and platinum-based chemotherapy. Validation of this result could have important clinical implications. Clinical trials aimed at targeting therapy based on biomarker expression are generally in the early phase setting, with overall results being moderate. The identification of biomarkers for mesothelioma remains a key research question due to their potential to improve patient outcomes in this deadly cancer.

A Community-Driven, Openly Accessible Molecular Pathway Integrating Knowledge on Malignant Pleural Mesothelioma.

Malignant pleural mesothelioma (MPM) is a highly aggressive malignancy mainly triggered by exposure to asbestos and characterized by complex biology. A significant body of knowledge has been generated over the decades by the research community which has improved our understanding of the disease toward prevention, diagnostic opportunities and new treatments. Omics technologies are opening for additional levels of information and hypotheses. Given the growing complexity and technological spread of biological knowledge in MPM, there is an increasing need for an integrating tool that may allow scientists to access the information and analyze data in a simple and interactive way. We envisioned that a platform to capture this widespread and fast-growing body of knowledge in a machine-readable and simple visual format together with tools for automated large-scale data analysis could be an important support for the work of the general scientist in MPM and for the community to share, critically discuss, distribute and eventually advance scientific results. Toward this goal, with the support of experts in the field and informed by existing literature, we have developed the first version of a molecular pathway model of MPM in the biological pathway database WikiPathways. This provides a visual and interactive overview of interactions and connections between the most central genes, proteins and molecular pathways known to be involved or altered in MPM. Currently, 455 unique genes and 247 interactions are included, derived after stringent manual curation of an initial 39 literature references. The pathway model provides a directly employable research tool with links to common databases and repositories for the exploration and the analysis of omics data. The resource is publicly available in the WikiPathways database (Wikipathways : WP5087) and continues to be under development and curation by the community, enabling the scientists in MPM to actively participate in the prioritization of shared biological knowledge.