Public Adverse Event Data Insights into the Safety of Pembrolizumab in Melanoma Patients

Advancing drug safety science by integrating molecular knowledge with post-marketing adverse event reports

Promising drug development efforts may frequently fail due to unintended adverse reactions. Several methods have been developed to analyze such data, aiming to improve pharmacovigilance and drug safety. In this work, we provide a brief review of key directions to quantitatively analyzing adverse events and explore the potential of augmenting these methods using additional molecular data descriptors. We argue that molecular expansion of adverse event data may provide a path to improving the insights gained through more traditional pharmacovigilance approaches. Examples include the ability to assess statistical relevance with respect to underlying biomolecular mechanisms, the ability to generate plausible causative hypotheses and/or confirmation where possible, the ability to computationally study potential clinical trial designs and/or results, as well as the further provision of advanced features incorporated in innovative methods, such as machine learning. In summary, molecular data expansion provides an elegant way to extend mechanistic modeling, systems pharmacology, and patient‐centered approaches for the assessment of drug safety. We anticipate that such advances in real‐world data informatics and outcome analytics will help to better inform public health, via the improved ability to prospectively understand and predict various types of drug‐induced molecular perturbations and adverse events.

Canine Oral Melanoma Genomic and Transcriptomic Study Defines Two Molecular Subgroups with Different Therapeutical Targets

Simple Summary

In humans, mucosal melanoma (MM) is a rare and aggressive cancer. The canine model is frequently and spontaneously affected by MM, thus facilitating the collection of samples and the study of its genetic bases. Thanks to an integrative genomic and transcriptomic analysis of 32 canine MM samples, we identified two molecular subgroups of MM with a different microenvironment and structural variant (SV) content. We demonstrated that SVs are associated with recurrently amplified regions, and identified new candidate oncogenes (TRPM7, GABPB1, and SPPL2A) for MM. Our findings suggest the existence of two MM molecular subgroups that could benefit from dedicated therapies, such as immune checkpoint inhibitors or targeted therapies, for both human and veterinary medicine.

Abstract

Mucosal melanoma (MM) is a rare, aggressive clinical cancer. Despite recent advances in genetics and treatment, the prognosis of MM remains poor. Canine MM offers a relevant spontaneous and immunocompetent model to decipher the genetic bases and explore treatments for MM. We performed an integrative genomic and transcriptomic analysis of 32 canine MM samples, which identified two molecular subgroups with a different microenvironment and structural variant (SV) content. The overexpression of genes related to the microenvironment and T-cell response was associated with tumors harboring a lower content of SVs, whereas the overexpression of pigmentation-related pathways and oncogenes, such as TERT, was associated with a high SV burden. Using whole-genome sequencing, we showed that focal amplifications characterized complex chromosomal rearrangements targeting oncogenes, such as MDM2 or CDK4, and a recurrently amplified region on canine chromosome 30. We also demonstrated that the genes TRPM7, GABPB1, and SPPL2A, located in this CFA30 region, play a role in cell proliferation, and thus, may be considered as new candidate oncogenes for human MM. Our findings suggest the existence of two MM molecular subgroups that may benefit from dedicated therapies, such as immune checkpoint inhibitors or targeted therapies, for both human and veterinary medicine.