What is UM’s main focus?
At the department of Toxicogenomics of Maastricht University (UM) we have a multidisciplinary team of (cell) biologists, chemists, geneticists, toxicologists and bioinformaticians that is working in close collaboration to establish the biological impact of exposures to potentially toxic compounds and to develop safe therapeutic strategies for genetic and non-genetic diseases. The rapid development of omics-technologies, has enabled us to establish responses on different molecular levels with higher sensitivity than most classical effect markers, and providing information on the involved molecular mechanisms of action. As such, toxicogenomics research combines toxicology with genomics approaches, and in particular next generation sequencing, in order to obtain more accurate understanding of toxicological processes and related disease mechanisms in order to maintain, restore or improve normal function. The application of these innovative omics-technologies in in vitro investigations of human, (patient-derived) cell models, in human population studies and in human health risk analysis can be regarded as the central research paradigm of our department.
The mission of our department is to explore, develop and to exploit the full potential of innovative cell technologies and genomics platforms, for the purpose of advancing mechanism-based in vitro assays using human cells, for predictive toxicology, as well as for developing novel biomarkers of toxic exposure and related diseases to be used in human population studies. Furthermore, we aim to contribute to the prevention and treatment of human disease by facilitating the development of safe drugs, stem cell therapy and consumer products without animal testing, by designing (personalized) prevention and treatment strategies and the identification of environmental health hazards.
How has participating in TransQST impacted your organization?
Participating in TransQST enabled us to collaborate with several Pharma companies that are experienced in developing multi-scale models that make it easier to assess the safety profile of drug candidates before undergoing clinical testing phase. Through this collaboration we were able to further explore how transcriptomic and metabolomics data can be integrated in such models. This has eventually resulted in new methodologies that can be applied for risk assessment by pharma partners.
Another impact on our work is the establishment of a new organoid based model of the gastro-intestinal tract, either with or without co-culture of immune cells. Adding immune cells to the organoid system allow the evaluation of potential impacts of inflammatory conditions on drug toxicity. The collaboration with CrownBio advanced the characterization of the phenotypic responses of our organoid model after exposure to different toxic compounds.
What challenges has UM faced across the project? What are your main achievements in TransQST?
At UM, we have successfully established human colon organoids to investigate drug-induced mechanisms of toxicity. Our drug treated “mini-gut” model provided an abundance of good quality data, including functional and morphology assays, image analysis, transcriptomics and metabolomics. This data can now be integrated computationally by TransQST partners to evaluate mechanisms of GI toxicity induced by different classes of compounds. We have extensively investigated the chemotherapeutics 5-FU, doxorubicin and gefitinib (tyrosine kinase inhibitor). We also led the establishment of a 3D co-culture combining colon organoids and macrophages, in order to study inflammation-associated drug toxicity. We were able to expose the co-culture to a few compounds, namely LPS, doxorubicin and ibuprofen (a NSAID). The results with the co-culture were promising. LPS and doxorubicin stimulated the production of cytokines in the co-culture, and the addition of ibuprofen, being an anti-inflammatory, decreased the levels of cytokines in the supernatant. We concluded that we have developed a novel co-culture system combining colon organoids and intestinal macrophages in the context of TransQST goals. Future studies on longer-term co-culture system and test different compounds are being planned.
Finally, we were also responsible for a human intervention study with cancer patients taking a monotherapy with capecitabine (5-FU). One of the main goals was to compare the patients responses with those of colon organoids exposed to 5-FU. Some overlapping in biological processes and gene markers was observed. Taken all together, findings from this study will help future drug design and screening studies particularly on deciding which is the most suitable and translatable preclinical model to predict more accurately all human risks.
Several publications led by the UM team as a result of our work and collaborations have been already published in leading international scientific journals.
The biggest challenges were the delays caused by Covid-19. The lab work had to be interrupted which caused delays in generating data. It also affected greatly the human intervention study, as we could not recruit any patients during the pandemic. Nevertheless, we were able to overcome these challenges and generate good quality and insightful results on drug-induced intestinal toxicity.
Which TransQST outcomes would you highlight and why?
We would like to highlight the advanced in vitro models (organoids) and experimental designs that were established during this project. Likewise, the in silico tools that were developed successfully thanks to the efforts and collaboration of many researchers/institutions. Together, we were able to create alternative models that can provide insight into drug toxicity and improve assessment of drug safety profiles, which are aligned with the project goals. Moreover, the TransQST was successful in the many collaborations that took part in the project, particularly those between academia and pharma companies, bringing them closer.
In your view, what is the main contribution of TransQST in the field?
It was clear from the start of TransQST that in comparison to other organs, less progress had been made on human-relevant prediction of drug-induced GI toxicity and that large data gaps were evident. Our work on the advanced human organoid models resulted in the generation of new data on GI toxicity. In addition, new data were also generated for both in vitro and in vivo rodent models. The data generated, including transcriptomic and metabolomics and phenotypic responses allowed for cross-compounds and cross-species comparisons that were not available before, i.e. translational analyses could be conducted. Furthermore, we integrated the omics data in multi scale models for GI toxicity. In fact, we believe that the greatest advances of predictive models that can be used by pharma partners in drug development were made for GI toxicity. Currently, discussions with regulators are ongoing on how to advance the predictive models on GI toxicity for the next generation of risk assessment procedures.