When the subject of cancer arises, a common topic of discussion is the need for newer, better treatment options. This is, of course, an important goal – but what we often overlook is that we already have a wide variety of drugs available to us. The issue is that, when a patient presents with a rare type of cancer, we don’t know its drug susceptibilities – and that, understandably, hinders the selection of the most effective treatment.
To combat this, my colleagues and I used patients’ own cells to create tumor organoids. These smaller, lab-grown versions of tumors maintain the cell-cell interactions, heterogeneity, and drug response of their cancer of origin. A high-throughput method can then screen hundreds of treatments to identify the pathways that are particularly vulnerable to drug inhibition.
Many rare tumors are poorly characterized at the molecular level. For some, we have so little information on their drug response that there is no established standard of care at all. This is partly because it’s very difficult to perform clinical trials for rare cancers, which is why my colleagues and I aim to create organoid models that can test not only targeted therapies, but also different chemotherapy regimens to help guide future treatment decisions.
The cancer cells that form tumor organoids come directly from surgery and can be seeded on the same day. Once established, our technique uses a miniaturized system with hundreds of wells to automatically assess the effect of each drug on the organoids. This setup means that we can add 96 drugs in under two minutes.
When we tested the method on four patients – one with peritoneal cancer and three with ovarian cancer – we were able to build personalized snapshots of the most effective drugs for each patient’s organoids. For example, one had an extremely rare type of ovarian cancer that is diagnosed in fewer than 200 US women each year. This patient’s organoids responded to a class of drugs called cyclin-kinase inhibitors, which can prevent the cancer from growing. Under ordinary circumstances, we would have had no way to determine the effect of cyclin-kinase inhibitors on this specific cancer subtype because there are no known biomarkers.
We now plan to work closely with pathologists to procure the tissue and validate the organoid models, and with oncologists to pinpoint a list of treatments that should be prioritized for testing. Because this approach provides results within a week of surgery, we believe that it is compatible with therapeutic decision-making and hope to make organoid screening an option for as many patients as possible.
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References
- N Phan et al., “A simple high-throughput approach identifies actionable drug sensitivities in patient-derived tumor organoids”, Commun Biol, 2 (2019). PMID: 30820473.
