What exactly is cancer drug sensitivity screening and precision medicine?
Precision medicine is all about tailoring diagnostics and treatment to find the molecular causes of a disease. Once these molecular causes are found, we can then target them to
the extent possible in each patient. This implies stratifying patient populations using modern diagnostics tools, which can include biomarkers, whole exome or genome sequencing into groups that will or will not benefit from a particular treatment, or individualising treatment at the level of each patient.
Cancer drug sensitivity screening is one new method we are exploring to see if we can advise clinicians on how to individualise cancer treatment. It implies testing a panel of drugs directly on cancer cells from each patient in vitro to see which drugs can kill the cancer cells from that particular patient.
This method is in its early stages, and it should be used in combination with mutational analysis and all other types of data available from the patient. Predictions of what will work inside patients also need to be tested in animal models, followed by clinical trials to see how well the method works. Next, we would need to assess how much patient benefit this actually gives.
How are you working with cancer drug sensitivity screening and precision medicine at NCMM/UiO?
In my group at NCMM we are currently testing some 400 drugs at five different concentrations against cancer cells from patients with two types of leukaemia - chronic lymphocytic leukaemia and multiple myeloma. This project is a collaboration with the groups of Prof Ludvig Munthe, Dept. of Immunology OUS / Klinmed, UiO and Professor Geir Tjønnfjord and Dr Fredrik Schjesvold. Dept of Haematology, OUS, and funded by the Regional Health Authority for South Eastern Norway and the Norwegian Cancer Society.
Our next move is to model on the data we have, integrating other types of information, to help predict combinations of drugs that may be even more powerful (drug synergy prediction) and test those against patient cells.
Ultimately, we want to test such predictions in xenograft models with patient-derived cells, (in collaboration with the groups of Dr. Judith Staerk and Camila Esguerra at NCMM), and then in patients in small clinical trials. We are working to establish the system’s pharmacology component to analyse the data with Arnoldo Frigessi’s group at the Oslo Centre for Biostatistics and Epidemiology, and also with international collaborators at FIMM (Institute for Molecular Medicine Finland), the EMBL (European Molecular Biology Laboratory) and elsewhere.
With the UiO: Life Science Convergence grant, we want to take this approach further by looking at solid tumours and, in a more integrative approach where we have medical imaging data, sequencing data and cancer drug sensitivity screening data from several cancers in patients on and off treatment. Here, we will develop the modelling and simulation aspects even further.
What do you hope to discover?
We hope to find methods to advise clinicians on how to individualise the treatment of cancer patients that have already exploited other treatment options. We hope to develop models and algorithms that allow us to predict, based on the data, which drug combinations to test in order to save patient materials.
We then hope to be able to enter clinical trials to test such predictions in patients and ultimately to provide some patient benefit. I would also like us to be able to integrate testing of immunomodulating strategies in the pipelines for cancer drug sensitivity screening.
What do you think these types of research mean for cancer therapies, and cancer patients in the longer term?
I think it is important to keep exploring opportunities for patients and what new technological advances may bring in terms of patient benefit. Since NCMM leads the national infrastructure for chemical biology and high-throughput screening (NOR-OPENSCREEN) and has one of the four nodes in this network, we have the technology and robotics to actually do cancer drug sensitivity screening.
I felt it was important that we started working with cancer drug sensitivity early on at NCMM, so that we have competence and methods to support such projects. Alongside supporting researchers at NCMM, it’s important that we can also support a breath of such projects in different cancers lead by scientists all over Norway.
Where do you hope these types of therapies will be in ten years’ time? Do you have any more thoughts on the future of personalised cancer research?
In terms of cancer drug sensitivity screening, I think it will take around five years before we have data from patients. We need to establish the testing and screening methods for each cancer. We will need to test a series of patient samples in vitro, validate these findings in animal models with patient-derived xenografted cancers, and then test predictions in the first patients in clinical protocols.
From there we will then, if successful, need to test more patients. I expect that the jury is going to be out for another five years to determine how much patient benefit such an approach may actually deliver. I think this is only one strategy that will co-develop with other methods which could dramatically change this path. Furthermore, I think that the power of heterogeneous data integration, modelling and simulations and machine learning may accelerate the development considerably. It will be very exciting to see how introduction of such methods could transform medicine in many fields.
"Looking for a shortcut to personalised medicine" Interview with Kjetil Taskén about personalised medicine on Titan.uio.no: https://titan.uio.no/node/2163
Watch a presentation by Kjetil Taskén on individulaised cancer therapy at the UiO:Life Science Conference 2017 via the NRK website (Presentation starts 16 minutes into the video): https://tv.nrk.no/serie/kunnskapskanalen/MDDP17000617/17-06-2017