Screening of cancer drug sensitivity data to predict cancer therapies.
PINpoINT is developing a digital pipeline to identify tailored treatments for individual patients with hematological cancer and to model patient outcome using computational predictive tools.
The project started in the second half of 2019 and most of our recent efforts have focused primarily on generating datasets required for the final stage of the project, i.e. analysis, mathematical modeling and predictions of drug/drug interactions.
Eight articles have recently been published that capitalize on these datasets and analyses. Examples of these articles include the development of a novel tool to analyze large drug combination datasets, which often consist of millions of datapoints; predictive biomarkers for drug responses of chronic lymphocytic leukemia cells; and novel insight into intracellular signaling pathways.
The project has now entered its final stage, during which we will disseminate our findings and datasets that were created in the earlier stages of the project. We expect to publish several high-impact, interdisciplinary articles in 2022 and 2023.
One highlight of 2021 was a workshop that PINpOINT co-organized with Bioteknologirådet on November 29 at Litteraturhuset in Oslo: “Hvor presis er egentlig presisjonsmedisin?”, which discussed whether it is realistic to reach and fully implement precision medicine, its major challenges, and how society can contribute to precision medicine-focused research. For us, the added value is the dynamic interaction between biologists, mathematicians and ethicists, which allows us not only to develop a pipeline for precision medicine for leukemia, but also to investigate the ethical, legal and regulatory aspects of such a personalized medicine pipeline to ascertain Responsible Research and Innovation.
Is it possible to predict which cancer therapies will be effective before administering them to the patient? PINpOINT, a collaboration of research labs at Oslo University Hospital and the University of Oslo, is screening cancer drug sensitivity data to do just that.
Blood cancers like acute myelogenic leukemia, multiple myeloma, and chronic lymphocytic leukemia, can be difficult to treat because people respond differently to treatments. While hematologists work to find the right treatment, the cancer may grow and worsen and the patient may experience side effects. Even when an effective therapy is identified, many patients cannot tolerate it or develop resistance to it. Combining therapies can improve drug responses and delay resistance, but the genetic factors and biomarkers that determine whether treatments will be effective for certain patient populations are still largely unknown.
By linking genetic testing with drug response information, PINpOINT will predict which drugs and drug combinations will be effective blood cancer therapies and at what dose. This type of precision medicine approach may improve treatment outcomes, reduce the side effects and costs of therapies, and even help discover new drugs or treatment schemes.
PINpOINT’s model uses data from viability testing of live patient cells and high-throughput flow cytometry (HTFC) tests after applying therapeutic drugs to cancer cells in the lab. The researchers use this information to validate drugs and combinations of drugs outside of the patients, avoiding side-effects and speeding up drug efficacy tests. The researchers’ early results showed that the doses of ibrutinib and venetoclax, common and effective treatments for chronic lymphocytic leukemia, could be reduced by a factor of 10-100 without losing efficacy.
Building a complete model of drug-cancer interactions requires expanding the data set to include patients beyond Norway and collecting millions of data points about clinical history, genomic markers, drugs, and drug combinations. Putting all of this information into a predictive model requires a great deal of scientific expertise and computing power. To meet this challenge, the PINpOINT team is made up of researchers from labs with expertise in leukemias and myeloma, biostatistics specific to tumor research and systems pharmacology. The PerCaThe project, also part of the Digital Life Norway portfolio, has overlapping PIs and expertise and is working to answer similar questions. The DLN-affiliated DrugLogics project at NTNU is also focused on systems pharmacology in cancer.
PINpOINT aims to improve drug efficacy and reduce side effects through better understanding of personalized cancer treatment. Their goal is to create a clinical decision-support system that uses patient drug sensitivity, genomic, and clinical data to model responses and make treatment suggestions. The researchers will work with the Norwegian biotech advisory board for communication and dissemination and will be hosting public discussions to make sure that patients and clinicians are involved in the development. The researcher in charge of the PINpOINT RRI activities, Anna Smajdor, has a background in medical research ethics. PINpOINT will also share their results with pharmaceutical companies to facilitate interaction, collaboration and further development based on findings.
PINpOINT is headed by Kjetil Tasken and Jorrit Enserink at the Institute for Cancer Research at Oslo University Hospital.