Screening of cancer drug sensitivity data to predict cancer therapies.
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.
University of Oslo (PIs Arnoldo Frigessi and Anna Smajdor)
Arnoldo is professor in statistics and group leader of the Innovation and Industry involvement working group.