Karolinska Institutet, FIMM
Precision Cancer Medicine
Making cancer care more effective and individualized is a central aim for cancer researchers worldwide. This is usually being pursued via DNA sequencing based efforts by the identification of oncogenic driver mutations. We believe and have emerging evidence that this will miss many therapeutic opportunities and additional endpoints including cell-based functional testing should be examined. Toward these goals, we carry out comprehensive ex vivo drug efficacy testing on patient-derived cells along with –omics profiling. We believe this approach will help to personalize treatment, aid in prioritizing drugs for clinical testing, provide for intelligent selection of drug combinations and improve treatment outcomes. Our work has a strong translational angle and is often carried out while the patient is receiving care. Our goal is to provide the treating clinician with additional treatment options should there be a need.
Initially we explored this functional drug testing platform in acute myeloid leukemia (AML) where the relevant material is more readily available. We have now also advanced to solid tumors including but not limited to ovarian, prostate and renal cancer. In solid tumors, relevant patient-derived ex vivo models are less readily available and the limited amount of tissue can be a challenge. Towards this we use different reprogramming methods of patient-derived primary cells in 2D, as well as 3D organoid cultures. We carry out genomics profiling of both tissue and model to ensure representativity of the cell models.
We have mapped the translational progress of our work into three phases, where phase I represents testing feasibility of model development. In phase II model development is doable, but representativity is still not optimal and no translation into treatment has been achieved. Phase III constitutes the final stage, where the cell models have generated actionable drugs that have been used in patient treatment. Our work is carried out in parallel both at the Science for Life Laboratory, Department of Oncology and Pathology, Karolinska Institutet in Stockholm, Sweden and at the Institute for Molecular Medicine Finland in Helsinki, Finland.
Olli Kallioniemi, Professor, Director SciLifeLab
Susanne Wikblad, PA, Admin
Päivi Östling, Associate Professor, Co-Principal Investigator
Brinton Seashore-Ludlow, Assistant Professor
Elisabeth Moussaud-Lamodiére, PhD, Senior lab manager
Sallinen Riitta, PhD, Project leader
Franscesco Marabita, PhD, Senior bioinformatician
Turkki Riku, PhD, Bioinformatician
James Tojo, PhD, Postdoctoral researcher
Sandra Jernström, PhD, Postdoctoral researcher
Tom Erkers, PhD, Postdoctoral researcher
Emilie Flaberg, PhD, MD stud, Postdoctoral researcher
Minozada Rezan, MSc, Labtechnician
Struyf Nona, MSc, Labtechnician
Consistency in drug response profiling. Mpindi JP, Yadav B, Östling P, Gautam P, Malani D, Murumägi A, Hirasawa A, Kangaspeska S, Wennerberg K, Kallioniemi O, Aittokallio T. Nature. 2016, Nov 30;540(7631): E5-E6. doi: 10.1038/nature20171, PMID: 27905421
Comprehensive drug testing of patient-derived conditionally reprogrammed cells from castration-resistant prostate cancer. Saeed K, Rahkamaa V, Eldfors S, Bychkov D, Mpindi JP, Yadav B, Paavolainen L, Aittokallio T, Heckman C, Wennerberg K, Peehl DM, Horvath P, Mirtti T, Rannikko A, Kallioniemi O, Östling P, af Hällström TM, Eur Urol. 2017 Mar;71(3):319-327 doi:10.1016/j.eururo.2016.04.019. Epub 2016 May 6. PMID: 27160946
Impact of normalization methods on high-throughput screening data with high hit rates and drug testing with dose-response data. Mpindi JP, Swapnil P, Dmitrii B, Jani S, Saeed K, Wennerberg K, Aittokallio T, Östling P, Kallioniemi O.Bioinformatics. 2015, Dec 1;31(23):3815-21. doi: 10.1093/bioinformatics/btv455. Epub 2015 Aug 7.
Axitinib effectively inhibits BCR-ABL1(T315I) with a distinct binding conformation. Pemovska T, Johnson E, Kontro M, Repasky G, Chen J, Wells P, Cronin C, McTigue M, Kallioniemi O, Porkka K, Murray B, Wennerberg K. Nature. 2015, Mar 5;519(7541):102-5. doi: 10.1038/nature14119. Epub 2015 Feb 9. PMID: 25686603
Individualized Systems Medicine (ISM) strategy to tailor treatments for patients with chemorefractory acute myeloid leukemia. Pemovska T, Kontro M, Yadav B, …, Aittokallio T*, Heckman CA*, Porkka K*, Kallioniemi O*, Wennerberg K*. Cancer Discov. 2013, Dec;3(12):1416-29. doi: 10.1158/2159-8290.CD-13-0350. Epub 2013 Sep 20. PMID: 24056683