The initial focus on leukaemia research has resulted in a series of publications in top level journals (e.g. NEJM, Nature, Cancer Discovery, Blood, Leukaemia). These studies have established FIMM and its collaborators as global leaders in functional assessment and translational research in this disease area.While leukaemia has been the basis and flagship of this programme, it has expanded to other cancer types, including multiple myeloma, ovarian cancer, prostate cancer, renal cell carcinoma, lung cancer, and melanoma.
A key area of focus for several FIMM research groups, and building from the DSRT techniques, includes the development of AI and machine learning tools to integrate clinical, functional, and genomic profiles to predict drug targets and to identify response-predictive marker combinations for improved clinical translation—including prediction of effective synergistic drug combinations. FIMM researchers, along with their collaborators at Helsinki Institute for Information Technology HIIT, have excelled in several international crowdsourcing competitions for highly demanding scientific problems, including response prediction in cancer cells and patients. Winning models have been published in Nature Biotechnology in 2014 and Lancet Oncology in 2016.
The systems-wide approaches to understand disease progression and treatment response of cancer have been complemented with strong disease modelling and functional studies. For example, studies of immunocompetent murine models of lung cancer have provided evidence that the cell-of-origin plays a major role in the aetiology of histotype-specific tumour progression, amounting to heterogeneity in lesion-specific immune microenvironments (Nagaraj et al. 2017). In addition, tumour explant modelling refined through a public-private IMI-PREDECT consortium effort (2011-2016, coordinated from FIMM), showed that combination responses to signalling inhibitors corresponds with spatially-defined targeted pathway activities. These modelling efforts not only yielded protocols and tissue biomarkers of drug response, but importantly, endorse that phenotypic profiling of functional drug responses of each individual patient’s unique tumour tissue is essential.