The iCAN Flagship Project is a globally unique pan-cancer biobank study. It combines cancer genetics, translational and clinical cancer research, biobanks, information technology and artificial intelligence in a completely novel way.
The project links deep molecular profiling of at least 15,000 fresh frozen tumors with patients’ longitudinal health data, including electronic health records, national registries and patient reported outcomes. The research hypothesis is that through this linkage, a new level of understanding of cancer in the context of the host will be achieved.
Using machine learning and AI to extract relevant predictive features from each dataset and level, the study is expected to increase knowledge of immuno-oncology, tumor microenvironment and development of disease resistance – and thereby result in discoveries of new targets and contribute to development of improved treatments.
In addition to accelerating discoveries, the aim is to extract new relevant predictive features, provide a platform for developing early-stage leads/diagnostics, and to enable adaptive clinical trials.
Multidisciplinary research teams advancing breakthrough discoveries
The study currently includes 15 subprojects, detailed below. Their multidisciplinary teams include clinicians, researchers, technicians, nurses, surgeons, pathologists, molecular biologists and data scientists. The number of Principal Investigators currently exceeds 70 and the number of total staff amounts to nearly 200.
The iCAN teams have a strong track record in translational and clinical cancer as well as data science, which has generated more than 33,000 citations and over 120 highly cited publications.
The subprojects study a wide range of cancer types: abdominal, colorectal, lung and thoracic, breast, ovarian, urologic, pediatric, and rare cancers, lymphomas, multiple myeloma, and acute myeloid leukemia. Each has a specific research focus, as well as responsibilities in sample collection and analysis, as described in the list below.
|Name of study||Coordinating Principal Investigator (PI)||Acronym|
|Pan-cancer organoid biobank for precision medicine in abdominal cancers||Toni Seppälä||iCAN-PANORG|
|Somatic and hereditary genetic variation in colorectal cancer||Lauri A. Aaltonen||iCAN-COLGEN|
|Integrating ctDNA, organoid, and drug sensitivity analyses for precision medicine in lung and thoracic cancer||Ilkka Ilonen||iCAN-LUNG|
|Translating structured data to novel treatments in breast cancer||Samuli Ripatti||iCAN-BREAST|
|Immunogenomic profiling to discover effective combination therapies for ovarian cancer||Anniina Färkkilä||iCAN-OVA|
|Dissecting the crosstalk between brain tumor cells and astrocytes||Pirjo Laakkonen||iCAN-BRAIN|
|Discovery of new targets and approaches for precision cancer medicine in pediatric solid tumors||Minna Koskenvuo||iCAN-PEDI|
|Molecular profiling and ex vivo tumor models of rare cancers for the discovery of novel cancer treatments||Outi Monni||iCAN-RARE|
|Individualized prostate cancer diagnostics and treaments based on advanced profiling||Antti Rannikko||iCAN-PROSTA|
|Complex immune organoids of urological cancers for the discovery of novel immunotherapeutic treatments||Vincenzo Cerullo||iCAN-IMORG|
|Functional immunological profiling of selected malignancies||Satu Mustjoki||iCAN-IMMPROF|
|Towards risk-adapted, biomarker-driven treatments in lymphomas||Sirpa Leppä||iCAN-LYMPH|
|Exploring leukemogenesis with deep phenotyping and integrative machine learning||Outi Kilpivaara||iCAN-LEUKE|
|Determining drug responses in multiple myeloma & acute myeloid leukemia||Caroline Heckman||iCAN-HEMA|