Core competence of the group is in the methods of computer science, statistical modeling, and machine learning. We often utilize a data-driven approach based on high-throughput genomic, epigenomic, transcriptomic and/or proteomic data. These data are integrated and analyzed computationally in an effort to better understand the biological processes and networks driving a disease or phenotype. The generated hypotheses are then validated and refined experimentally.

In addition to computational work we have set up an experimental brain tumor research program in collaboration with Tampere University Hospital. We are utilizing and developing primary cell cultures and single cell analysis to gain insight into tumor biology.

Selected research directions:

Integrative tumor data analysis

We develop and apply computational methods for integration of multilevel genomics and proteomics data from in-house and public data sets. We have actively participated in international networks including the Cancer Genome Atlas. Here our main focus is on understanding the mechanisms that are driving tumor progression and evolution. We study how heterogeneous genomic aberrations in clinical tissue samples affect tumor phenotypes and converge through gene regulatory networks. We mainly focus on prostate cancer and brain tumors.

Main collaborators: Prof. Tapio Visakorpi, Prof. G. Steven Bova, Prof. Ilya Shmulevich, Adj. Prof. Olli Lohi, Adj. Prof. Merja Heinäniemi

Circulating tumor DNA analysis

We develop computational methods for reconstructing the genomic landscape of cancer cells in a patient’s body, based on fragments of tumor DNA in their bloodstream. These minimally invasive “liquid biopsies” (10 mL blood sample) enable clinicians to understand the mutations driving a patient’s cancer, and allow them to better guide patient treatment. In collaboration with the Vancouver Prostate Centre, we use liquid biopsies to study mechanisms of resistance against approved and experimental cancer therapies in internationally leading clinical trials, particularly in the context of prostate cancer and bladder cancer.

Main collaborators: Dr. Alexander Wyatt, Prof. Teuvo Tammela, Prof. Tapio Visakorpi

Brain tumor research

We have developed Brain tumor research program at Tampere in collaboration with University of Tampere and Tampere University Hospital. We utilize extensive retrospective sample collection of brain tumors, have setup prospective brain tumor sample collection, and are developing primary cell cultures from gliomas. We aim to characterize brain tumor heterogeneity and to understand the interplay of tumor cells and immune cells as drivers of brain tumors. We also seek to develop tools for diagnostics and management e.g. through application of cell free tumor DNA analysis.

Experimental brain tumor research team is led by Dr. Kirsi Granberg.

Main collaborators: Hannu Haapasalo, MD, PhD, Joonas Haapasalo, MD, PhD, Kristiina Nordfors MD, PhD, Prof. Wei Zhang

Bioimage informatics

Bioimage informatics research team focuses on developing image analysis for cancer research and digital pathology. Our research uses state-of-the-art machine learning for quantitative analysis of whole slide images of histological tissue sections both in 2D and in 3D. Our solutions facilitate routine pathology through decision support in diagnosis, and provide novel insight for cancer research through quantitative characterization of heterogeneity in the tissue.

Bioimage informatics team is led by Adj. Prof. Pekka Ruusuvuori.

Main collaborations: Prof. Carolina Wählby, Prof. Martin Eklund, Adj. Prof. Leena Latonen, Prof. Tapio Visakorpi, Prof. Jorma Isola, Adj. Prof. Merja Heinäniemi