“Translational research seeks, as the name would suggest, to translate research findings into something that benefits patients in clinical care. Clinical experience, on the other hand, serves as a source of new approaches for research carried out in the laboratory,” Professor Arto Mannermaa explains.
In translational cancer research, the key focus is on the effects of genetic and environmental factors on the risk of cancer, as well as on factors affecting cancer prognosis, such as genetic and epigenetic variables, and the ability of cancer cells to survive treatment. Machine learning and deep neural network analysis are used to process large sets of data.
At the University of Eastern Finland, translational cancer research has been identified as a focus area in research, bringing together a number of researchers from different fields and covering a multitude of approaches ranging from the genetics of cancer and molecular mechanisms to imaging and clinical trials. The research area is led by Professor Veli-Matti Kosma, with Mannermaa as the deputy leader.
“The objective is to identify the key factors contributing to the risk of cancer, to improve cancer diagnostics, and to develop increasingly personalised and more effective treatments. Our research aims at discovering new biomarkers of cancer as well as new targets for cancer drugs,” Kosma says.
By combining data on the biological characteristics of tumours, such as mutations, with tumour imaging data, researchers are able to make increasingly accurate classifications of cancer. Information on an individual’s normal genetic background and lifestyle information are used in risk assessment. This results in a vast amount of data that can be analysed with the help of machine learning.
Close collaboration with other research groups within the university and with Kuopio University Hospital, as well as long-term international collaboration, constitutes a strength of cancer research at the Kuopio Campus. Other important resources include the Genome Centre of Eastern Finland, the National Cancer Center Finland and its regional unit Fican East, and the Biobank of Eastern Finland. The establishment of the latter has significantly improved the availability of high-level research materials. Currently, the biobank provides researchers access to materials of approximately 90,000 cases of cancer, and biobanks have already provided a significant boost for research in health sciences. For example, the international Finngen project is based on sample materials collected by biobanks from donors giving their voluntary consent. The objective is to chart the genetic background of half a million Finns.
More than 180 known risk factors of breast cancer
A number of genetic and environmental factors, such as lifestyles, contribute to the risk of cancer. For example, researchers have identified more than 180 genetic risk factors of breast cancer, which is the most common type of cancer in women. Researchers and patient data from Kuopio have also participated in these extensive international studies.
“The significance of individual genetic variation for a person's cancer risk is usually small, but in case of a large number of risk affecting variants, the susceptibility to develop cancer may become considerably high,” Kosma points out.
Instead of focusing on individual risk factors, researchers now use artificial intelligence to find the most important combinations of genetic and environmental factors.
Based on their genetic risk, one per cent of women have more than three times the average risk of developing breast cancer. The better these risk factors are known, the better screening and prevention measures can be targeted. Genes also play a role in how well a person responds to treatment. In some cases, treatment is already tailored on the basis of the patient’s genetic background and the genetic mutations found in the tumour. In the future, this will increase in the treatment of breast cancer and other cancers alike.
“For instance, a certain drug can be highly effective in a small group of patients who have a specific tumour subtype, while others may not benefit from the drug,” Mannermaa says.
New treatments stemming from hormonal regulation in cancer
New opportunities for treatment are also sought from hormonal regulation in cancer. Most breast cancers are estrogen-dependent, and this insight has been utilised in cancer treatments for quite some time. Moreover, prostate cancer, which is the most common type of cancer in men, is typically associated with severe disruptions in androgen and epigenetic regulation. Indeed, recent years have witnessed increasingly effective drugs targeting the androgen receptor. Drugs that operate on the epigenetic level, i.e. on the level of genetic regulation, are being developed for both breast and prostate cancer. At the University of Eastern Finland, Professor Jorma Palvimo’s research group studies the function of estrogen and androgen receptors in breast and prostate cancer cells, and their disturbed regulatory mechanisms at the genome- and proteome-wide levels. This line of research studies how to use these to find better biomarkers and to develop compounds that inhibit cancer cell growth.
Treatment-resistant and relapsed leukaemia constitutes a challenge
Unlike many other cancers, leukaemia can start to develop already during the foetal period. It is a challenge in some cases of relapsed leukaemia and leukaemia that is slow to respond to treatment that current methods are unable to shed light on what causes treatment-resistance and what alternative targets of treatment the cells might have.
“In leukaemic cells, we often find mutations in factors that regulate cell differentiation, which is why we expect discover cells that resemble stem cells and cells that are partially differentiated. The differentiation stage of cells can be identified in the gene transcription profile, which we nowadays can determine at the level of individual cells. Our findings clearly highlight cell plasticity, which is an important phenomenon to understand when developing new, targeted treatments,” Associate Professor Merja Heinäniemi says. Genome-wide analyses and deep sequencing techniques are a forte of Heinäniemi’s research group.
Imaging is an important aspect of cancer diagnostics, and imaging devices and methods are constantly evolving. Professor Ritva Vanninen’s research group studies MRI biomarkers, their prognostic significance and associations with genomic data and other biological characteristics of tumours. Using artificial intelligence, it is possible to process and validate large sets of imaging variables together with other factors that affect a cancer patient’s prognosis.