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Computer Model to Predict Prostate Cancer Progression

No. 68 | 11/12/2018

An international team of cancer researchers from Germany and Denmark have used cancer patient data to develop a computer model that can predict the course of disease for prostate cancer. The model is currently being implemented at a prostate cancer clinic in Germany. The researchers have also found the enzyme that appears to trigger some of the first mutations in prostate cancer.

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Prostate cancer is one of the most frequently diagnosed cancer in men in the western world with more than a million new cases each year. One of the key challenges is to differentiate between aggressive and non-aggressive disease. An international team involving researchers from BRIC at the Faculty of Health and Medical Sciences, the University of Copenhagen, and Rigshospitalet, the German Cancer Research Center (DKFZ) and the European Molecular Biology Laboratory (EMBL) in Heidelberg will solve this challenge with a computer model.

The researchers have studied the earliest mutational events in prostate cancer to develop a computer model, described in a new study that has just been published in the scientific journal Cancer Cell. The researchers collected patient data from close to 300 men who have had their entire cancer genome sequenced to characterise all mutations present in the tumour. Based on the data set, the researchers have developed the computer model which can be used to predict how prostate cancer will develop for a given patient.

'If we have a patient with a particular set of mutations, we can use the model to predict the most likely next mutation that the patient will experience at some point - and how it will affect the patient's clinical situation. As an illustration, we can predict with some probability that if you have mutation A, you are likely to get mutation B before you get C. We can also predict if the next mutation is likely to change the clinical outcome of the disease'.

'So far, our data sets comprise around 300 patients, but we expect to collect data from several thousand patients in the coming years. The model will be better the more data it can learn from', says group leader and co-author of the study Joachim Weischenfeldt, BRIC, UCPH.

The computer model is currently being implemented at a clinic in Germany. The researchers expect it to take two to three years to have the model fully implemented as an integral part of the clinic's processes. Later, in a not too distant future the researchers hope that the model can also be introduced at hospitals in other countries, for example Denmark.

Mechanism Contributing to the First Mutations in Prostate Cancer Have Been Found

The approximately 300 patients from the study all had their entire genome sequenced. With genome sequencing, it becomes possible to tailor the treatment of the individual - also referred to as personalised medicine. The patients whose data the researchers have used have primarily been so-called early onset patients. This group is defined as men who are diagnosed with prostate cancer before reaching the age of 55 years.

'Prostate cancer develops over many years. We have therefore been particularly interested in the group of patients where the cancer is detected at young age as this allows us to analyse the tumour at an early stage. This is an important element because in this way we get a cleaner picture of the first mutations and alterations that occur in the tumour, to find out what is the initiating factor', says co-author Doctor Clarissa Gerhauser, DKFZ.

So far, it has not been known precisely what initiates prostate cancer. However due to the focus on the earliest detected tumours, the researchers uncovered a mutational mechanism involving an enzyme called APOBEC. This enzyme may help trigger the disease – i.e. trigger some of the very first mutations in prostate cancer.

'We hypothesise that this enzyme mutates the prostate cells at a low but constant rate. Each time the cell divides, APOBEC is likely to cause mutations. If you have early-onset prostate cancer, you may have a couple of mutations caused by APOBEC. Twenty years later, you may have 10-20 mutations', says co-author Doctor Jan O. Korbel, group leader at EMBL.

'The most common oncogene in prostate cancer involves a certain fusion gene. The APOBEC enzyme may contribute to the formation of this fusion gene. We cannot say that there is causality, but there is a strong correlation between mutations caused by APOBEC and other alterations such as this fusion gene,' says Joachim Weischenfeldt.

The researchers have also found a putative novel oncogene in prostate cancer – ESRP1 – which is associated with very fast-dividing and highly aggressive prostate cancer. It is located closely to an already known oncogene, and the researchers believe this is the reason that it has not been discovered until now. In the study, the researchers show that the oncogene ESRP1 may be used as a possible new biomarker to detect whether a patient will have aggressive prostate cancer, which they validated on a cohort consisting of 12,000 other patients with the same type of cancer.

The study is the result of a large transnational collaboration between universities from different countries among others Germany, Norway, Canada and Denmark. Besides UCPH, DKFZ, EMBL, Max Planck Institute for Molecular Genetics and Charité – Universitätsmedizin Berlin has e.g. also been involved with professor and co-author Thorsten Schlomm, who is leading the clinical implementation of the computer model at the clinic in Germany.

The study is supported by the German Federal Ministry of Education and Research (BMBF) through projects for early onset prostate cancer, the Arvid Nilsson Foundation, Rigshospitalet's Research Foundation, the ERC Starting Grant, the Sander Foundation, grant from the Helmholtz International Graduate School at the German Cancer Research Center, the Norwegian Research Council and the American National Institute of Health.

C. Gerhäuser et al.: Molecular Evolution of early onset prostate cancer identifies molecular risk markers and clinical trajectories. Cancer Cell 2018, DOI: 10.1016/j.ccell.2018.10.016

With more than 3,000 employees, the German Cancer Research Center (Deutsches Krebsforschungszentrum, DKFZ) is Germany’s largest biomedical research institute. DKFZ scientists identify cancer risk factors, investigate how cancer progresses and develop new cancer prevention strategies. They are also developing new methods to diagnose tumors more precisely and treat cancer patients more successfully. The DKFZ's Cancer Information Service (KID) provides patients, interested citizens and experts with individual answers to questions relating to cancer.

To transfer promising approaches from cancer research to the clinic and thus improve the prognosis of cancer patients, the DKFZ cooperates with excellent research institutions and university hospitals throughout Germany:

  • National Center for Tumor Diseases (NCT, 6 sites)
  • German Cancer Consortium (DKTK, 8 sites)
  • Hopp Children's Cancer Center (KiTZ) Heidelberg
  • Helmholtz Institute for Translational Oncology (HI-TRON Mainz) - A Helmholtz Institute of the DKFZ
  • DKFZ-Hector Cancer Institute at the University Medical Center Mannheim
  • National Cancer Prevention Center (jointly with German Cancer Aid)
The DKFZ is 90 percent financed by the Federal Ministry of Education and Research and 10 percent by the state of Baden-Württemberg. The DKFZ is a member of the Helmholtz Association of German Research Centers.


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