Researchers Develop Computer Model to Predict Prostate Cancer Progression

Researchers Develop Computer Model to Predict Prostate Cancer Progression

A new study has yielded a new computer model to understand the progression of prostate cancer, which may yield insights into understanding the disease and providing care for patients.

The study, “Molecular Evolution of Early-Onset Prostate Cancer Identifies Molecular Risk Markers and Clinical Trajectories,” was published in Cancer Cell.

One of the main challenges for researchers studying prostate cancer is understanding the progression of the disease at the molecular level so that accurate predictions can be made regarding prognosis and optimal treatment.

Given the complexity of genetic and molecular events that take place during prostate cancer development, an international team of researchers sought to develop a computer model that analyzes these changes and differentiates between aggressive and non-aggressive disease.

Researchers particularly focused on the earliest mutational events in prostate cancer, and collected data from 292 men with early onset prostate cancer  (diagnosed before age 55).

This data included the fully sequenced cancer genome, as well as the tumor transcriptome (what genes are being expressed) and methylome (a measurement of one kind of epigenetic alteration, which can affect how DNA sequences are “read”).

Using this data, the researchers created a computer model for the progression of prostate cancer.

“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,” Joachim Weischenfeldt, co-author of the study, said in a press release. “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.”

The team was able to group cancer patients into four major subgroups based on these molecular alterations, each one having different risks. Among these, they found that patients with rearrangements in the gene ESRP1 tend to have particularly aggressive tumors — a finding that was validated in 12,000 other patients with the same kind of tumor.

The researchers were particularly interested in understanding the earliest events that initiate prostate cancer, and by analyzing their model, they devised a hypothesis that might explain how at least some of these tumors form. They think that the earliest mutations in prostate cancer are caused by the enzyme APOBEC3.

“We hypothesize that this enzyme mutates the prostate cells at a low but constant rate,” said Jan Korbel, a study co-author. “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.”

Weischenfeldt said,”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.”

The computer model is currently being implemented at a hospital in Germany, and there are plans to continue adding data to keep refining it.

“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,”  Weischenfeldt said.