How does a normal cell turn into a deadly cancer? Seeking an answer to this question, and working alongside other international working groups, researchers examined the tumor genomes of nearly 300 prostate cancer patients. Their findings describe the ways in which changes in the prostate cells' genetic information pave the way for cancer development. Using a newly-developed computer model, it is now possible to predict the course of the disease in individual patients. It is hoped this will enable clinicians to develop tailor-made treatments. The results of this study were published in the journal Cancer Cell.
Prostate tumors are usually slow-growing, meaning that not all patients require immediate treatment. Until recently, physicians had been unable to distinguish between benign and aggressive forms of the disease, particularly when dealing with tumors diagnosed at an early stage in the disease process. The researchers developed a criterion that would make this type of classification possible.
To do so, they studied the molecular profiles of close to 300 prostate tumors. They sequenced the information encoded within the cells' genetic material, recorded chemical changes to the genetic code, and measured the activity of specific genes within cancerous tissues. The integrative analysis identified four molecular subgroups, including a particularly aggressive subgroup with recurrent duplications associated with increased expression of ESRP1, which was validated in 12,000 tissue microarray tumors. "We were able to identify tumor subtypes that progress at different rates and therefore require different types of treatment," says one of the study's lead authors.
The author adds: "We now know which of these mutations occur first, initiating the process of change from prostate cells to tumor cells, and which of them are more likely to follow later." The researchers then used these results to develop a computer-based model capable of predicting the likely course of the disease in individual patients. "When an individual patient's tumor shows a specific mutation, we are now able to predict which mutation is likely to follow, and how good the patient's prognosis is," explains the led author. "Our team is currently busy incorporating our computer model into the treatment process. This will enable clinicians to model a particular treatment's likelihood of success. As for the timescale involved, we expect it will take two to three years for this algorithm-based method to become clinical routine."
In an effort to improve the reliability of prognoses, the research consortium is planning to spend the next few years collating additional data on thousands of patients, which they will then use to further develop and enhance their computer model. Their ultimate aim is to make it easier for physicians to decide on the most suitable treatments for individual patients.
Predicting the prostate cancer progression using computer model!
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