“Scientists have identified five types of prostate cancer, each with a distinct genetic signature,” BBC News reports. The hope is that recognising the genetic signature of a specific cancer could lead to targeted treatments, as is the case with some types of breast cancer.
By analysing the DNA of prostate cancer cells from 259 men, researchers identified five distinct prostate cancer subgroups. Called “iClusters”, the subgroups described the genetic characteristics of the tumour and gave clues about how it might behave in the future.
In the future doctors might be able to use the iClusters to decide the best treatment for each man. However, they are not yet ready to be used in hospitals to influence treatment decisions.
Where did the story come from?
The study was carried out by researchers from the University of Cambridge in collaboration with academic institutions in Sweden, Norway and Belfast.
It was funded by a large number of academic and charity medical research funders, including the National Institute for Health Research, Cancer Research UK, and the Swedish Cancer Society.
The study was published in the peer-reviewed medical journal EBioMedicine.
The BBC’s article was balanced and accurate. It quoted researcher Dr Alastair Lamb, who said: “These findings could help doctors decide on the best course of treatment for each individual patient, based on the characteristics of their tumour.”
He also cautioned there were still many questions to be ironed out, including whether the technique could be used routinely in hospitals.
What kind of research was this?
This was a genetic study seeking to identify subgroups of prostate cancer. Prostate cancer is the most common cancer in men in the UK (not counting non-melanoma skin cancer), with more than 40,000 new cases diagnosed every year.
The cause remains unknown, and some cases of prostate cancer are more aggressive than others. Currently, treatment decisions and prognosis are based on the size and type of the tumour, whether it has spread, and the level of prostate-specific antigen (PSA) in the blood. PSA is a protein produced by the prostate.
In this study, the researchers wanted to see if the characteristics and behaviour of prostate cancers could be predicted by particular DNA errors.
Some countries use PSA to screen asymptomatic men for prostate cancer. But current opinion in the UK is this is not accurate enough. Inaccuracy could lead to many unnecessary operations in healthy men that can in turn lead to life-impacting complications, such as urinary incontinence and impotence.
Understanding the genetics and behaviour of cancer could be fundamental to improving the way we treat the disease in the future.
What did the research involve?
DNA data from the prostate cancer cells of 259 men were number-crunched to produce five distinct subgroups, termed “iClusters”. These not only described the tumour’s DNA characteristics, but to some degree predicted their future clinical behaviour.
In total, the researchers studied 482 tumour samples from 259 men with primary prostate cancer. They produced the initial five subgroups using data from 156 men from a Cambridge database. To validate the findings, they repeated the exercise in a further 103 men from a Stockholm database.
The team also had data on tumour progression, including six-monthly PSA tests and cancer staging. The researchers didn’t have survival information, so instead used “biochemical relapse” to predict future clinical behaviour. Biochemical relapse was defined as a PSA level above 0.2ng/ml.
The number-crunching involved integrating data on the number of copies of genes associated with prostate cancer (copy number alterations) and genetic points linked to changes in gene expression (known as array transcriptomics). This integrated approach is the origin of the “i” in iCluster.
What were the basic results?
The study identified five separate patient subgroups with distinct genomic alterations and expression profiles, based on 100 discriminating genes. These subgroups consistently predicted biochemical relapse and were further validated in a third cohort with long-term follow-up.
The discriminating genes included six previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), but also 94 not previously linked to the disease.
The study said the subset of the 100 genes outperformed established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures.
How did the researchers interpret the results?
The researchers said the five profiles could be used for the early detection of aggressive cases of prostate cancer in a clinical setting, and inform treatment decisions.
They said: “Our findings are clinically significant because they will assist urologists in recommending different treatment approaches for those men who are classified as being in low, intermediate or high-risk categories according to conventional clinical criteria.”
Using DNA analysis, this study identified five subgroups (iClusters) of prostate cancer. A large portion of the iCluster-discriminating genes were not previously known to be linked to prostate cancer – an interesting finding in itself. The hope is the iClusters might help doctors treat the disease better based on their specific genetic signature.
However, this study focused on developing reliable subgroups. It did not look at whether the groups improved treatment, disease progression or death rates from prostate cancer. This research is yet to be carried out.
One of the main limitations of the research is it used biochemical relapse to estimate survival. This may not be accurate and reduces the ability of the iClusters to predict future survival at this stage.
Dr Alastair Lamb, quoted by BBC Online, said: “The next step is to confirm these results in bigger studies and drill down into the molecular ‘nuts and bolts’ of each specific prostate cancer type.”
Also on BBC Online, Dr Iain Frame, of Prostate Cancer UK, said: “For men to truly benefit from these findings, it is now vital that the research community comes together to confirm the most efficient methods for testing for different types of prostate cancer that can be brought to the clinic.”