An international team of researchers lead by Luca Magnani, from Imperial College, London, UK as part of the EU H2020 EpiPredict consortium coordinated by Pernette Verschure, SILS, UvA has developed strategies to deduce intra-tumour and inter-patient phenotypic heterogeneity. The researchers annotated the epigenome in clinical samples from patients with luminal breast cancer. Crucially, the findings reveal how tumours can change their ‘appearance’ to evade cancer treatments, using epigenetic mechanisms. Findings have been published online in Nature Medicine.

Tumour heterogeneity is a major hurdle
Breast cancer is the most common cancer type and second most frequent cause of cancer-related death in women. 70% of all breast cancer patients are diagnosed with estrogen receptor positive (ER+) breast cancer and receive hormone therapy as follow-up treatment. In more than 20% the cancer returns later on and can develop into a metastasized more advanced tumour form that spreads around the body. The intra-tumour and inter-patient phenotypic heterogeneity is a major hurdle for diagnosis and treatment outcome. In this study, the researchers tackled this tumour heterogeneity by monitoring the epigenome of tumour samples from patients with primary or metastatic ER+ breast cancer.

Epigenetic regulatory mechanisms
Epigenetic regulatory mechanisms play an important role in maintaining cell-type specific gene expression. Changes in epigenetic regulation enable cancer tumours to adapt to their environment, evade treatment – and ultimately survive longer. The researchers systemically monitored epigenetic regulatory regions, called enhancers, that act as ciphers to tell the cell to switch on certain genes to become activated. Chemical modifications of DNA associated histone proteins were measured in clinical ER+ breast cancer tumours. The results revealed that particularly the Yin Yang 1 protein has a unique role in driving epigenetic enhancer activity and in switching on the SLC9A3R1 gene, which helped cancers grow and evade treatment.

Epigenetic tumor evolution
The findings may open avenues for new treatments, and help understand why some tumours become resistant to treatment. This suggests doctors should take new tumour samples when a patient’s cancer spreads around the body, said Dr Luca Magnani, study author from the Department of Surgery and Cancer at Imperial, PI in the EU H2020 funded EpiPredict consortium: “At the moment, patients usually have a biopsy when they are first diagnosed with breast cancer. Doctors then analyze this tissue sample to identify what type of breast cancer a patient has, as this will dictate the best treatment for them. However, our results suggest tumours switch different genes on and off as they progress, which can fundamentally change their ‘appearance’. Therefore, if a tumour becomes more aggressive, and spreads around the body, we would advise always taking a second biopsy. The cancer might have changed significantly in this time, and would respond to different treatments. Although taking a second biopsy when a patient’s cancer relapses is becoming much more much common, it’s still not happening all the time.”

International teamwork
The research team including researchers from the Department of Surgery and Cancer at Imperial, the European Institute of Oncology in Milan, the University of Liverpool, and Case Western Reserve University in Cleveland, will now study larger numbers of patient samples, and follow the same group of patients to track how epigenetic enhancer activation in these cancers evolves. They will also investigate a type of breast cancer known as triple negative, which is very difficult to treat. Dr Magnani said: “As expected, our work has raised a lot of questions - and we now need to answer them. But it is only through international collaboration – and working as a team – that we can get this vital work done, and hopefully help more patients beat the disease. We could have never done this on our own.”
 
The work was funded by the Wellcome Trust, Cancer Research UK and the European Union, EpiPredict (642691) from the Marie Sklodowska Curie actions programme.