The University of Nottingham

A study by researchers in Nottingham has identified seven distinct types of breast cancer, a discovery which could lead to new and improved prognostic tests for patients with the disease.

The findings, reported in the British Journal of Cancer, could revolutionise the way in which breast cancer patients are treated by giving clinicians more detailed information about a patient’s breast cancer type and helping them create a more personalised treatment plan, avoiding over or under-treatment.

The research, funded by Breast Cancer Campaign, was led by Dr Andy Green in the University’s Division of Oncology, in collaboration with colleagues at Nottingham University Hospitals NHS Trust and Nottingham Trent University.

Dr Green said: “With an increasing number of treatment options available for breast cancer patients, decision making regarding the choice of the most appropriate treatment method is becoming increasingly complex. Improvements in care and outcome for patients with breast cancer will involve improved targeting of effective therapies to appropriate patients.

“Equally important should be improvement in parallel strategies to avoid unnecessary or inappropriate treatment and side effects.”

Affordable test

Breast cancer is a biologically complex disease and each tumour can have very different properties, so the more information that doctors have about each patient’s cancer, the better they can plan treatments. Currently just two proteins are tested for as standard in breast cancer cells (known as biomarkers): the oestrogen receptor (ER), and human epidermal growth factor receptor 2 (HER2), alongside information about the tumour size, spread and grade[1],[2],[3].

Dr Green and colleagues, who also included Professor Ian Ellis in the Division of Oncology and Jon Garibaldi and Daniele Soria in the University’s School of Computer Science, wanted to see if, by testing for more biomarkers, but keeping the number of biomarkers as low as possible to make an affordable test a realistic proposition, they could devise categories that better reflect the diversity of breast cancer and, importantly, better predict how a patient’s cancer is likely to progress.

Using tissue that now forms part of the Breast Cancer Campaign Tissue Bank, the team tested 1073 tumour samples and from these, 997 (93%) fitted perfectly into one of seven classes, whereas 76 (7%) had mixed characteristics and couldn’t be put into a distinct category. They then verified these classes in another 238 tumour samples.

The seven classes are defined by different combinations and levels of ten biomarkers found in breast cancer cells. These biomarkers include ER and HER2, the two biomarkers currently tested for in clinics, but also others that are not currently tested for, such as p53, cytokeratins, HER3 and HER4.