Breast cancer is the most common cancer in the UK and 15% of new cancer cases are breast cancer. In 2015 just over 55,000 new cases were diagnosed, in 2016 just over 11,500 people died from the disease, 78% of women survive for 10 years or more and 23% of new cases were preventable in 2015. The number of new cases being diagnosed is rising in women, but stable in men.
It is recommended that women check their breasts regularly for lumps or signs of changes and attend a mammogram when invited to do so. If you find a lump or changes to your breasts, it is recommended to make an appointment to see your GP as soon as possible.
Scientists emphasise the importance of multigenerational family data to assess breast cancer risk
A study has emphasised the importance of taking multigenerational family information in order to assess a woman’s risk of developing breast cancer. The scientists, from Columbia University compared breast cancer prediction models and found that those models that used family history as a basis was more accurate, even if women had an average or below average risk of developing the disease. The study was published in The Lancet Oncology in February 2019.
The scientists used the Breast Cancer Prospective Family Study Cohort which has just under 19,000 women who live in the US, Australia and Canada. They did not have the disease when recruited between March 1992 and June 2011, and were aged between 20 and 70 years of age. These women also had a family history of breast cancer available. The scientists used four breast cancer risk models to calculate risk scores for the final group of just over 15,700 women. The risk models used a variety of ways to use information. The scientists then performed a second analysis to compare the risk models after 10 years.
The two models that contained multigenerational family history data were able to predict breast cancer risk more accurately than the other two models. This was also the case when women did not have a family history of the disease and did not have the BRCA1 and BRCA2 mutations. The models that did well were BOADICIA (the Breast and Ovarian Analysis of Disease, Incidence and Carrier Estimation Algorithm model) and IBIS (the International Breast Cancer Intervention Study model). The two that did not perform as well in women under 50 as well as in the study generally, were BRCAPRO (a computer programme which predicts whether a person has an inherited BRCA1 or BRCA2 mutation) and BCRAT (the Breast Cancer Risk Assessment Tool.
The scientists emphasised the importance of including a detailed family history when assessing the future risk of a woman developing breast cancer. Types of cancer and the ages at diagnosis should also be included. The scientists also suggested that further independent validation would be needed to help scientists which models should be used in which situations.
Breast cancer research information provides much-needed research tool
Since the discovery in 2012 that breast cancer was not just one, but 10 different diseases, with different prognoses and responding differently to treatments, scientists have been working hard to discover more about the conditions. They have also been trying to discover what can make recurrence more likely and whether the treatment given can affect this. The original study took biopsies from 2,000 women and sequenced the genetics to understand more about each tumour. The scientists were able to compare the samples to non-cancerous tissue samples from the same women and, most importantly, because the study has taken place over decades, they were also able to know the eventual result of the individual developing cancer.
Scientists from the Cancer Research UK Cambridge Institute and the British Columbia Cancer Agency have continued the work from the original study, testing more samples which have been collected from around the world to make sure that the disease was being classified correctly. They have found that the classifications made 7 years ago can still be applied today. The study was published in Nature and the abstract is available to read online.
They found that using the original classification from the 2012 study enabled them to predict how different types of the disease would behave as well as a DNA test for tumours known as PAM50. In some cases, their classifications were more accurate. The scientists also found that one of the 10 categories of breast cancer tumour had to be further split. This had been noted as a possibility in the original study.
The tumours had been grouped together because of features in their DNA, but some were oestrogen receptor positive and others were triple negative (had no receptors for oestrogen, herceptin or progesterone). This group had accounted for 1 in 5 tumours, but this discovery split it into two.
The scientists have also discovered more information about triple negative breast cancer tumours. These are the one of the most aggressive tumours, but the scientists again, found 2 groups: one that had a good chance of the cancer not returning if they had not had a recurrence within 5 years, while the other group had a very high chance of recurrent cancer, even after five years. This was the opposite to results in the previous trial. Treatment would be the same for both sets of patients, even though they could have very different outcomes.
The scientists recommend that their findings be taken into account when setting up new trials. They hope that it could provide better ways to treat the different types of tumour. A current trial in Cambridge is aiming to enrol women who are being categorised into the eleven different subtypes of breast cancer.
The findings of this study are not yet being used to influence practice in the NHS but the scientists hope that future studies will be able to influence current practice to enable more women to survive this disease.
- Caldas, C., et al., Dynamics of breast-cancer relapse reveal late-recurring ER-positive genomic subgroups, March 2019, Nature, 567, 399-404
- Terry, M.B., et al., 10-year performance of four models of breast cancer risk: a validation study, The Lancet Oncology, February 2019