Artificial intelligence (AI) can predict if an aggressive type of breast cancer will spread, based on changes in a patient’s lymph nodes, Breast Cancer Now funded scientists have discovered.
The research, published today (Friday 26th May) in The Journal of Pathology, shows that by analysing the immune responses in the lymph nodes of women with triple negative breast cancer, it’s possible to tell how likely the disease is to spread to other parts of the body.
When breast cancer cells spread from the cancer in the breast to other parts of the body it’s called secondary or metastatic breast cancer and although treatable, it can’t be cured.
The team at the Breast Cancer Now Unit at King’s College London have developed an AI model to predict how likely a patient is to develop secondary (incurable) breast cancer based on immune responses in the lymph nodes.
Lymph nodes are pea-sized lumps of tissue found throughout the body that help it fight against infection. Breast cancer cells typically first spread to lymph nodes in the armpit (axilla) which are closest to the tumour. If this has happened, patients are usually given more intensive treatment.
However, the scientists discovered that even when the breast cancer cells hadn’t spread to the lymph nodes, it was still possible to predict, from their immune responses, the likelihood of the cancer spreading elsewhere in the body.
The scientists tested their AI model on more than 5,000 lymph nodes donated by 345 patients to biobanks*, including the Breast Cancer Now Tissue Bank. They confirmed it could establish the likelihood of breast cancer spreading to other organs.
The team hope the AI model will be tested in clinical trials and could one day assist doctors in planning treatment, helping give patients peace of mind about the likelihood of triple negative breast cancer spreading.
Around 15% of breast cancers are triple negative and there are currently few targeted treatments. Triple negative breast cancer is more likely than most other breast cancers to return or spread during the first years following treatment.
This type of breast cancer is more common in women who have inherited an altered BRCA gene, black women, women who have not yet reached the menopause and women aged under 40.
Dr Anita Grigoriadis, who led the research at the Breast Cancer Now Unit at King’s College London, said: “By demonstrating that lymph node changes can predict if triple negative breast cancer will spread, we’ve built on our growing knowledge of the important role that immune response can play in understanding a patient’s prognosis.
“We’ve taken these findings from under the microscope and translated them into a deep-learning framework to create an AI model to potentially help doctors treat and care for patients, providing them with another tool in their arsenal for helping to prevent secondary breast cancer.
“We’re planning to test the model further at centres across Europe to make it even more robust and precise. The transition from assessing tissue on glass slides under a microscope to using computers in the NHS is gathering pace. We want to leverage this change to develop AI-powered software based on our model for pathologists to use to benefit women with this hard-to-treat breast cancer.”
Dr Simon Vincent, director of research, support and influencing at Breast Cancer Now, said: “Each year around 8,000 UK women are diagnosed with triple negative breast cancer, which is a more aggressive form of breast cancer, often with poorer outcomes.
“If, thanks to this research, it’s possible to provide women with more tailored treatment and care based on the likelihood of the breast cancer spreading, it could help to save lives and reduce stress and worry. We look forward to further findings to understand how this could work in practice to benefit women affected by this type of breast cancer.”
ENDS
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Notes to Editors
*Additional support for this research was provided by the KCL Cancer biobank, Tianjin Medical University, IIT Bombay and Tata Memorial Hospital and The Netherlands Cancer Institute
Breast Cancer Now’s vital research is only possible thanks to the incredible generosity of its supporters. This project’s funding was supported by the Asda Tickled Pink campaign.
Additional funding was provided by Cancer Research UK and the Medical Research Council.
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The research was carried out by Anita Grigoriadis, Gregory Verghese, Mengyuan Li and Fangfang Liu with guidance from Amit Sethi, Louise Jones, Sarah E Pinder and Roberto Salgado.