UK researchers secure £800k to investigate breast cancer recurrence using AI

UK researchers have secured £800,000 to use AI to study breast cancer recurrence, focusing on why some oestrogen receptor-positive tumours return years after treatment.

The funding will support two projects examining how cancer cells survive treatment, remain dormant and later begin growing again.

Most breast cancers do not return after treatment, but some cells can remain inactive for decades before reactivating, often leading to incurable metastatic breast cancer, which has spread to other parts of the body.

Researchers at The Institute of Cancer Research, London, will use the funding from Breast Cancer Now to study these processes and look for patterns that could help predict which cancers are more likely to return.

The projects focus on oestrogen receptor (ER)-positive breast cancer, in which cancer cells have receptors for the hormone oestrogen.

Professor Luca Magnani, Professor of Epigenetic Plasticity at The Institute of Cancer Research, London, said: “Dormant cancer cells are extremely hard to track and study due to their nature.

“We identified and analysed ad hoc clinical cohorts with cutting-edge technologies which could provide first hand insights into the nature of these cells and how standard treatments shape their evolution.

“The collaboration with Dr Secrier will dramatically scale up our ability to interrogate these unique datasets.”

Around 44,000 women are diagnosed with ER-positive breast cancer each year in the UK, accounting for approximately 80 per cent of all breast cancer diagnoses.

The first project, led by Professor Magnani in collaboration with Dr Maria Secrier from University College London, will investigate how ER-positive cancer cells become dormant, remain inactive and resume growing.

Using artificial intelligence (AI) models trained on large datasets from cancer cells undergoing treatment, researchers will examine molecular changes linked to dormancy and look for patterns that could help explain how cells become inactive and reactivate.

They will also study how dormant cancer cells interact with surrounding immune cells, blood vessels and connective tissue, and whether these interactions help or hinder the cells.

The aim is to identify biological changes that could signal when dormant cells are likely to become active again.

A second project, led by Dr Maggie Cheang, will analyse tumour samples from people with ER-positive breast cancer who participated in the POETIC clinical trial.

The trial followed patients for more than 10 years after surgery, collecting tumour samples before treatment, during therapy and from cancers that subsequently returned.

Researchers will use imaging, molecular analysis and AI to study how cancer cells are organised, interact with surrounding tissue and survive treatment.

They hope to identify signs, potentially within two weeks of diagnosis, that a cancer is developing treatment resistance or is more likely to return.

Treatment resistance occurs when cancer cells survive or stop responding effectively to therapies intended to control them.

Dr Cheang said the research could eventually help doctors assess recurrence risk and offer more personalised follow-up care.

“Late relapse can feel unpredictable and frightening. We want to change that.

“By combining detailed imaging, molecular and clinical trial data with the power of AI, we can study tumours in much greater detail and find patterns that would be impossible to see otherwise.

“We hope this will help us spot risk earlier, guide better treatment and give people more confidence about the future.”

Neither project has yet established a method of predicting or preventing recurrence. Both are investigating the biological processes that could help make this possible.

Dr Simon Vincent, chief scientific officer at Breast Cancer Now, said the projects could help develop tools to identify people at greater risk and allow doctors to tailor follow-up care.

For people who have undergone breast cancer treatment, the possibility of the disease returning can remain a concern.

The researchers hope their findings will eventually help doctors identify treatment resistance earlier and provide more tailored care after breast cancer treatment.