Breast Cancer Now commits £800,000 to AI research into late breast cancer recurrence

pharmafile | October 28, 2026 | News story | |  AI, Immunology, Oncology, breast cancer, cytology, oncology, research and development 

Breast Cancer Now is investing £800,000 in two research projects using artificial intelligence (AI) to investigate why oestrogen receptor-positive (ER-positive) breast cancers can recur years after treatment, with the aim of identifying patients at greatest risk.

Around 80% of breast cancers in the UK are ER-positive. Although many patients do not experience a recurrence, some cancer cells survive treatment in a dormant state before becoming active again, potentially leading to incurable metastatic disease.

Professor Maria Secrier at University College London, working with Professor Luca Magnani’s laboratory at The Institute of Cancer Research (ICR), will use AI models trained on cancer-cell data to investigate how ER-positive cancer cells enter and remain dormant, and what prompts them to resume growing.

The team will also examine how dormant cells interact with their surrounding environment, including immune cells, blood vessels and connective tissue, to identify biological changes that may signal a future recurrence.

A second project, led by Dr Maggie Cheang at the ICR, will analyse tumour samples from the POETIC clinical trial, which followed patients for more than 10 years after breast cancer surgery. Samples collected before and during treatment, alongside samples from cancers that subsequently recurred, will be studied using advanced imaging and molecular techniques.

AI and computational analysis will then be used to identify patterns associated with treatment resistance and later recurrence. The researchers hope to find early indicators of risk, potentially detectable within two weeks of diagnosis, that could eventually help clinicians tailor treatment and follow-up.

“The challenge of understanding why some ER-positive breast cancers come back after many years is not a lack of data, but a lack of innovative tools to study the data,” said Professor Secrier. “So we’re combining cutting-edge AI with our biology expertise to find ways to predict, and stop, ER-positive breast cancer returning.”

The projects aim to improve understanding of late recurrence and lay the groundwork for better risk prediction. Further research would be needed to establish whether the findings can support reliable clinical tools or change patient management.

Pic: NCI