Conducted by London’s Institute of Cancer Research (ICR), the work applied machine learning to gene sequences and molecular data from breast tumours, identifying vital differences across ‘luminal A’ breast cancer that have until now been treated as a single category. Patients with luminal A tumours often have the best survival rates, but there is a wide response to the standard treatments given, with patients reacting differently to drugs and immunotherapy.
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“Doctors have used the current classification of breast cancers as a guide for treatment for years, but it is quite crude and patients who seemingly have the same type of the disease often respond very differently to drugs,” said Dr Maggie Cheang, leader of the Genomic Analysis Clinical Trials Team at the ICR.
“Our study has used AI algorithms to spot patterns within breast cancers that human analysis had up to now missed – and found additional types of the disease that respond in very particular ways to treatment.
“Among the exciting implications of this research is its ability to pick out women who might respond well to immunotherapy, even when the broad classification of their cancer would suggest that these treatments wouldn’t work for them.
The AI revealed that women with a cancer type labelled ‘inflammatory’ had immune cells present in their tumours and high levels of a protein called PD-L1, suggesting they were likely to respond to immunotherapies. Patients with tumours that contained a specific change in chromosome 8 had worse survival than other groups when treated with the drug tamoxifen, tending to relapse around 50 per cent earlier that patients with a different tumour type. Those patients could potentially benefit from an additional treatment to delay or prevent late relapse. The research, published in the journal NPJ Breast Cancer, could also help identify these new treatments and drug targets.
“Our new study has shown that AI is able to recognise patterns in breast cancer that are beyond the limit of the human eye, and to point us to new avenues of treatment among those who have stopped responding to standard hormone therapies,” said research lead Dr Anguraj Sadanandam, team leader in Systems and Precision Cancer Medicine at the ICR.
The ICR team had previously used AI in the same way to uncover five different types of bowel cancer. According to Dr Sadanandam, the same process could be applied across the entire spectrum of cancer, with potential for widespread targeted oncological treatments.
“AI has the capacity to be used much more widely, and we think we will be able to apply this technique across all cancers, even opening up new possibilities for treatment in cancers that are currently without successful options,” he said.
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Whoopee, they've solved how to keep a light on but not a lot else.