AI could predict risk of lung cancer recurrence

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Computer scientists working with pathologists have trained an artificial intelligence tool to determine which patients with lung cancer have a higher risk of their disease coming back after treatment—part of Cancer Research UK’s landmark TRACERx study.

The AI tool was able to differentiate between immune cells and cancer cells, enabling researchers to build a detailed picture of how lung cancers evolve in response to the immune system in individual patients.

The paper was published in Nature Medicine May 27 and is showcased alongside eight other TRACERx publications on the Nature website.

Although this research is in its early stages, the approach could speed up how doctors predict which patients are more likely to see their lung cancer return, so they can be closely monitored with tailored treatment plans.

The AI tool—developed by researchers at The Institute of Cancer Research, London, in collaboration with scientists at University College London Cancer Institute and the Francis Crick Institute—was trained by pathologists to pick out immune cells from cancer cells. This allowed the tool to map out areas in tumours where the number of immune cells were high compared to the number of cancer cells, in patients with lung cancer.

Using the AI tool, the team found that while some parts of the tumor were packed with immune cells, described as hot regions, other parts of the tumour appeared to be completely devoid of them, which they described as cold regions.

When the researchers followed the progress of patients who had a higher number of cold regions, they found patients were at a higher risk of relapse.

This study is part of the TRACERx* (Tracking Cancer Evolution through therapy [Rx]) lung study—a £14 million, 9-year study funded by Cancer Research UK.

In the study, led by Yinyin Yuan, of The Institute of Cancer Research, and researchers from the UCL Cancer Institute and the Francis Crick Institute, AI pathology image-mapping technology was combined with next-generation sequencing. They used this tool to analyse samples from 100 patients with non-small cell lung cancer who took part in the TRACERx study.

The team’s work revealed that cancer cells found in immune cold regions may have evolved more recently than cancer cells found in immune hot regions that are packed with immune cells.

The researchers suggest that areas of the tumour with fewer immune cells may have developed a cloaking mechanism under evolutionary pressure from the immune system allowing them to hide from the body’s natural defences.

Their AI tool can assess how many regions with this cloaking mechanism exist within a tumor.

“Our research has revealed fresh insights into why some lung cancers are so difficult to treat, and we wouldn’t have been able to do this without the scale and scope of the TRACERx project,” Yuan said.

TRACERx is Cancer Research UK’s single biggest investment in lung cancer.

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