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AI tool could pick out patients at highest risk of relapse

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Dr Yinyin Yuan

Team Leader in Computational Pathology at The Institute of Cancer Research, London

Most advanced cancers undergo genetic changes that enable them to resist drugs meant to kill them. Scientists like Dr Yinyin Yuan are working to better understand why this happens in lung cancer.

New research, which aims to harness the principles of evolution to stop cancer in its tracks, has transformed our understanding of how lung cancer evolves over time – and has highlighted how big of a role the immune system plays in cancer evolution.

This research is thanks to the TRACERx project; an initiative funded by Cancer Research UK, involving researchers like Dr Yinyin Yuan and the Computational Pathology and Integrative Genomics Team at The Institute of Cancer Research, London.

“Our research has helped us gain insight into how lung cancers can cloak themselves to escape the attention of the immune system. In doing so, it can continue to evolve and develop,” explains Dr Yuan. “Cancer’s ability to evolve and to come back after treatment is one of the biggest challenges facing cancer researchers and doctors today.”

Understanding the immune environment

TRACERx is helping scientists understand the types of immune landscapes that enable tumours to grow.

Tumours’ immune environments can differ. They can be filled with immune cells, or have almost none. Sometimes there is a mixture, with ‘hot’ regions full of immune cells and ‘cold’ regions with sparse immune cells.

This AI tool could be used in the future to pick out lung cancer patients at highest risk of relapse.

As part of the TRACERx initiative, Dr Yuan and her team have applied machine learning to genetic data and pathology images to create an AI tool capable of distinguishing immune cells from cancer cells.

This creates a detailed picture of how lung cancers evolve in response to the immune system in different patients.

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.

Therefore, 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.

Picking out patients at highest risk

The hope is that this AI tool could be used in the future to pick out lung cancer patients at highest risk of relapse, helping inform a more tailored treatment strategy.

“Our research is helping us understand why some lung cancers are so difficult to treat,” says Dr Yuan.

“We’re aiming to get a picture of the complex relationship between lung cancer and the immune system. By improving our understanding, we might be able to target cancer’s ability to evade the immune system – potentially coming up with ways to reactivate immune cells and encourage them to go after sly cancer cells.”

The biggest cancer killer in the UK

While the TRACERx initiative focuses on four cancer types – lung, melanoma, prostate and renal cancer – Dr Yuan’s team specifically studies lung cancer.

Her team’s research is bringing us closer to an era of precision medicine for this cancer type, which remains, by far, the biggest cancer killer in the UK.

“Lung cancer’s high mortality rate is partly due to its ability to evolve, become resistant to treatment and relapse. It is very encouraging to see that we can make progress by trying to understand lung tumours as evolving ecosystems.”

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