AI Tool Enhances Treatment Selection for Advanced Bowel Cancer Patients

Researchers at London’s Institute of Cancer Research (ICR) and the RCSI University of Medicine and Health Sciences in Dublin have developed an AI-driven tool named PhenMap, aimed at identifying which patients with advanced bowel cancer are most likely to benefit from the drug bevacizumab. This drug, recently approved by the NHS, is designed to slow cancer progression by depriving tumors of essential growth proteins. However, it is effective for only a small subset of patients and can cause serious side effects, including blood clots and gastrointestinal issues.

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In the UK, approximately 10,000 cases of advanced bowel cancer are diagnosed annually, with a notable increase among young adults. The five-year survival rate for advanced cases is as low as 10%, underscoring the urgency of effective treatment strategies. The study analyzed data from 117 European bowel cancer patients who had previously undergone chemotherapy and were treated with bevacizumab. By integrating complex genetic data, PhenMap can identify patients likely to experience adverse reactions to the drug, potentially sparing thousands from unnecessary side effects.

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PhenMap utilizes advanced AI algorithms to analyze the genetic makeup of colorectal cancer (CRC) tumors alongside clinical and demographic data. The tool generates a score indicating the likelihood of a patient benefiting from bevacizumab, as well as a risk score for potential mortality following treatment. Notably, the study found that patients with a mutation in the BRAF gene were consistently categorized as high-risk, correlating with poorer outcomes.

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Anguraj Sadanandam, a professor at ICR, emphasized the significance of this development, stating, “Once bowel cancer spreads to other parts of the body, there are very few treatment options available for patients.” He noted that while the introduction of bevacizumab is a positive step, many patients may not benefit, leading to unnecessary side effects.

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The researchers plan to validate PhenMap's effectiveness using a larger cohort of patients and explore its applicability to other cancer types. The hope is that this tool will not only enhance clinical outcomes but also optimize NHS resources by reducing the financial burden associated with ineffective treatments.

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While the findings are promising, there are calls for caution. The need for extensive testing on larger patient groups before widespread implementation has been highlighted, as the current study's sample size may not fully represent the diverse patient population.

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There is a discrepancy regarding the number of patients eligible for bevacizumab treatment. According to the National Institute for Health and Care Excellence (NICE), approximately 7,000 out of the 10,000 diagnosed with metastatic disease each year are eligible. However, the broader implications of the AI tool's effectiveness remain to be fully explored.

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“Our research uses advanced AI methods to pull together large amounts of complex data, helping us to spot patterns that would otherwise be impossible for a human to see, and to uncover the clues hidden within a patient’s tumour.” — Anguraj Sadanandam, Professor, ICR

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“However, we know that the majority of patients won’t benefit from the drug, meaning thousands of people in England could be facing unpleasant side effects unnecessarily.” — Anguraj Sadanandam, Professor, ICR

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“Once bowel cancer spreads to other parts of the body, there are very few treatment options available for patients.” — Anguraj Sadanandam, Professor, ICR

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“Until now, we haven’t been able to identify these patients.” — Anguraj Sadanandam, Professor, ICR

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