Artificial Intelligence Could Create Better Outcomes For Bowel Cancer Patients
United Kingdom, 22 April 2021 – A test which uses artificial intelligence (AI) to measure proteins present in some patients with advanced bowel cancer could hold the key to more targeted treatment, according to research published today.
A team at the University of Leeds collaborated with researchers at Roche Diagnostics to develop the technique, which will help doctors and patients to decide on the best treatment options.
They used samples from a previous trial funded by Cancer Research UK to look at the levels of two proteins, known as AREG and EREG, which are produced by some colorectal cancers.
Algorithms driven by AI enabled the researchers to show that patients with higher levels of these proteins received significant benefit from a treatment which inhibits a different protein involved in cancer cell growth, known as EGFR. Of equal importance, patients with low levels of the proteins did not benefit from the treatment.
Currently, anti-EGFR treatments are only given to patients with advanced, incurable bowel cancers. The researchers hope their methodology could be used in the future to identify patients in the earlier stages of illness who could also benefit from the drugs.
Lead author of the report, Christopher Williams, from Leeds University’s Division of Pathology and Data Analytics, said: “As more treatment options become available for advanced colorectal cancer, it is becoming increasingly difficult for patients and their doctors to choose the treatment that’s right for them. This test will help patients navigate this decision-making process more easily.”
Today’s publication of the findings in the journal Clinical Cancer Research is timely as it coincides with Bowel Cancer Awareness Month in the UK. The study was funded by Innovate UK and Roche Diagnostics as well as Yorkshire Cancer Research. It was part of a program of work in this field being conducted by the National Pathology Imaging Co-operative.
The report’s senior author, Kandavel Shanmugam, who is a senior director of medical innovation at Roche Diagnostics, said: “As increasing numbers of complex tests are developed to target the right cancer treatments to the right patients, developing streamlined methods for delivering test results will be essential to improve cancer care.
“By using artificial intelligence to semi-automate the test process, we anticipate it may be easier for results to be delivered to patients faster to better influence treatment decisions.”
Roche is a global pioneer in diagnostics and pharmaceuticals focused on advancing science to improve people’s lives.
Abstract
Purpose High tumor mRNA levels of the EGFR ligands, amphiregulin (AREG) and epiregulin (EREG) are associated with anti-EGFR agent response in metastatic colorectal cancer (mCRC). However, ligand RNA assays have not been adopted into routine practice due to issues with analytical precision and practicality. We investigated whether AREG/EREG immunohistochemistry (IHC) could predict benefit from the anti-EGFR agent, panitumumab. Experimental Design Artificial intelligence algorithms were developed to assess AREG/EREG IHC in 274 patients from the PICCOLO trial of irinotecan+/-panitumumab (Ir vs IrPan) in RAS wild-type (-wt) mCRC. The primary endpoint was progression-free survival (PFS). Secondary endpoints were Response Evaluation Criteria in Solid Tumors (RECIST) response rate (RR) and overall survival (OS). Models were repeated adjusting separately for BRAF mutation status and primary tumor location (PTL). Results High ligand expression was associated with significant PFS benefit from IrPan compared with Ir (8·0 vs 3·2 months; HR 0·54, 95% CI 0·37-0·79; p=0·001); whereas low ligand expression was not (3·4 vs 4·4 months; HR 1·05, 95% CI 0·74-1·49; p=0·78). The ligand- treatment interaction was significant (pinteraction=0·02) and remained significant after adjustment for BRAF- mutation status and PTL. Likewise, RECIST RR was significantly improved in patients with high ligand expression (IrPan vs Ir: 48% vs 6%; p<0·0001) but not those with low ligand expression (25% vs 14%; p=0·10) (pinteraction=0·01). The effect on OS was similar but not statistically significant. Conclusion AREG/EREG IHC identified patients who benefitted from the addition of panitumumab to irinotecan chemotherapy. IHC is a practicable assay that may be of use in routine practice.
Further information
Read the full research, Artificial intelligence-assisted amphiregulin and epiregulin immunohistochemistry predicts panitumumab benefit in RAS wild-type metastatic colorectal cancer, published 22 April 2021 in the journal Clinical Cancer Research. DOI: 10.1158/1078-0432.CCR-21-0120
For media enquiries contact University of Leeds press officer Kersti Mitchell at k.mitchell@leeds.ac.uk.
The University of Leeds
The University of Leeds is one of the largest higher education institutions in the UK, with more than 38,000 students from more than 150 different countries, and a member of the Russell Group of research-intensive universities. The University plays a significant role in the Turing, Rosalind Franklin and Royce Institutes.
We are a top ten university for research and impact power in the UK, according to the 2014 Research Excellence Framework, and are in the top 100 of the QS World University Rankings 2021.
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Source: Roche Diagnostics
