A test that uses AI to measure proteins in some patients with colorectal cancer might just take its treatment to the next level. This new development is a result of a recent study published in the Clinical Research Cancer journal.
Proteins behind colorectal cancer
In association with researchers at Roche Diagnostics, researchers from the University of Leeds worked to get the best option for medical practice and patients. The study mainly used specimens from existing trials which the Cancer Research UK financially backed to observe the levels of two proteins, namely AREG and EREG. Certain colorectal cancers generated both.
A similar report by cancer said that algorithms ran by artificial intelligence allowed the researchers to prove that patients with higher levels of the two proteins stood to gain from therapy that constrains another protein that enhances cancer cell growth. The protein is identified as EGFR.
Equally essential, proteins with low levels of the two proteins did not gain much from the therapy. According to a report by Digital Health, EGFR therapy is currently only offered to people who suffer from Advanced chronic bowel cancers. The researchers hope that their approach can identify patients in earlier stages who could benefit from the therapy.
The lead author of the study, Christopher William, observed that as treatment methods of colorectal cancer increase, patients and health practitioners find it harder to identify which one to use. He hopes that using AI, patients with high levels of EREG and AREG will go through therapy and reduce their chances of acquiring EGFR.
The study’s release was timely as it coincided with the UK’s Bowel Cancer Awareness Month. Furthermore, the research was funded by Roche Diagnostics and Innovate UK.
Fast results required to make quick decisions
Roche Diagnostics’ senior director, who was also a senior author of the study, Kandavel Shanmugam, observed as complex experiments to get the best custom treatments for specific patients are developed, easier ways to deliver test results will need to be developed. The director further added that using AI to semi-automate the process will lessen the time patients have to wait for the results, which will positively affect the window they have to make decisions on treatment.
