‘Super Test’ for Prostate Cancer to Revolutionize Screening and Diagnosis

Each year, there are 55,000 new cases of prostate cancer in the UK, over 330,000 across the European Union, and more than one million men receiving treatment at any given time. Most men initially undergo prostate-specific antigen (PSA) tests as the first step in evaluating prostate cancer, but elevated PSA levels are considered unreliable for a definitive cancer diagnosis. Research has shown that approximately 70% of men with elevated PSA levels do not have cancer, while about 20% of men with normal or low PSA levels do have cancer—often an aggressive subtype that is only discovered later when there is limited time for effective treatment. To address this issue, scientists have developed a new "super test" for prostate cancer aimed at revolutionizing the screening and diagnosis of the disease, accelerating personalized treatment options for patients.

Developed by scientists at EDX Medical (Cambridge, UK), the test detects the presence or absence of cancerous cells, identifies early and late-stage cancer signs, differentiates between slow-growing and aggressive types, and assesses genetic and hereditary risks in the patient. The "super test" uses a multi-omics approach, combining proteomic, transcriptomic, genetic/hereditary, and epigenetic biomarker signatures to provide comprehensive biological data. This new test studies the most comprehensive combination of clinically validated prostate-related biomarkers known, from both blood and urine samples. It measures over 100 clinically validated biomarkers, which are then analyzed by a specially developed artificial intelligence (AI)-powered algorithm that generates a detailed report for doctors. These biomarkers have all been clinically validated and published in previous trials involving more than 31,000 positive prostate cancer samples and over 100,000 control non-cancer samples. In contrast, current advanced tests typically rely on up to 20 biomarkers per test.

In addition to biomarker data, a detailed list of phenotypic and symptom data is incorporated and analyzed simultaneously by the AI algorithm. This interpretation, driven by the proprietary AI algorithm, highlights early cancer signs and key characteristics that can inform treatment decisions. The non-invasive "super test" can identify various prostate cancer subtypes, focusing on features particularly important for patients in higher-risk non-Caucasian groups. The scientists expect the test to consistently deliver extremely high accuracy, with sensitivity and specificity between 96-99% across a broad age range and diverse ethnic groups. In comparison, current standard prostate testing, such as PSA tests and biopsies, often have accuracy rates below 50%. A highly accurate prostate cancer test would offer significant benefits for seemingly healthy men aged 45-70, as well as for healthcare providers. The improved accuracy should reduce the need for unnecessary MRI scans and significantly decrease the reliance on highly invasive digital rectal examinations (DRE).

“We have been studying this area intensively and are tremendously excited by what we believe is a truly game-changing test. Every indication thus far shows it will be the most accurate and sensitive screening test available and will be transformative in tackling prostate cancer in men who may have no idea if anything is wrong with them,” said Prof Sir Chris Evans, founder and chief scientific officer of EDX Medical. “Our integrated approach highlights the potential of combining these molecular signatures, offering a powerful, non-invasive diagnostic tool that can certainly improve clinical outcomes and help personalize treatment for patients. The incorporation of all these biomarkers into routine screening could revolutionize prostate cancer management by enabling earlier detection and more accurate risk prediction. What sets this test apart is the use of so many biomarkers with best-in-class instrument and reagent technology and our bespoke AI algorithm.”

Related Links:
EDX Medical

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