Wilding, Sam, Goss, Victoria, Sukdao, Wesley, Hamady, Zaed, Lord, Joanne, Coleman, Adam, Pointer, Catherine, Walters, Jocelyn, Herbert, Will, Mclaughlin, Katy, Waugh, Robert, Irvine, Nicola, Oliver, Tom, Soulsby, Irene, Hooper, Julie, Crabb, Simon J., Griffiths, Gareth, Yates, Emma and Davies, Andrew (2025) Multicancer early detection in a cohort of patients with confirmed and suspected cancer by measuring plasma amino acid cross sections with the Enlighten test: MODERNISED protocol. BMJ Open, 15 (11), [e108220]. (doi:10.1136/bmjopen-2025-108220).
Abstract
Introduction: detecting cancer earlier improves treatment options and long-term survival. A multicancer early detection test that reliably picks up early-stage cancer would potentially save lives and reduce the cost of treating cancer. One promising candidate is the Enlighten test, which applies machine learning to plasma amino acid concentrations to detect cancer. In a cohort of 77 patients recently diagnosed with breast, colorectal, pancreatic or prostate cancer, 60 (78%) were detected by the test (sensitivity), with no false positives in 20 healthy controls. The MODERNISED study will further develop the Enlighten test to detect 10 different cancers by adding bladder, lung, melanoma, oesophageal, ovarian and renal cancer to the test.
Methods and analysis: MODERNISED (ISRCTN17299125) is a multicentre prospective, non-interventional, case–control study. We aim to recruit 1000 adult participants with a recent cancer diagnosis, 250 adult participants with symptoms of cancer where a cancer diagnosis was ruled out by the National Health Service (NHS) standard of care and 100 healthy adult volunteers. Cancer tissue of origin (ToO) will include bladder, breast, colorectal, lung, melanoma, oesophageal, ovarian, pancreatic, prostate and renal. Participants in the two non-cancer cohorts who are later diagnosed with cancer will be moved to the cancer cases cohort. The primary aim is to train and validate a machine learning algorithm to detect cancer, which will be evaluated by AUROC. Secondary aims include training and validating an algorithm to predict ToO and stage of cancer, exploring differences in performance by demographics and estimating how sensitivity varies across specificity cut-offs of 95%, 99% and 99.9%. These results will provide a statistically powered estimate of how well the Enlighten test can discriminate between individuals with and without cancer, which can then be validated for clinical use in further research.
Ethics and dissemination: this study is sponsored by University Hospital Southampton NHS Foundation Trust and has been approved by the Health Research Authority and Health and Care Research West Midlands (24/WM/0234). Results will be presented at scientific meetings and published in international peer-reviewed journals. Lay summaries of study progress and findings will be published on the Southampton Clinical Trial Unit’s website.
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