LAUSR

Simple Summary The incidence of endometrial cancer has increased across the western world, and with it the need for fast and efficient diagnostic methods. This study explores the potential of implementing a non-invasive test for the early detection of endometrial cancer. The concept of this new diagnostic alternative involves the analysis of carefully collected urine samples from female patients, together with infrared spectroscopy and statistical methods that allow the identification and prediction of the samples. Interestingly, we were able to obtain some of the spectral biomarkers that may be useful in the detection of endometrial cancer, such as spectral bands of DNA, or phenyl group vibrations that have been found to be highly linked to cancer. Additionally, the predictive values rise to over 90% specificity and sensitivity, making this technique an excellent technique to be explored in clinical studies, now that biomarkers have been identified in uncontaminated urine. These promising results in predicting and discriminating classes of cancer, suggest that this technique should be evaluated in pragmatic studies in cancer triage clinics. Abstract Current triage for women with post-menopausal bleeding (PMB) to diagnose endometrial cancer rely on specialist referral for intimate tests to sequentially image, visualise and sample the endometrium. A point-of-care non-invasive triage tool with an instant readout could provide immediate reassurance for low-risk symptomatic women, whilst fast-tracking high-risk women for urgent intrauterine investigations. This study assessed the potential for infrared (IR) spectroscopy and attenuated total reflection (ATR) technology coupled with chemometric analysis of the resulting spectra for endometrial cancer detection in urine samples. Standardised urine collection and processing protocols were developed to ensure spectroscopic differences between cases and controls reflected cancer status. Urine spectroscopy distinguished endometrial cancer (n = 109) from benign gynaecological conditions (n = 110) with a sensitivity of 98% and specificity of 97%. If confirmed in subsequent low prevalence studies embedded in PMB clinics, this novel endometrial cancer detection tool could transform clinical practice by accurately selecting women with malignant pathology for urgent diagnostic work up whilst safely reassuring those without.