Urinary Microbiome as a Biomarker for Melanoma Diagnosis and Response Prediction to Systemic Tumour Therapy

Overview

This study looks at whether the bacteria naturally present in urine (the "urinary microbiome") can help doctors better understand melanoma, a type of skin cancer, and predict how well patients respond to treatment. In recent years, researchers have discovered that bacteria in the body-especially in the gut-can influence cancer development and how patients respond to therapy. However, very little is known about the bacteria in urine and whether they may also play a role in cancer. In this study, patients with melanoma who are starting treatment (such as immunotherapy or targeted therapies) will be asked to provide urine samples and stool samples at several time points, as well as answer questionnaires about their health and lifestyle. A group of people without melanoma will also provide urine samples for comparison. Researchers will analyze these samples to identify the types of bacteria present and how they change over time. They will then investigate whether certain bacterial patterns are linked to better or worse treatment outcomes. The study does not change the medical treatment patients receive. Participation mainly involves providing samples and filling out questionnaires, which represents only a small additional effort. The results of this study may help to identify new, non-invasive biomarkers that could improve early diagnosis and help doctors choose the most effective treatment for melanoma patients in the future

This pilot study investigates the urinary microbiome as a potential non-invasive biomarker in patients with melanoma undergoing systemic therapy. It aims to determine whether microbial composition in urine differs between melanoma patients and matched controls, and whether it is associated with and predictive of response to immune checkpoint inhibition or targeted therapy. In a prospective observational matched cohort design, melanoma patients initiating systemic therapy and control participants are recruited. Patients provide urine and stool samples at baseline and at two follow-up time points during therapy, along with clinical and lifestyle data, while controls provide a single urine sample and questionnaire data. Microbiome profiling is performed using 16S rRNA gene sequencing, followed by bioinformatic and statistical analyses to assess microbial diversity, composition, and associations with clinical variables. The study evaluates differences in urinary and gut microbiome composition between patients and controls, longitudinal changes during therapy, and associations with treatment response. Statistical approaches include matched analyses, correlation and regression models, and receiver operating characteristic analyses to assess the predictive potential of microbiome-derived biomarkers. This study is expected to provide first insights into the role of the urinary microbiome in melanoma and its potential utility as a biomarker for diagnosis and prediction of therapeutic response, contributing to the development of personalized treatment strategies.