Abstract Background: The omics era has greatly expanded the repertoire of approaches available to unravel the complexity underpinning human health, with the ability to rapidly characterize genomes, epigenomes, transcriptomes, proteomes and metabolomes from a wide range of sample types. Urogenital cancers, including prostate cancer, is the most prevalent cancer in men. Current early detection methods rely on blood screening of prostate-specific antigen (PSA), however, it has a high rate of false positives, resulting in the search for alternative biomarkers. Urine is an ultra-non-invasive analyte ideal for urogenital cancer detection, including prostate cancer. Cell free RNA/DNA (cfRNA/DNA), along with metabolomics directly from urine, is an ideal candidate for biomarker identification for use in diagnostics, treatment monitoring and tumor tissue of origin prediction. Methods: Here we describe integrated metabolomics and RNA-Seq analysis from a series of prostate cancer affected and control urine samples. First, cfRNA from affected and control samples were isolated using a specialized method with efficient cfRNA recovery rate from urine. The cfRNA was then subjected to highly sensitive RNA-Seq to evaluate a series of prostate cancer biomarkers. The same urine samples were also subjected to metabolite profiling using multiple complementary LC-MS assays to deliver the highest quality untargeted metabolomics data. Both data types were used for integrated multiomics analysis. Results: Urine proves to be an ideal ultra-non-invasive method for biomarker screening and detection. Integrated analysis across multiple data modalities, including transcriptomics and metabolomics, allows for holistic views of pathways and processes that are highly impacted, with increased statistical significance than any one modality alone. Conclusion: Biomarker detection and multiomics analyses are critical to assess individuals in both pre- and post-treatment during therapeutic development and early-stage clinical trials. Urine offers a truly non-invasive approach that, when combined with omics tools, can provide comprehensive insight across urogenital patient cohorts. Citation Format: Bhaven Mehta, Andrea O’Hara, Ethan Stancliffe, Tom Cohen, David Corney, Haythem Latif. Integrated multiomics for deep molecular exploration of prostate cancer from urine abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 7843.
Mehta et al. (2026) studied this question.