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http://hdl.handle.net/1942/49030| Title: | Patient-specific alterations in blood plasma cfRNA profiles enable accurate classification of cancer patients and controls | Authors: | Morlion, Annelien Decruyenaere, Philippe Schoofs, Kathleen Anckaert, Jasper Johns Ramirez, Nickolas Nuytens, Justine Vanden Eynde, Eveline Verniers, Kimberly Everaert, Celine Brusselle, Guy Callens, Steven Haerynck, Filomeen Hemelsoet, Dimitri Hoste, Eric Lambert, Jo Lumen, Nicolaas Offner, Fritz Paemeleire, Koen Smith, Vanessa van den Eynde, Lies Van Dorpe, Jo Vanhaecke, Amber Van Vlierberghe, Hans Mariman, An THAS, Olivier Vandesompele, Jo Mestdagh, Pieter |
Issue Date: | 2026 | Publisher: | SPRINGERNATURE | Source: | Communications Medicine, 6 (1) (Art N° 230) | Abstract: | BackgroundCirculating nucleic acids in blood plasma form an attractive, minimally invasive resource to study human health and disease. In this study, we aimed to identify cell-free RNA alterations that can distinguish cancer patients from cancer-free individuals.MethodsWe first performed mRNA capture sequencing on 266 blood plasma samples from cancer patients and controls, including a discovery set of 208 donors across 25 cancer types and a replication set of 58 donors across three cancer types. We first conducted group-level comparisons and then compared individual patient profiles to a reference control population in a one-versus-many approach. This approach was further evaluated in independent cohorts: a prostate cancer plasma cohort (n = 180), a non-malignant disease plasma cohort (n = 125), a lymphoma plasma cohort (n = 65), and a bladder cancer urine cohort (n = 24), each including both patients and controls.ResultsHere we show that cancer patients exhibit both cancer type-specific and general cell-free RNA alterations. However, differentially abundant RNAs vary widely among patients and across cohorts, hampering robust biomarker identification. By comparing individual patient profiles to control populations, we identify so-called biomarker tail genes, which strongly deviate from controls. The number of these genes per sample distinguishes cancer patients from control samples. Independent cohorts also confirm the potential of this approach.ConclusionsOur findings demonstrate substantial heterogeneity in cell-free RNA alterations among cancer patients and propose that patient-specific changes can be exploited for classification. | Notes: | Mestdagh, P (corresponding author), Univ Ghent, Dept Biomol Med, Ghent, Belgium.; Mestdagh, P (corresponding author), Canc Res Inst Ghent CRIG, OncoRNALab, Ghent, Belgium. pieter.mestdagh@ugent.be |
Document URI: | http://hdl.handle.net/1942/49030 | ISSN: | 2730-664X | e-ISSN: | 2730-664X | DOI: | 10.1038/s43856-026-01507-8 | ISI #: | 001745110700002 | Rights: | The Author(s) 2026. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/bync-nd/4.0/. | Category: | A1 | Type: | Journal Contribution |
| Appears in Collections: | Research publications |
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| s43856-026-01507-8.pdf | Published version | 1.92 MB | Adobe PDF | View/Open |
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