Next-generation biomarkers for cancer-associated thrombosis prediction: the role of non-genomic-omics
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Authors
Prediction of cancer-associated thrombosis (CAT) remains a major clinical challenge. Although genomic data and clinic-genetic scores have advanced understanding, they do not explain all inter-individual variability in CAT risk. Non-genomic omics, including proteomics, transcriptomics and epigenomics, capture complementary, dynamic biological information that can improve risk stratification. In summary, genomics contributes one piece of a much larger puzzle, necessary, informative, but fundamentally insufficient when used alone to understand, predict or manage CAT. This review synthesizes recent evidence on these non-genomic–omics for CAT prediction, highlights current limitations (validation, standardization, causal inference) and outlines priorities for translational development and clinical validation.
Supporting Agencies
This work was supported by Networking Biomedical Research Centre in the subject areas of Rares Diseases (CIBERER CB23/07/00042) initiatives of Instituto de Investigación Carlos III (ISCIII), 2021 SGR00830 from Generalitat de Catalunya, the Spanish Government Instituto de Salud Carlos III and Fondo de Investigación Sanitaria (ISCIII-FIS) (PI24/00682), CERCA Programme/Generalitat de Catalunya, and the nonprofit association Activa’TT por la Salud.How to Cite

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