Next-generation biomarkers for cancer-associated thrombosis prediction: the role of non-genomic-omics

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.