Comprehensive Landscape of Diagnostic, Prognostic and Predictive Biomarkers in Colorectal Cancer: From Genomics to Multi-Omics Integration in Precision Medicine.
1/5 보강
Colorectal cancer (CRC) remains one of the leading causes of cancer-related morbidity and mortality worldwide.
APA
Agüera-Sánchez A, Peña-Ros E, et al. (2026). Comprehensive Landscape of Diagnostic, Prognostic and Predictive Biomarkers in Colorectal Cancer: From Genomics to Multi-Omics Integration in Precision Medicine.. Journal of personalized medicine, 16(1). https://doi.org/10.3390/jpm16010048
MLA
Agüera-Sánchez A, et al.. "Comprehensive Landscape of Diagnostic, Prognostic and Predictive Biomarkers in Colorectal Cancer: From Genomics to Multi-Omics Integration in Precision Medicine.." Journal of personalized medicine, vol. 16, no. 1, 2026.
PMID
41590540 ↗
Abstract 한글 요약
Colorectal cancer (CRC) remains one of the leading causes of cancer-related morbidity and mortality worldwide. Despite advances in screening and therapeutic strategies, early detection and individualized treatment remain major challenges. In recent years, an expanding repertoire of biomarkers has emerged, spanning genomic, transcriptomic, proteomic, and metabolomic signatures. Epigenetic features, such as DNA methylation panels, as well as non-coding RNAs and the gut microbiome, hold potential not only for improving early diagnosis but also for refining prognosis and predicting therapeutic responses within the framework of precision oncology. This narrative review provides an updated, integrative overview of CRC diagnostic, prognostic, and predictive biomarkers. We distinguish established markers already in clinical practice, such as and mutations, amplification, microsatellite instability/mismatch repair deficiency (MSI/dMMR), and widely investigated molecular alterations including mutations and immune-checkpoint-related markers, from novel biomarkers with growing translational potential. We also discuss the implementation challenges of these biomarkers in clinical practice, including issues related to validation, standardization, and cost-effectiveness, as well as the multi-modal approach for the development of composite diagnostic panels.
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