Work

AI-enabled multi-omics integration in colorectal cancer: from molecular stratification to clinical translation

Year: 2026

Type: article

Abstract: Colorectal cancer (CRC) remains a heterogeneous disease for which improved molecular stratification is needed across the clinical pathway. Multi-omics technologies have expanded insight into CRC biology, and artificial intelligence (AI) has created new possibilities for integrating molecular, pathological, imaging, and clinical data. This review examines how these approaches are being applied across screening, diagnosis, treatment, and prognosis, with particular emphasis on their clinical relevance and translational limitations. We argue that, despite encouraging advances in biomarker discovery and risk prediction, most current studies remain retrospective and are constrained by heterogeneity of data sources, limited standardisation, weak interpretability, and insufficient external or prospective validation. AI-enabled multi-omics integration has substantial potential in CRC, but meaningful clinical impact will require rigorous validation and implementation frameworks suited to routine care.

Source: Frontiers in Cell and Developmental Biology

DOI: 10.3389/fcell.2026.1797221

Authors: Honghua Su, Tiangui Wang, Chaofan Chen

Institutions: Kunming Municipal Hospital of Traditional Chinese Medicine, Yunnan University of Traditional Chinese Medicine

Language: English

Topic: Colorectal Cancer Treatments and Studies

Subfield: Oncology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,801