# Navigating the molecular landscape: integrated multiomics liquid biopsy for biomarker discovery in early detection and monitoring of colorectal cancer

## TL;DR

This review explores how combining multiple molecular signals in liquid biopsies can improve early detection and monitoring of colorectal cancer.

## Contribution

The paper provides a systematic review of multiomics integration strategies for biomarker discovery in colorectal cancer.

## Key findings

- Combining genomic, epigenomic, transcriptomic, proteomic, and metabolomic signals improves early detection and monitoring.
- Multiomics approaches overcome limitations of single-signal detection methods.
- Bioinformatics and AI models enhance biomarker panel performance.

## Abstract

The elevated mortality associated with colorectal cancer is largely due to delayed diagnosis and post-treatment disease recurrence, highlighting the urgent clinical need for molecular markers with exceptional sensitivity and specificity to support early detection and longitudinal disease monitoring. Although conventional liquid biopsy methods targeting single analytes have clinical value, they have inherent limitations in terms of early screening sensitivity, specificity, and tissue-of-origin identification. This review systematically catalogs multiomics biomarker discoveries and summarizes integration strategies for liquid biopsy in colorectal cancer, highlighting how the combination of genomic, epigenomic, transcriptomic, proteomic, and metabolomic signals can improve early detection, MRD monitoring, and treatment guidance. By synthesizing the existing literature, we focus on how this integrated approach overcomes the constraints of single-signal detection, comprehensively delineates the molecular landscape of colorectal cancer, and advances the development of high-performance multiomics biomarker panels. Furthermore, this review explores recent progress in the application of bioinformatics and artificial intelligence-driven cross-omics integration models to optimize biomarker panel performance. In summary, this comprehensive analysis of multiomics integration not only clarifies approaches to molecular marker discovery but also provides a theoretical basis for refining clinical management strategies for colorectal cancer, thereby establishing a framework for precision oncology practices built on continuous molecular surveillance.