Published online Jul 27, 2025. doi: 10.4240/wjgs.v17.i7.107110
Revised: April 24, 2025
Accepted: May 28, 2025
Published online: July 27, 2025
Processing time: 130 Days and 7.9 Hours
Gastrointestinal (GI) malignancies, including gastric and colorectal cancers, remain one of the primary contributors to cancer-related illness and death globally. Despite the availability of conventional diagnostic tools, early detection and personalized treatment remain significant clinical challenges. Integrated multi-omics methods encompassing genomic, transcriptomic, proteomic, metabo
To investigate the application of multi-omics approaches in the early detection, risk stratification, treatment optimization, and biomarker discovery of GI malignancies.
The systematic review process was conducted in accordance with the PRISMA 2020 guidelines. Five databases, PubMed, ScienceDirect, Scopus, ProQuest, and Web of Science, were searched for studies published in English from 2015 onwards. Eligible studies involved human subjects and focused on multi-omics integration in GI cancers, including biomarker identification, tumor microenvironment analysis, tumor heterogeneity, organoid modeling, and artificial intelligence (AI)-driven analytics. Data extraction included study characteristics, omics modalities, clinical applications, and evaluation of study quality conducted with the Cochrane risk of bias 2.0 instrument.
A total of 17196 initially identified articles, 20 met the inclusion criteria. The findings highlight the superiority of multi-omics platforms over traditional biomarkers (e.g., carcinoembryonic antigen and carbohydrate antigen 19-9 in detecting early stage GI cancers. Key applications include the identification of circulating tumor DNA, extra
Multi-omics approaches offer significant advancements in the early diagnosis, prognostic evaluation, and personalized treatment of GI malignancies. Their integration with AI analytics, organoid biobanking, and microbiota modulation provides a pathway for precision oncology research.
Core Tip: Gastrointestinal malignancies present substantial diagnostic and therapeutic challenges due to their molecular complexity. This systematic review highlights how comprehensive omics strategies incorporating genomic, transcriptomic, proteomic, and metabolomic data and epigenomics, integrated with machine learning and artificial intelligence, can revolutionize precision oncology. These strategies enable early detection through biomarkers like circulating tumor DNA and extracellular vesicles, enhance risk stratification, and uncover mechanisms of drug resistance and tumor heterogeneity, paving the way for individualized gastrointestinal cancer therapies.