Multi-omics data integration in upper gastrointestinal cancers research: A review of concepts, approaches, and application

Abstract

AbstractUpper gastrointestinal (GI) cancers, including esophageal, gastric, liver, and pancreatic cancers, are a major medical and economic burden worldwide. Despite significant advances in radiotherapy, chemotherapy, and targeted treatments for upper GI cancers in the past decade, a high recurrence rate and poor prognosis are still challenging in upper GI cancer management. This trouble is rooted in the current diagnosis methods and the lack of adequate and reliable diagnostic/prognostic biomarkers. The diagnosis of almost every disease of the upper GI tract still depends on invasive investigations such as endoscopy of the upper GI tract, manometry of the stomach and esophagus, or radiography. Although cancer was considered a single disease in the organ of origin in the past, today, it is accepted that cancer is a heterogeneous disease assuming the same organ of origin. Therefore, to conduct precision/personalized medicine, it seems necessary to have suitable biomarkers to make an accurate diagnosis, appropriate patient classification, prognosis assessment, and drug response in cancers. Systems biology and multi-omics research are strategies adopted to provide genetic and molecular biomarkers in cancer. Toward studying complex biological processes, multi-omics data analysis provides an opportunity to gain a deeper and more comprehensive understanding of cancer development and progression. Multi-omics approaches are new frameworks that integrate omics datasets, including genome, epigenome, transcriptome, proteome, metabolome, and metagenome, on the same set of samples to understand cancer's molecular and clinical characteristics better. Therefore, in this review, we focus on the integrated multi-omics studies conducted on esophageal, gastric, liver, and pancreatic cancers and discuss the results regarding diagnostic and prognostic biomarkers, as well as biomarkers that determine the response to treatment.