Integrative Multi-omics in Oncology: Bridging Molecular Complexity and Clinical Relevance

Abstract

is a global health concern since it is a multifactorial complex disease, and early detection and novel therapeutic options are necessary for more successful cancer treatment. Cancer affects the entire body and causes several alterations at the molecular level. Biological omics, which includes genomes, transcriptomics, proteomics, metabolomics, and radiomics, seeks to better understand cancer development at these several levels. This strategy shifts cancer research from analyzing single factors to investigating several factors simultaneously. The rapid advancement of omics technologies enables the easy collecting of multi-omics data, hence improving predictive, preventative, and customized treatment. In terms of cancer prognostic prediction, diagnostics, and prevention, as well as cancer therapy and drug responses, this study presented a complete and critical assessment of the systematic method for predictive, preventive, and personalized medicine (PPPM) for cancer. To improve the effectiveness of PPPM for cancer, this review paper looked at multidimensional data from several sources, as well as the use of computational approaches and multidisciplinary omics methodology. This review provided new viewpoints on how both individual and integrated -omics technologies are currently being employed. This review article discusses the methods, achievements, and clinically relevant outcomes of multi-omics technologies in cancer research, with a focus on the necessity and scientific validity of incorporating multi-omics into cancer research and clinically applicable outcomes.