ABSTRACT
This chapter discusses general concepts on the generation of omics data, along with available strategies for multi-omics data analysis and integration in the context of clinical oncology. Omics technologies offer a new view of biological function and organization at level of different molecular systems. The improvement or development of new omics technologies notably ameliorated personalized medicine, in the prevention or treatment settings, by providing a broad range of information from genetic to metabolic tumor-specific features. The cancer genome carries several somatic changes that include single nucleotide substitutions, small insertions and deletions, structural rearrangements, and copy number variations. Metabolomics data can contribute to an integrative approach to decipher cancer disease facilitating and accelerating the clinical practice. The application of high-throughput technologies for the monitoring of almost all the key players within cells leads to the possibility to investigate cancer samples at different levels. The ultimate goal of the efforts is to discriminate among cancers samples to deliver precision and personalized treatments.
