13 General Introduction For single oncogene-driven tumors, such as malignant melanoma with a BRAF V600E mutation, genomics-based treatment is valuable approach9. Unfortunately, not all tumors harbor a clear genomic diver mutation. Some may be driven by a multitude of aberrantly activated kinase signaling pathways, such as renal cell carcinoma27. In these tumor types, a functional pathway analysis may be a more promising approach28,29. (Phospho)proteomics based on liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) may offer insight in aberrantly activated kinase signaling pathways and potential drug targets through the global analysis of phosphorylated proteins. In particular, phosphotyrosine-(pTyr)-phosphoproteomics provides an opportunity for the identification of patient subgroups likely to benefit from tyrosine kinase inhibitors (TKI’s)30,31. In the past decade, advances in technology have enabled us to generate large-scale molecular data, allowing characterization of complex biological systems in great detail. For quite some time, research efforts have focused on unidimensional approaches to discovery of clinically useful biomarkers, i.e. genomics, transcriptomics or proteomics analysis32. The new fields of research created by these efforts are often referred to as “omics”, a field of study that focusses on large-scale data/information to understand biology33. The application of these omics techniques have enabled major improvements in the understanding of cancer biology, the identification of biomarkers and the personalized treatment of patients with cancer. The integrated use of multiple omics may hold an opportunity for further improvement of our knowledge of biological processes. This multi-omics approach is suggested by numerous recent reviews to greatly benefit the field of precision oncology34-36. To date, only limited examples of truly multi-omics studies are available32. Most so-called multi-omics analyses only describe one omics approach, complemented with a limited amount of data from additional techniques, often obtained through targeted analyses32. Given the fact that different omics datasets do not overlap extensively and the correlation between data sets is extremely limited, it is likely that different omics approaches assess disparate pieces of the puzzle of the complex pathophysiology of cancer development and progression. True multi-omics analysis of tissues obtained from patients with cancer is still in its infancy. Nevertheless, recent advances in each of the omics techniques bring the clinical application of multi-omics in the standard care for patients with cancer closer by the day. PRE-ANALYTICAL REQUIREMENTS TO ENABLE MULTI-OMICS ANALYSIS Development and wider implementation of multi-omics in clinical studies faces many challenges32. One of the most critical hurdles is tissue availability. A true multi-omics analysis requires multiple techniques to be performed on a tissue of interest. To allow for optimal correlation between these types of omics, they are ideally performed on the same piece of tissue to minimize the effect of intra-and inter-patient heterogeneity. Each of the omics techniques has its own minimally required quantity, often expressed as, for example, minimal tumor cell percentage, nanograms of DNA or RNA, or milligrams of protein. Clinical tissue samples, however, 1
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