Cancer with heavily economic and social burden is the hot point in the field of medical research. Some remarkable achievements have been made; however, the exact mechanisms of tumor initiation and development remain unclear. Cancer is a complex, whole-body disease that involves multiple abnormalities in the levels of DNA, RNA, protein, metabolite and medical imaging. Biological omics including genomics, transcriptomics, proteomics, metabolomics and radiomics aims to systematically understand carcinogenesis in different biological levels, which is driving the shift of cancer research paradigm from single parameter model to multi-parameter systematical model. The rapid development of various omics technologies is driving one to conveniently get multi-omics data, which accelerates predictive, preventive and personalized medicine (PPPM) practice allowing prediction of response with substantially increased accuracy, stratification of particular patients and eventual personalization of medicine. This review article describes the methodology, advances, and clinically relevant outcomes of different “omics” technologies in cancer research, and especially emphasizes the importance and scientific merit of integrating multi-omics in cancer research and clinically relevant outcomes.

How many proteins can be identified in a 2DE gel spot within an analysis of a complex human cancer tissue proteome?Two-dimensional gel electrophoresis (2DE) in proteomics is traditionally assumed to contain only one or two proteins in each 2DE spot. However, 2DE resolution is being complemented by the rapid development of high sensitivity mass spectrometers. Here we compared MALDI-MS, LC-Q-TOF MS and LC-Orbitrap Velos MS for the identification of proteins within one spot. With LC-Orbitrap Velos MS each Coomassie Blue-stained 2DE spot contained an average of at least 42 and 63 proteins/spot in an analysis of a human glioblastoma proteome and a human pituitary adenoma proteome, respectively, if a single gel spot was analyzed. If a pool of three matched gel spots was analyzed this number further increased up to an average of 230 and 118 proteins/spot for glioblastoma and pituitary adenoma proteome, respectively. Multiple proteins per spot confirm the necessity of isotopic labeling in large-scale quantification of different protein species in a proteome. Furthermore, a protein abundance analysis revealed that most of the identified proteins in each analyzed 2DE spot were low-abundance proteins. Many proteins were present in several of the analyzed spots showing the ability of 2DE-MS to separate at the protein species level. Therefore, 2DE coupled with high-sensitivity LC-MS has a clearly higher sensitivity as expected until now to detect, identify and quantify low abundance proteins in a complex human proteome with an estimated resolution of about 500 000 protein species. This clearly exceeds the resolution power of bottom-up LC-MS investigations. Keywords:Protein species / Proteome / Resolution / Tandem mass spectrometry / Two-dimensional gel electrophoresis DOI 10.1002/elps.201700330Additional supporting information may be found in the online version of this article at the publisher's web-site Electrophoresis 2018, 39, 965-980

Genome mutually interacts with internal and external environmental factors to result in different phenome that contains two important elements of proteins and metabolites, which link genome to predictive, preventive and personalized medicine (PPPM) or precision medicine (PM). Proteomic variations are the final presentation of the genomic and transcriptomic variations, and are involved in a wide range of variations including copy number of protein, splicing, post-translational modifications, translocation/re-distribution, spatial conformation, and pathway-network systems. Metabolomic variations are the comprehensive results originated from all types of in vivo substances, and are involved in a wide range of alterations of metabolites generated from sugars, lipids, proteins, and nucleic acids, and metabolic network systems. Currently the studies on variations in proteome and in metabolome are much insufficient in the width and depth in the fields of proteomics and metabolomics. The development of high-throughput, high-sensitivity, and especially high-reproducibility approaches is necessary to maximize the coverage of variations in proteome and in metabolome. The studies of proteomic and metabolomic variations directly result in the discovery of effective biomarkers to clarify molecular mechanisms of a disease, determine reliable therapeutic targets, and benefit precise prediction, diagnosis, and prognosis assessment. It has more important scientific values in PPPM or PM. BIOLOGICAL SIGNIFICANCE.

Abnormal expression of the E3 ubiquitin ligase A20 has been found in some malignant cancers, including hepatocellular carcinoma (HCC). Here, we discovered that A20 is an E3 ubiquitin ligase for phosphofructokinase, liver type (PFKL) in HCC A20 interacts with PFKL and promotes its degradation, therefore inhibiting glycolysis in HCC cell lines. Downregulation of A20 in HCC cells promotes proliferation, migration, and glycolysis, all of which can be inhibited by targeting PFKL with RNA interference. Importantly, A20 is downregulated in advanced HCC tissues and inversely correlated with PFKL expression. Thus, our findings establish A20 as a critical regulator of glycolysis and reveal a novel mechanism for A20 in tumor suppression and PFKL regulation. Given that an increased level of glycolysis is linked with HCC, this study also identifies potential therapeutic targets for HCC treatment.