Immunotherapy and Cancer: The Multi-Omics Perspective.

Immunotherapies have revolutionized cancer treatment approaches. Because not all patients respond positively to immune therapeutic agents, it represents a challenge for scientists who strive to understand the mechanisms behind such resistance. In-depth exploration of tumor biology, using novel technologies such as omics science, can help decode the role of the tumor immune microenvironment (TIME) in producing a response to the immune blockade strategies. It can also help to identify biomarkers for patient stratification and personalized treatment. This review aims to explore these new models and highlight their possible pivotal role in changing clinical practice.

Cardiovascular Biomarkers in Cardio-Oncology: Antineoplastic Drug Cardiotoxicity and Beyond.

Serum biomarkers represent a reproducible, sensitive, minimally invasive and inexpensive method to explore possible adverse cardiovascular effects of antineoplastic treatments. They are useful tools in risk stratification, the early detection of cardiotoxicity and the follow-up and prognostic assessment of cancer patients. In this literature review, we aim at describing the current state of knowledge on the meaning and the usefulness of cardiovascular biomarkers in patients with cancer; analyzing the intricate relationship between cancer and cardiovascular disease (especially HF) and how this affects cardiovascular and tumor biomarkers; exploring the role of cardiovascular biomarkers in the risk stratification and in the identification of chemotherapy-induced cardiotoxicity; and providing a summary of the novel potential biomarkers in this clinical setting.

Omics sciences and precision medicine in melanoma.

Background: This article provides an overview of the application of omics sciences in melanoma research. The name omics sciences refers to the large-scale analysis of biological molecules like DNA, RNA, proteins, and metabolites. Methods: In the course of this review, we have adopted a focu-sed research strategy, meticulously selecting the most pertinent and emblematic articles related to the topic. Our methodology included a systematic examination of the scientific literature to guarantee a thorough and precise synthesis of the existing sources. Results: With the advent of high-throughput technologies, omics have become an essential tool for understanding the complexity of melanoma. In this article, we discuss the different omics approaches used in melanoma research, including genomics, transcriptomics, proteomics, and metabolomics. We also highlight the major findings and insights gained from these studies, including the identification of new therapeutic targets and the development of biomarkers for diagnosis and prognosis. Finally, we discuss the challenges and future directions in omics-based melanoma research, including the integration of multiple omics data and the development of personalized medicine approaches. Conclusions: Overall, this article emphasizes the importance of omics science in advancing our understanding of melanoma and its potential for improving patient outcomes.

Big (Bio)Chemical Data Mining Using Chemometric Methods: A Need for Chemists.

This Review summarizes how big (bio)chemical data (BBCD) can be analyzed with multivariate chemometric methods and highlights some of the important challenges faced by modern analytical researches. Here, the potential of chemometric methods to solve BBCD problems that are being encountered in chromatographic, spectroscopic and hyperspectral imaging measurements will be discussed, with an emphasis on their applications to omics sciences. In addition, insights and perspectives on how to address the analysis of BBCD are provided along with a discussion of the procedures necessary to obtain more reliable qualitative and quantitative results. In this Review, the importance of "big data" and of their relevance to (bio)chemistry are first discussed. Thereafter, analytical tools which can produce BBCD are presented as well as the theoretical background of chemometric methods and their limitations when they are applied to BBCD. Finally, the importance of chemometric methods for the analysis of BBCD in different chemical disciplines is highlighted with some examples. In this work, we have tried to cover many of the current applications of big data analysis in the (bio)chemistry field.

An Updated Taxonomy and a Graphical Summary Tool for Optimal Classification and Comprehension of Omics Research.

The volume of publications and the type of research approaches used in omics system sciences are vast and continue to expand rapidly. This increased complexity and heterogeneity of omics data are challenging data extraction, sensemaking, analyses, knowledge translation, and interpretation. An extended and dynamic taxonomy for the classification and summary of omics studies are essential. We present an updated taxonomy for classification of omics research studies based on four criteria: (1) type and number of genomic loci in a research study, (2) number of species and biological samples, (3) the type of omics technology (e.g., genomics, transcriptomics, and proteomics) and omics technology application type (e.g., pharmacogenomics and nutrigenomics), and (4) phenotypes. In addition, we present a graphical summary approach that enables the researchers to define the main characteristics of their study in a single figure, and offers the readers to rapidly grasp the published study and omics data. We searched the PubMed and the Web of Science from 09/2002 to 02/2018, including research and review articles, and identified 90 scientific publications. We propose a call toward omics studies' standardization for reporting in scientific literature. We anticipate the proposed classification scheme will usefully contribute to improved classification of published reports in genomics and other omics fields, and help data extraction from publications for future multiomics data integration.

The Gene-Centric Content Management System and Its Application for Cognitive Proteomics.

The Human Proteome Project is moving into the next phase of creating and/or reconsidering the functional annotations of proteins using the chromosome-centric paradigm. This challenge cannot be solved exclusively using automated means, but rather requires human intelligence for interpreting the combined data. To foster the integration between human cognition and post-genome array a number of specific tools were recently developed, among them CAPER, GenomewidePDB, and The Proteome Browser (TPB). For the purpose of tackling the task of protein functional annotating the Gene-Centric Content Management System (GenoCMS) was expanded with new features. The goal was to enable bioinformaticans to develop self-made applications and to position these applets within the generalized informational canvas supported by GenoCMS. We report the results of GenoCMS-enabled integration of the concordant informational flows in the chromosome-centric framework of the human chromosome 18 project. The workflow described in the article can be scaled to other human chromosomes, and also supplemented with new tracks created by the user. The GenoCMS is an example of a project-oriented informational system, which are important for public data sharing.

Short overview on metabolomics approach to study pathophysiology of oxidative stress in cancer.

Association of oxidative stress with carcinogenesis is well known, but not understood well, as is pathophysiology of oxidative stress generated during different types of anti-cancer treatments. Moreover, recent findings indicate that cancer associated lipid peroxidation might eventually help defending adjacent nonmalignant cells from cancer invasion. Therefore, untargeted metabolomics studies designed for advanced translational and clinical studies are needed to understand the existing paradoxes in oncology, including those related to controversial usage of antioxidants aiming to prevent or treat cancer. In this short review we have tried to put emphasis on the importance of pathophysiology of oxidative stress and lipid peroxidation in cancer development in relation to metabolic adaptation of particular types of cancer allowing us to conclude that adaptation to oxidative stress is one of the main driving forces of cancer pathophysiology. With the help of metabolomics many novel findings are being achieved thus encouraging further scientific breakthroughs. Combined with targeted qualitative and quantitative methods, especially immunochemistry, further research might reveal bio-signatures of individual patients and respective malignant diseases, leading to individualized treatment approach, according to the concepts of modern integrative medicine.

Integration of cardiac proteome biology and medicine by a specialized knowledgebase.

RATIONALE: Omics sciences enable a systems-level perspective in characterizing cardiovascular biology. Integration of diverse proteomics data via a computational strategy will catalyze the assembly of contextualized knowledge, foster discoveries through multidisciplinary investigations, and minimize unnecessary redundancy in research efforts. OBJECTIVE: The goal of this project is to develop a consolidated cardiac proteome knowledgebase with novel bioinformatics pipeline and Web portals, thereby serving as a new resource to advance cardiovascular biology and medicine. METHODS AND RESULTS: We created Cardiac Organellar Protein Atlas Knowledgebase (COPaKB; www.HeartProteome.org), a centralized platform of high-quality cardiac proteomic data, bioinformatics tools, and relevant cardiovascular phenotypes. Currently, COPaKB features 8 organellar modules, comprising 4203 LC-MS/MS experiments from human, mouse, drosophila, and Caenorhabditis elegans, as well as expression images of 10,924 proteins in human myocardium. In addition, the Java-coded bioinformatics tools provided by COPaKB enable cardiovascular investigators in all disciplines to retrieve and analyze pertinent organellar protein properties of interest. CONCLUSIONS: COPaKB provides an innovative and interactive resource that connects research interests with the new biological discoveries in protein sciences. With an array of intuitive tools in this unified Web server, nonproteomics investigators can conveniently collaborate with proteomics specialists to dissect the molecular signatures of cardiovascular phenotypes.