Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.

Breast cancer is the most common cancer in females that accounts for highest cancer specific deaths worldwide. In the last few decades research has proven that breast cancer can be treated if diagnosed at early stages and proper therapeutic strategy is adopted. Omics-based recent approaches have unveiled the molecular mechanism behind the breast tumorigenesis and aid in identification of next-generation molecular markers for early diagnosis, prognosis and even the effective targeted therapy. Significant development has taken place in the field of omics in breast cancer in the last decade. The most promising omics approaches and their outcomes in breast cancer have been presented in this book for the first time. The book covers omics technologies and budding fields such as breast cancer miRNA, lipidomics, epigenomics, proteomics, nutrigenomics, stem cell, pharmacogenomics and personalized medicine and many more along with conventional topics such as breast cancer management etc. It is a research-based reference book useful for clinician-scientists, researchers, geneticists and health care industries involved in various aspects of breast cancer. The book will also be useful for students of biomedicine, pathology and pharmacy.

This book concisely describes the role of omics in precision medicine for cancer therapies. It outlines our current understanding of cancer genomics, shares insights into the process of oncogenesis, and discusses emerging technologies and clinical applications of cancer genomics in prognosis and precision-medicine treatment strategies. It then elaborates on recent advances concerning transcriptomics and translational genomics in cancer diagnosis, clinical applications, and personalized medicine in oncology. Importantly, it also explains the importance of high-performance analytics, predictive modeling, and system biology in cancer research. Lastly, the book discusses current and potential future applications of pharmacogenomics in clinical cancer therapy and cancer drug development.

This book is a concerted effort to put together the rapidly growing facets of biological data. It provides a platform for the readers to think about integrative approaches to solve complex biological problems. This fundamental book deals with the simplest concepts of omics to recent advancements in the field. The content is divided into seven chapters that provide insight into various omics approaches, omics technologies, and its applications. Each chapter delves into different molecular scales: genomics, transcriptomics, proteomics, and metabolomics. Further to provide a holistic view a chapter detailing microbiome has been included in the book. The sub-sections in the chapters is dedicated to introducing the various analytical tools such as next generation sequencing, chromatin immunoprecipitation, mass spectrometry, peptide mass fingerprinting, RNA Seq and NMR spectroscopy. It entails a chapter focused on the bioinformatics resources for analysis of the omics data. In summary, this comprehensive book emphasizes the recent advancements in the study of biomolecules spanning from DNA to metabolites.

Being a complex disease that affects millions of people world over, cancer research has assumed great significance. Translational cancer research transforms scientific discoveries in the laboratory into clinical application to reduce incidence of cancer, morbidity and mortality. On the other hand, personalized medicine in cancer is the concept that selection of a treatment should be tailored according to the individual patient’s specific genomic characteristics, including mutations, chromosomal aberrations, protein interactions, and SNPs, and even more, taking into account the inmume system, the metabolism and maybe in the next future also the microbiome.

This collection of 25 research papers comprised of 22 original articles and 3 reviews is brought together from international leaders in bioinformatics and biostatistics. The collection highlights recent computational advances that improve the ability to analyze highly complex data sets to identify factors critical to cancer biology. Novel deep learning algorithms represent an emerging and highly valuable approach for collecting, characterizing and predicting clinical outcomes data. The collection highlights several of these approaches that are likely to become the foundation of research and clinical practice in the future. In fact, many of these technologies reveal new insights about basic cancer mechanisms by integrating data sets and structures that were previously immiscible. Accordingly, the series presented here bring forward a wide range of artificial intelligence approaches and statistical methods that can be applied to imaging and genomics data sets to identify previously unrecognized features that are critical for cancer. Our hope is that these articles will serve as a foundation for future research as the field of cancer biology transitions to integrating electronic health record, imaging, genomics and other complex datasets in order to develop new strategies that improve the overall health of individual patients.

Introduces readers to the state of the art of omics platforms and all aspects of omics approaches for clinical applications This book presents different high throughput omics platforms used to analyze tissue, plasma, and urine. The reader is introduced to state of the art analytical approaches (sample preparation and instrumentation) related to proteomics, peptidomics, transcriptomics, and metabolomics. In addition, the book highlights innovative approaches using bioinformatics, urine miRNAs, and MALDI tissue imaging in the context of clinical applications. Particular emphasis is put on integration of data generated from these different platforms in order to uncover the molecular landscape of diseases. The relevance of each approach to the clinical setting is explained and future applications for patient monitoring or treatment are discussed. Integration of omics Approaches and Systems Biology for Clinical Applications presents an overview of state of the art omics techniques. These methods are employed in order to obtain the comprehensive molecular profile of biological specimens. In addition, computational tools are used for organizing and integrating these multi-source data towards developing molecular models that reflect the pathophysiology of diseases. Investigation of chronic kidney disease (CKD) and bladder cancer are used as test cases. These represent multi-factorial, highly heterogeneous diseases, and are among the most significant health issues in developed countries with a rapidly aging population. The book presents novel insights on CKD and bladder cancer obtained by omics data integration as an example of the application of systems biology in the clinical setting. Describes a range of state of the art omics analytical platforms Covers all aspects of the systems biology approach—from sample preparation to data integration and bioinformatics analysis Contains specific examples of omics methods applied in the investigation of human diseases (Chronic Kidney Disease, Bladder Cancer) Integration of omics Approaches and Systems Biology for Clinical Applications will appeal to a wide spectrum of scientists including biologists, biotechnologists, biochemists, biophysicists, and bioinformaticians working on the different molecular platforms. It is also an excellent text for students interested in these fields.