Latest generation sequencing revolutionizes the fields of cancer research and oncology. This follow-up volume focuses more extensively on single cell sequencing of cancer and trials in drug resistance. Another exciting feature is the bioinformatics tools given, that can be used on cancer genome studies. Scientists around the world are attempting to find the root cause of cancer. A reasonable cancer treatment plan and potential cure is more optimistic now with the unfolding of the cancer genome. The collective knowledge of how to leverage next generation sequencing in cancer research is paving the way. The important information provided in this volume will move the field forward in developing novel targeted cancer therapies.
This volume provides an interdisciplinary perspective of applying Next Generation Sequencing (NGS) technology to cancer research. It aims to systematically introduce the concept of NGS, a variety of NGS platforms and their practical implications in cancer biology.This unique and comprehensive text will integrate the unprecedented NGS technology into various cancer research projects as opposed to most books which offer a detailed description of the technology. This volume will present true experimental results with concrete data processing pipelines, discuss the bottleneck of each platform for real project in cancer research. In additional, single cancer cell sequencing as the proof of concept will be introduced in this book, along with cutting-edge information provided will help the intended audience to develop a comprehensive understanding of the NGS technology and practical whole genome sequencing data analysis and rapidly translate into their own research, specifically in the field of cancer biology.
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.
Clinical Applications for Next Generation Sequencing provides readers with an outstanding postgraduate resource to learn about the translational use of NGS in clinical environments. Rooted in both medical genetics and clinical medicine, the book fills the gap between state-of-the-art technology and evidence-based practice, providing an educational opportunity for users to advance patient care by transferring NGS to the needs of real-world patients. The book builds an interface between genetic laboratory staff and clinical health workers to not only improve communication, but also strengthen cooperation. Users will find valuable tactics they can use to build a systematic framework for understanding the role of NGS testing in both common and rare diseases and conditions, from prenatal care, like chromosomal abnormalities, up to advanced age problems like dementia. Fills the gap between state-of-the-art technology and evidence-based practice Provides an educational opportunity which advances patient care through the transfer of NGS to real-world patient assessment Promotes a practical tool that clinicians can apply directly to patient care Includes a systematic framework for understanding the role of NGS testing in many common and rare diseases Presents evidence regarding the important role of NGS in current diagnostic strategies
Cancer results from accumulated mutations in the genome. Sequencing is an accurate method to detect mutations. Second-generation sequencing technology, commonly referred to as next-generation sequencing technology, enables rapid, efficient and affordable DNA sequencing, and is transforming the scale and scope of cancer research. The technology is sufficiently flexible and affordable to allow sequencing of many cancer genomes, and thus facilitates both sequencing of samples from large patient cohorts and during disease progression in individual cancer patients. The high depths of redundant sequence coverage that can be obtained using some second-generation sequencing technologies, along with sequencing reads amplified from single DNA molecules, facilitate detection of subclones of cells in tumors. Large-scale genome sequencing of hundreds or even thousands of cancer samples is being conducted by several groups that aim to identify and characterize cancer driver mutations. Goals of such work, previously infeasible with Sanger sequencing instruments, are to use this information to improve cancer prognosis, diagnosis and therapeutic decision-making. The speed of data analysis is rate limiting, and investigators are struggling to accommodate and interpret the data deluge produced by second-generation technologies. In this chapter, we discuss cancer properties that are revealed by sequencing and the implication of such properties in experimental design and data interpretation. We describe past, current and upcoming sequencing technologies and the application of second-generation sequencing technologies in cancer genomics. Finally, we discuss the impact of second-generation sequencing technology in shaping personalized medicine.
Genomic sequencing technologies have augmented the classification of cancer beyond tissue of origin and towards a molecular taxonomy of cancer. This has created opportunities to guide treatment decisions for individual patients with cancer based on their cancer’s unique molecular characteristics, also known as precision cancer medicine. The purpose of this text will be to describe the contribution and need for multiple disciplines working together to deliver precision cancer medicine. This entails a multi-disciplinary approach across fields including molecular pathology, computational biology, clinical oncology, cancer biology, drug development, genetics, immunology, and bioethics. Thus, we have outlined a current text on each of these fields as they work together to overcome various challenges and create opportunities to deliver precision cancer medicine. As trainees and junior faculty enter their respective fields, this text will provide a framework for understanding the role and responsibility for each specialist to contribute to this team science approach.
Next generation sequencing (NGS) has surpassed the traditional Sanger sequencing method to become the main choice for large-scale, genome-wide sequencing studies with ultra-high-throughput production and a huge reduction in costs. The NGS technologies have had enormous impact on the studies of structural and functional genomics in all the life sciences. In this book, Next Generation Sequencing Advances, Applications and Challenges, the sixteen chapters written by experts cover various aspects of NGS including genomics, transcriptomics and methylomics, the sequencing platforms, and the bioinformatics challenges in processing and analysing huge amounts of sequencing data. Following an overview of the evolution of NGS in the brave new world of omics, the book examines the advances and challenges of NGS applications in basic and applied research on microorganisms, agricultural plants and humans. This book is of value to all who are interested in DNA sequencing and bioinformatics across all fields of the life sciences.
Next Generation Sequencing (NGS) is the latest high throughput technology to revolutionize genomic research. NGS generates massive genomic datasets that play a key role in the big data phenomenon that surrounds us today. To extract signals from high-dimensional NGS data and make valid statistical inferences and predictions, novel data analytic and statistical techniques are needed. This book contains 20 chapters written by prominent statisticians working with NGS data. The topics range from basic preprocessing and analysis with NGS data to more complex genomic applications such as copy number variation and isoform expression detection. Research statisticians who want to learn about this growing and exciting area will find this book useful. In addition, many chapters from this book could be included in graduate-level classes in statistical bioinformatics for training future biostatisticians who will be expected to deal with genomic data in basic biomedical research, genomic clinical trials and personalized medicine. About the editors: Somnath Datta is Professor and Vice Chair of Bioinformatics and Biostatistics at the University of Louisville. He is Fellow of the American Statistical Association, Fellow of the Institute of Mathematical Statistics and Elected Member of the International Statistical Institute. He has contributed to numerous research areas in Statistics, Biostatistics and Bioinformatics. Dan Nettleton is Professor and Laurence H. Baker Endowed Chair of Biological Statistics in the Department of Statistics at Iowa State University. He is Fellow of the American Statistical Association and has published research on a variety of topics in statistics, biology and bioinformatics.
Cancer Genomics for the Clinician is a practical guide to cancer genomics and its application to cancer diagnosis and care. The book begins with a brief overview of the various types of genetic alterations that are encountered in cancer, followed by accessible and applicable information on next generation sequencing technology and bioinformatics; tumor heterogeneity; whole genome, exome, and transcriptome sequencing; epigenomics; and data analysis and interpretation. Each chapter provides essential explanations of concepts, terminology, and methods. Also included are tips for interpreting and analyzing molecular data, as well as a discussion of molecular predictors for targeted therapies covering hematologic malignancies and solid tumors. The final chapter explains the use of FDA-approved genomic-based targeted therapies for breast cancer, lung cancer, sarcomas, gastrointestinal cancers, urologic cancers, head and neck cancer, thyroid cancer, and many more. Assembled in an accessible format specifically designed for the non-expert, this book provides the clinical oncologist, early career practitioner, and trainee with an essential understanding of the molecular and genetic basis of cancer and the clinical aspects that have led to advancements in diagnosis and treatment. With this resource, physicians and trainees will increase their breadth of knowledge and be better equipped to educate patients and families who want to know more about their genetic predispositions to cancer and the targeted therapies that could be considered and prescribed. Key Features: Describes how cancer genomics and next generation sequencing informs cancer screening, risk factors, therapeutic options, and clinical management across cancer types Explains what mutations are, what tests are needed, and how to interpret the results Provides information on FDA-approved targeted therapies that are being used in the clinic Covers different sequencing platforms and technologies and how they perform in research settings Includes access to the fully searchable eBook
