Precision Cancer Medicine
Precision Cancer Medicine

Author: Sameek Roychowdhury

Publisher: Springer Nature

Published: 2020-01-02

Total Pages: 196

ISBN-13: 3030236374

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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.

Application of Bioinformatics in Cancers
Application of Bioinformatics in Cancers

Author: Chad Brenner

Publisher: MDPI

Published: 2019-11-20

Total Pages: 418

ISBN-13: 3039217887

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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.

Cancer Evolution
Cancer Evolution

Author: Charles Swanton

Publisher: Perspectives Cshl

Published: 2017

Total Pages: 350

ISBN-13: 9781621821434

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Tumor progression is driven by mutations that confer growth advantages to different subpopulations of cancer cells. As a tumor grows, these subpopulations expand, accumulate new mutations, and are subjected to selective pressures from the environment, including anticancer interventions. This process, termed clonal evolution, can lead to the emergence of therapy-resistant tumors and poses a major challenge for cancer eradication efforts. Written and edited by experts in the field, this collection from Cold Spring Harbor Perspectives in Medicine examines cancer progression as an evolutionary process and explores how this way of looking at cancer may lead to more effective strategies for managing and treating it. The contributors review efforts to characterize the subclonal architecture and dynamics of tumors, understand the roles of chromosomal instability, driver mutations, and mutation order, and determine how cancer cells respond to selective pressures imposed by anticancer agents, immune cells, and other components of the tumor microenvironment. They compare cancer evolution to organismal evolution and describe how ecological theories and mathematical models are being used to understand the complex dynamics between a tumor and its microenvironment during cancer progression. The authors also discuss improved methods to monitor tumor evolution (e.g., liquid biopsies) and the development of more effective strategies for managing and treating cancers (e.g., immunotherapies). This volume will therefore serve as a vital reference for all cancer biologists as well as anyone seeking to improve clinical outcomes for patients with cancer.

Deep Learning for Cancer Diagnosis
Deep Learning for Cancer Diagnosis

Author: Utku Kose

Publisher: Springer Nature

Published: 2020-09-12

Total Pages: 311

ISBN-13: 9811563217

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This book explores various applications of deep learning to the diagnosis of cancer,while also outlining the future face of deep learning-assisted cancer diagnostics. As is commonly known, artificial intelligence has paved the way for countless new solutions in the field of medicine. In this context, deep learning is a recent and remarkable sub-field, which can effectively cope with huge amounts of data and deliver more accurate results. As a vital research area, medical diagnosis is among those in which deep learning-oriented solutions are often employed. Accordingly, the objective of this book is to highlight recent advanced applications of deep learning for diagnosing different types of cancer. The target audience includes scientists, experts, MSc and PhD students, postdocs, and anyone interested in the subjects discussed. The book can be used as a reference work to support courses on artificial intelligence, medical and biomedicaleducation.

Evolution of Translational Omics
Evolution of Translational Omics

Author: Institute of Medicine

Publisher: National Academies Press

Published: 2012-09-13

Total Pages: 354

ISBN-13: 0309224187

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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.

Transcriptome Analysis
Transcriptome Analysis

Author: Miroslav Blumenberg

Publisher: BoD – Books on Demand

Published: 2019-11-20

Total Pages: 110

ISBN-13: 1789843278

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Transcriptome analysis is the study of the transcriptome, of the complete set of RNA transcripts that are produced under specific circumstances, using high-throughput methods. Transcription profiling, which follows total changes in the behavior of a cell, is used throughout diverse areas of biomedical research, including diagnosis of disease, biomarker discovery, risk assessment of new drugs or environmental chemicals, etc. Transcriptome analysis is most commonly used to compare specific pairs of samples, for example, tumor tissue versus its healthy counterpart. In this volume, Dr. Pyo Hong discusses the role of long RNA sequences in transcriptome analysis, Dr. Shinichi describes the next-generation single-cell sequencing technology developed by his team, Dr. Prasanta presents transcriptome analysis applied to rice under various environmental factors, Dr. Xiangyuan addresses the reproductive systems of flowering plants and Dr. Sadovsky compares codon usage in conifers.

Diagnosis and Management of Cholangiocarcinoma
Diagnosis and Management of Cholangiocarcinoma

Author: James H. Tabibian

Publisher: Springer Nature

Published: 2021-05-28

Total Pages: 589

ISBN-13: 3030709361

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This book provides a comprehensive, state-of-the-art overview of cholangiocarcinoma (CCA). The text is structured to effectively present a broad yet concise overview of bile duct cancer, its relevant definitions, classification schemata, clinical management tenets, translational (including molecular and cellular) facets, and future directions. The book features numerous high-yield illustrations and is authored by an eclectic range of renowned experts in various areas of CCA, reflecting the multidisciplinary nature of the field. Filling a critical gap in the field, Diagnosis and Management of Cholangiocarcinoma: A Multidisciplinary Approach is a valuable resource for clinicians and practitioners who treat patients with bile duct cancer.

Molecular Pathology in Cancer Research
Molecular Pathology in Cancer Research

Author: Sunil R. Lakhani

Publisher: Springer

Published: 2017-01-20

Total Pages: 369

ISBN-13: 149396643X

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The aim of the book is to discuss the application of molecular pathology in cancer research, and its contribution in the classification of different tumors and identification of potential molecular targets, as well as how this knowledge may be translated into clinical practice, and the huge impact this field is likely to have in the next 5 to 10 years.

Cancer Cell Lines Part 1
Cancer Cell Lines Part 1

Author: John Masters

Publisher: Springer Science & Business Media

Published: 2006-04-11

Total Pages: 295

ISBN-13: 0306468727

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Continuous cell lines derived from human cancers are the most widely used resource in laboratory-based cancer research. The first 3 volumes of this series on Human Cell Culture are devoted to these cancer cell lines. The chapters in these first 3 volumes have a common aim. Their purpose is to address 3 questions of fundamental importance to the relevance of human cancer cell lines as model systems of each type of cancer: 1. Do the cell lines available accurately represent the clinical presentation? 2. Do the cell lines accurately represent the histopathology of the original tumors? 3. Do the cell lines accurately represent the molecular genetics of this type of cancer? The cancer cell lines available are derived, in most cases, from the more aggressive and advanced cancers. There are few cell lines derived from low grade organ-confined cancers. This gap can be filled with conditionally immortalized human cancer cell lines. We do not know why the success rate for establishing cell lines is so low for some types of cancer and so high for others. The histopathology of the tumor of origin and the extent to which the derived cell line retains the differentiated features of that tumor are critical. The concept that a single cell line derived from a tumor at a particular site is representative of tumors at that site is naïve and misleading.