Unveiling the Tumor Microenvironment by Machine Learning to Develop New Immunotherapeutic Strategies (Volume I.B)
Unveiling the Tumor Microenvironment by Machine Learning to Develop New Immunotherapeutic Strategies (Volume I.B)

Author: Nan Zhang

Publisher: Frontiers Media SA

Published: 2023-10-24

Total Pages: 297

ISBN-13: 2832536301

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The tumor microenvironment (TME) plays a critical role in tumor proliferation, progression, and therapeutic responses. TME is a complex network of cancer cells, stromal cells, and, most importantly, infiltrating immune cells. Cancer cells regulate numerous biological functions through direct or indirect interaction with TME components. Emerging evidence suggests that TME crucially influences the response to both chemotherapy and immunotherapy. As scientific research has entered the big data era with the fast development of high-throughput sequencing technologies, machine learning has been gradually widely applied to extract important knowledge from big data bioinformatics. Thus, characterizing the TME landscape in cancer and identifying different immune-related TME phenotypes using machine learning-based bioinformatics analyses, in vitro experiments, and in vivo experiments are of great interest and significance.

Unveiling the Tumor Microenvironment by Machine Learning to Develop New Immunotherapeutic Strategies (Volume I.A)
Unveiling the Tumor Microenvironment by Machine Learning to Develop New Immunotherapeutic Strategies (Volume I.A)

Author: Nan Zhang

Publisher: Frontiers Media SA

Published: 2023-10-24

Total Pages: 295

ISBN-13: 2832533779

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The tumor microenvironment (TME) plays a critical role in tumor proliferation, progression, and therapeutic responses. TME is a complex network of cancer cells, stromal cells, and, most importantly, infiltrating immune cells. Cancer cells regulate numerous biological functions through direct or indirect interaction with TME components. Emerging evidence suggests that TME crucially influences the response to both chemotherapy and immunotherapy. As scientific research has entered the big data era with the fast development of high-throughput sequencing technologies, machine learning has been gradually widely applied to extract important knowledge from big data bioinformatics. Thus, characterizing the TME landscape in cancer and identifying different immune-related TME phenotypes using machine learning-based bioinformatics analyses, in vitro experiments, and in vivo experiments are of great interest and significance.

The Drug Development Paradigm in Oncology
The Drug Development Paradigm in Oncology

Author: National Academies of Sciences, Engineering, and Medicine

Publisher: National Academies Press

Published: 2018-02-12

Total Pages: 145

ISBN-13: 0309457971

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Advances in cancer research have led to an improved understanding of the molecular mechanisms underpinning the development of cancer and how the immune system responds to cancer. This influx of research has led to an increasing number and variety of therapies in the drug development pipeline, including targeted therapies and associated biomarker tests that can select which patients are most likely to respond, and immunotherapies that harness the body's immune system to destroy cancer cells. Compared with standard chemotherapies, these new cancer therapies may demonstrate evidence of benefit and clearer distinctions between efficacy and toxicity at an earlier stage of development. However, there is a concern that the traditional processes for cancer drug development, evaluation, and regulatory approval could impede or delay the use of these promising cancer treatments in clinical practice. This has led to a number of effortsâ€"by patient advocates, the pharmaceutical industry, and the Food and Drug Administration (FDA)â€"to accelerate the review of promising new cancer therapies, especially for cancers that currently lack effective treatments. However, generating the necessary data to confirm safety and efficacy during expedited drug development programs can present a unique set of challenges and opportunities. To explore this new landscape in cancer drug development, the National Academies of Sciences, Engineering, and Medicine developed a workshop held in December 2016. This workshop convened cancer researchers, patient advocates, and representatives from industry, academia, and government to discuss challenges with traditional approaches to drug development, opportunities to improve the efficiency of drug development, and strategies to enhance the information available about a cancer therapy throughout its life cycle in order to improve its use in clinical practice. This publication summarizes the presentations and discussions from the workshop.

Oncoimmunology
Oncoimmunology

Author: Laurence Zitvogel

Publisher: Springer

Published: 2017-12-13

Total Pages: 700

ISBN-13: 3319624318

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In this book, leading experts in cancer immunotherapy join forces to provide a comprehensive guide that sets out the main principles of oncoimmunology and examines the latest advances and their implications for clinical practice, focusing in particular on drugs with FDA/EMA approvals and breakthrough status. The aim is to deliver a landmark educational tool that will serve as the definitive reference for MD and PhD students while also meeting the needs of established researchers and healthcare professionals. Immunotherapy-based approaches are now inducing long-lasting clinical responses across multiple histological types of neoplasia, in previously difficult-to-treat metastatic cancers. The future challenges for oncologists are to understand and exploit the cellular and molecular components of complex immune networks, to optimize combinatorial regimens, to avoid immune-related side effects, and to plan immunomonitoring studies for biomarker discovery. The editors hope that this book will guide future and established health professionals toward the effective application of cancer immunology and immunotherapy and contribute significantly to further progress in the field.

Medical Image Analysis
Medical Image Analysis

Author: Alejandro Frangi

Publisher: Academic Press

Published: 2023-09-20

Total Pages: 700

ISBN-13: 0128136588

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Medical Image Analysis presents practical knowledge on medical image computing and analysis as written by top educators and experts. This text is a modern, practical, self-contained reference that conveys a mix of fundamental methodological concepts within different medical domains. Sections cover core representations and properties of digital images and image enhancement techniques, advanced image computing methods (including segmentation, registration, motion and shape analysis), machine learning, how medical image computing (MIC) is used in clinical and medical research, and how to identify alternative strategies and employ software tools to solve typical problems in MIC. - An authoritative presentation of key concepts and methods from experts in the field - Sections clearly explaining key methodological principles within relevant medical applications - Self-contained chapters enable the text to be used on courses with differing structures - A representative selection of modern topics and techniques in medical image computing - Focus on medical image computing as an enabling technology to tackle unmet clinical needs - Presentation of traditional and machine learning approaches to medical image computing

Immunotherapy of Hepatocellular Carcinoma
Immunotherapy of Hepatocellular Carcinoma

Author: Tim F. Greten

Publisher: Springer

Published: 2018-08-22

Total Pages: 0

ISBN-13: 9783319879116

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In this book we provide insights into liver – cancer and immunology. Experts in the field provide an overview over fundamental immunological questions in liver cancer and tumorimmunology, which form the base for immune based approaches in HCC, which gain increasing interest in the community due to first promising results obtained in early clinical trials. Hepatocellular carcinoma (HCC) is the third most common cause of cancer related death in the United States. Treatment options are limited. Viral hepatitis is one of the major risk factors for HCC, which represents a typical “inflammation-induced” cancer. Immune-based treatment approaches have revolutionized oncology in recent years. Various treatment strategies have received FDA approval including dendritic cell vaccination, for prostate cancer as well as immune checkpoint inhibition targeting the CTLA4 or the PD1/PDL1 axis in melanoma, lung, and kidney cancer. Additionally, cell based therapies (adoptive T cell therapy, CAR T cells and TCR transduced T cells) have demonstrated significant efficacy in patients with B cell malignancies and melanoma. Immune checkpoint inhibitors in particular have generated enormous excitement across the entire field of oncology, providing a significant benefit to a minority of patients.

Advanced Healthcare Materials
Advanced Healthcare Materials

Author: Ashutosh Tiwari

Publisher: John Wiley & Sons

Published: 2014-05-09

Total Pages: 421

ISBN-13: 1118773683

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Offers a comprehensive and interdisciplinary view of cutting-edge research on advanced materials for healthcare technology and applications Advanced healthcare materials are attracting strong interest in fundamental as well as applied medical science and technology. This book summarizes the current state of knowledge in the field of advanced materials for functional therapeutics, point-of-care diagnostics, translational materials, and up-and-coming bioengineering devices. Advanced Healthcare Materials highlights the key features that enable the design of stimuli-responsive smart nanoparticles, novel biomaterials, and nano/micro devices for either diagnosis or therapy, or both, called theranostics. It also presents the latest advancements in healthcare materials and medical technology. The senior researchers from global knowledge centers have written topics including: State-of-the-art of biomaterials for human health Micro- and nanoparticles and their application in biosensors The role of immunoassays Stimuli-responsive smart nanoparticles Diagnosis and treatment of cancer Advanced materials for biomedical application and drug delivery Nanoparticles for diagnosis and/or treatment of Alzheimers disease Hierarchical modelling of elastic behavior of human dental tissue Biodegradable porous hydrogels Hydrogels in tissue engineering, drug delivery, and wound care Modified natural zeolites Supramolecular hydrogels based on cyclodextrin poly(pseudo)rotaxane Polyhydroxyalkanoate-based biomaterials Biomimetic molecularly imprinted polymers

Stem Cells – From Hype to Real Hope
Stem Cells – From Hype to Real Hope

Author: Khawaja Husnain Haider

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2018-12-17

Total Pages: 220

ISBN-13: 3110587041

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This book is a compilation of the bench experience of leading experts from various research labs involved in the cutting edge area of research. The authors describe the use of stem cells both as part of the combinatorial therapeutic intervention approach and as tools (disease model) during drug development, highlighting the shift from a conventional symptomatic treatment strategy to addressing the root cause of the disease process. The book is a continuum of the previously published book entitled "Stem Cells: from Drug to Drug Discovery" which was published in 2017.

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.