Multi-Omics Analysis in Tumor Microenvironment and Tumor Heterogeneity
| Author | : Jinhui Liu |
| Publisher | : Frontiers Media SA |
| Total Pages | : 517 |
| Release | : 2023-09-25 |
| Genre | : Science |
| ISBN | : 2832534287 |
Multi Omics Analysis In Tumor Microenvironment And Tumor Heterogeneity
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Cancer Evolution
| Author | : Charles Swanton |
| Publisher | : Perspectives Cshl |
| Total Pages | : 350 |
| Release | : 2017 |
| Genre | : Medical |
| ISBN | : 9781621821434 |
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.
The Heterogeneity of Cancer Metabolism
| Author | : Anne Le |
| Publisher | : Springer |
| Total Pages | : 186 |
| Release | : 2018-06-26 |
| Genre | : Medical |
| ISBN | : 331977736X |
Genetic alterations in cancer, in addition to being the fundamental drivers of tumorigenesis, can give rise to a variety of metabolic adaptations that allow cancer cells to survive and proliferate in diverse tumor microenvironments. This metabolic flexibility is different from normal cellular metabolic processes and leads to heterogeneity in cancer metabolism within the same cancer type or even within the same tumor. In this book, we delve into the complexity and diversity of cancer metabolism, and highlight how understanding the heterogeneity of cancer metabolism is fundamental to the development of effective metabolism-based therapeutic strategies. Deciphering how cancer cells utilize various nutrient resources will enable clinicians and researchers to pair specific chemotherapeutic agents with patients who are most likely to respond with positive outcomes, allowing for more cost-effective and personalized cancer therapeutic strategies.
Precision Molecular Pathology of Glioblastoma
| Author | : José Javier Otero |
| Publisher | : Springer Nature |
| Total Pages | : 266 |
| Release | : 2021-04-30 |
| Genre | : Medical |
| ISBN | : 3030691705 |
This volume provides a balanced and realistic review of the current state of glioblastoma, ranging from traditional histological review, molecular pathology of glioma, modern radiomics, neurosurgical focus, and integration of treatment plans by neuro-oncologists. The book reviews basic principles such as epidemiology and etiology, and modern 2016 WHO classification of CNS tumors. Chapters cover a general overview of common molecular techniques used in molecular pathology, molecular pathology in a developing country, key drivers of patient outcomes and predictors of response to radiation and/or chemotherapy treatment, and immunohistochemical surrogates for key molecular pathology. It concludes with reviews on radiomics, animal and stem cell models of glioblastoma, and a chapter on the emerging field of Glioblastoma Neuroscience. Precision Molecular Pathology of Glioblastoma is intended for pathology residents and fellows interested in glioblastoma, general surgical pathologists who need reviews on how to implement modern glioblastoma classification, as well as neuro-radiologists, oncologists, and radiation oncologists needing a holistic perspective to glioblastoma diagnosis and management.
Epithelial-Mesenchymal Plasticity in Cancer Metastasis
| Author | : Mohit Kumar Jolly |
| Publisher | : MDPI |
| Total Pages | : 512 |
| Release | : 2020-12-29 |
| Genre | : Medical |
| ISBN | : 3039367242 |
Recent studies have highlighted that epithelial-mesenchymal transition (EMT) is not only about cell migration and invasion, but it can also govern many other important elements such as immunosuppression, metabolic reprogramming, senescence-associated secretory phenotype (SASP), stem cell properties, therapy resistance, and tumor microenvironment interactions. With the on-going debate about the requirement of EMT for cancer metastasis, an emerging focus on intermediate states of EMT and its reverse process mesenchymal-epithelial transition (MET) offer new ideas for metastatic requirements and the dynamics of EMT/MET during the entire metastatic cascade. Therefore, we would like to initiate discussions on viewing EMT and its downstream signaling networks as a fulcrum of cellular plasticity, and a facilitator of the adaptive responses of cancer cells to distant organ microenvironments and various therapeutic assaults. We hereby invite scientists who have prominently contributed to this field, and whose valuable insights have led to the appreciation of epithelial-mesenchymal plasticity as a more comprehensive mediator of the adaptive response of cancer cells, with huge implications in metastasis, drug resistance, tumor relapse, and patient survival.
Application of Bioinformatics in Cancers
| Author | : Chad Brenner |
| Publisher | : MDPI |
| Total Pages | : 418 |
| Release | : 2019-11-20 |
| Genre | : Medical |
| ISBN | : 3039217887 |
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.
Hepatocellular Carcinoma
| Author | : Yujin Hoshida |
| Publisher | : Springer |
| Total Pages | : 366 |
| Release | : 2019-08-05 |
| Genre | : Medical |
| ISBN | : 3030215407 |
This book provides a comprehensive overview of the current limitations and unmet needs in Hepatocellular Carcinoma (HCC) diagnosis, treatment, and prevention. It also provides newly emerging concepts, approaches, and technologies to address challenges. Topics covered include changing landscape of HCC etiologies in association with health disparities, framework of clinical management algorithm, new and experimental modalities of HCC diagnosis and prognostication, multidisciplinary treatment options including rapidly evolving molecular targeted therapies and immune therapies, multi-omics molecular characterization, and clinically relevant experimental models. The book is intended to assist collaboration between the diverse disciplines and facilitate forward and reverse translation between basic and clinical research by providing a comprehensive overview of relevant areas, covering epidemiological trend and population-level patient management strategies, new diagnostic and prognostic tools, recent advances in the standard care and novel therapeutic approaches, and new concepts in pathogenesis and experimental approaches and tools, by experts and opinion leaders in their respective fields. By thoroughly and concisely covering whole aspects of HCC care, Hepatocellular Carcinoma serves as a valuable reference for multidisciplinary readers, and promotes the development of personalized precision care strategies that lead to substantial improvement of disease burden and patient prognosis in HCC.
Multi-Omics Approaches for Decoding Heterogeneity in Cancer Immunotherapy
| Author | : Lin Qi |
| Publisher | : Frontiers Media SA |
| Total Pages | : 267 |
| Release | : 2023-11-22 |
| Genre | : Science |
| ISBN | : 2832539653 |
Ovarian Cancers
| Author | : National Academies of Sciences, Engineering, and Medicine |
| Publisher | : National Academies Press |
| Total Pages | : 397 |
| Release | : 2016-04-25 |
| Genre | : Medical |
| ISBN | : 0309380499 |
In an era of promising advances in cancer research, there are considerable and even alarming gaps in the fundamental knowledge and understanding of ovarian cancer. Researchers now know that ovarian cancer is not a single disease-several distinct subtypes exist with different origins, risk factors, genetic mutations, biological behaviors, and prognoses. However, persistent questions have impeded progress toward improving the prevention, early detection, treatment, and management of ovarian cancers. Failure to significantly improve morbidity and mortality during the past several decades is likely due to several factors, including the lack of research being performed by specific disease subtype, lack of definitive knowledge of the cell of origin and disease progression, and incomplete understanding of genetic and non-genetic risk factors. Ovarian Cancers examines the state of the science in ovarian cancer research, identifies key gaps in the evidence base and the challenges to addressing those gaps, considers opportunities for advancing ovarian cancer research, and examines avenues for translation and dissemination of new findings and communication of new information to patients and others. This study makes recommendations for public- and private-sector efforts that could facilitate progress in reducing the incidence of morbidity and mortality from ovarian cancers.
Introduction to Mathematical Oncology
| Author | : Yang Kuang |
| Publisher | : CRC Press |
| Total Pages | : 469 |
| Release | : 2016-04-05 |
| Genre | : Mathematics |
| ISBN | : 1584889918 |
Introduction to Mathematical Oncology presents biologically well-motivated and mathematically tractable models that facilitate both a deep understanding of cancer biology and better cancer treatment designs. It covers the medical and biological background of the diseases, modeling issues, and existing methods and their limitations. The authors introduce mathematical and programming tools, along with analytical and numerical studies of the models. They also develop new mathematical tools and look to future improvements on dynamical models. After introducing the general theory of medicine and exploring how mathematics can be essential in its understanding, the text describes well-known, practical, and insightful mathematical models of avascular tumor growth and mathematically tractable treatment models based on ordinary differential equations. It continues the topic of avascular tumor growth in the context of partial differential equation models by incorporating the spatial structure and physiological structure, such as cell size. The book then focuses on the recent active multi-scale modeling efforts on prostate cancer growth and treatment dynamics. It also examines more mechanistically formulated models, including cell quota-based population growth models, with applications to real tumors and validation using clinical data. The remainder of the text presents abundant additional historical, biological, and medical background materials for advanced and specific treatment modeling efforts. Extensively classroom-tested in undergraduate and graduate courses, this self-contained book allows instructors to emphasize specific topics relevant to clinical cancer biology and treatment. It can be used in a variety of ways, including a single-semester undergraduate course, a more ambitious graduate course, or a full-year sequence on mathematical oncology.
