Understanding Cancer from a Systems Biology Point of View: From Observation to Theory and Back starts with a basic question, why do we sometimes observe accelerated metastatic growth after resection of primary tumors? Next, it helps readers understand the systemic nature of cancer and how it affects treatment approaches and decisions. The book puts together aspects of cancer that many readers have most likely never combined, using unfamiliar, novel methods. It is a valuable resource for cancer researchers, cancer biologists, mathematicians and members of the biomedical field who are interested in applying systems biology methodologies for understanding and treating cancer. - Explains the systemic nature of cancer and how it affects decisions on treatment - Brings a variety of methods together, showing, in detail, the logical approach to finding answers to complex questions - Discusses the theoretical underpinnings of cancer as a systemic disease, providing the reader with valuable information on applicable cases

An overview of the current systems biology-based knowledge and the experimental approaches for deciphering the biological basis of cancer.

Ecology and Evolution of Cancer is a timely work outlining ideas that not only represent a substantial and original contribution to the fields of evolution, ecology, and cancer, but also goes beyond by connecting the interfaces of these disciplines. This work engages the expertise of a multidisciplinary research team to collate and review the latest knowledge and developments in this exciting research field. The evolutionary perspective of cancer has gained significant international recognition and interest, which is fully understandable given that somatic cellular selection and evolution are elegant explanations for carcinogenesis. Cancer is now generally accepted to be an evolutionary and ecological process with complex interactions between tumor cells and their environment sharing many similarities with organismal evolution. As a critical contribution to this field of research the book is important and relevant for the applications of evolutionary biology to understand the origin of cancers, to control neoplastic progression, and to prevent therapeutic failures. - Covers all aspects of the evolution of cancer, appealing to researchers seeking to understand its origins and effects of treatments on its progression, as well as to lecturers in evolutionary medicine - Functions as both an introduction to cancer and evolution and a review of the current research on this burgeoning, exciting field, presented by an international group of leading editors and contributors - Improves understanding of the origin and the evolution of cancer, aiding efforts to determine how this disease interferes with biotic interactions that govern ecosystems - Highlights research that intends to apply evolutionary principles to help predict emergence and metastatic progression with the aim of improving therapies

The future of cancer research and the development of new therapeutic strategies rely on our ability to convert biological and clinical questions into mathematical models—integrating our knowledge of tumour progression mechanisms with the tsunami of information brought by high-throughput technologies such as microarrays and next-generation sequencing. Offering promising insights on how to defeat cancer, the emerging field of systems biology captures the complexity of biological phenomena using mathematical and computational tools. Novel Approaches to Fighting Cancer Drawn from the authors’ decade-long work in the cancer computational systems biology laboratory at Institut Curie (Paris, France), Computational Systems Biology of Cancer explains how to apply computational systems biology approaches to cancer research. The authors provide proven techniques and tools for cancer bioinformatics and systems biology research. Effectively Use Algorithmic Methods and Bioinformatics Tools in Real Biological Applications Suitable for readers in both the computational and life sciences, this self-contained guide assumes very limited background in biology, mathematics, and computer science. It explores how computational systems biology can help fight cancer in three essential aspects: Categorising tumours Finding new targets Designing improved and tailored therapeutic strategies Each chapter introduces a problem, presents applicable concepts and state-of-the-art methods, describes existing tools, illustrates applications using real cases, lists publically available data and software, and includes references to further reading. Some chapters also contain exercises. Figures from the text and scripts/data for reproducing a breast cancer data analysis are available at www.cancer-systems-biology.net.

A fundamental and groundbreaking reassessment of how we view and manage cancer When we think of the forces driving cancer, we don’t necessarily think of evolution. But evolution and cancer are closely linked because the historical processes that created life also created cancer. The Cheating Cell delves into this extraordinary relationship, and shows that by understanding cancer’s evolutionary origins, researchers can come up with more effective, revolutionary treatments. Athena Aktipis goes back billions of years to explore when unicellular forms became multicellular organisms. Within these bodies of cooperating cells, cheating ones arose, overusing resources and replicating out of control, giving rise to cancer. Aktipis illustrates how evolution has paved the way for cancer’s ubiquity, and why it will exist as long as multicellular life does. Even so, she argues, this doesn’t mean we should give up on treating cancer—in fact, evolutionary approaches offer new and promising options for the disease’s prevention and treatments that aim at long-term management rather than simple eradication. Looking across species—from sponges and cacti to dogs and elephants—we are discovering new mechanisms of tumor suppression and the many ways that multicellular life-forms have evolved to keep cancer under control. By accepting that cancer is a part of our biological past, present, and future—and that we cannot win a war against evolution—treatments can become smarter, more strategic, and more humane. Unifying the latest research from biology, ecology, medicine, and social science, The Cheating Cell challenges us to rethink cancer’s fundamental nature and our relationship to it.

The book shows how mathematical and computational models can be used to study cancer biology. It introduces the concept of mathematical modeling and then applies it to a variety of topics in cancer biology. These include aspects of cancer initiation and progression, such as the somatic evolution of cells, genetic instability, and angiogenesis. The book also discusses the use of mathematical models for the analysis of therapeutic approaches such as chemotherapy, immunotherapy, and the use of oncolytic viruses.