Multiscale Cancer Modeling PDF

Preface

In 2003, the conclusion of the Human Genome Project identified approximately 25,000 genes. How all these genes and the hundreds of thousands of proteins that they encode interact to form physiological phenotypes and how molecular alterations potentially lead to abnormal patterns, including cancer, is still largely unknown. Genes, cells, and tissues function through many intricate processes that span multiple scales in space and time. Therefore, focusing on a particular level of observation alone may not provide sufficient insight as to the mechanistic relationships across scales. However, the complexity involved is daunting and from an experimental perspective, it is often difficult technically if not prohibitively expensive to alter all parameters involved, reproducibly, in an effort to explore the data space methodically. It is here where in silico biology driven by cutting- edge mathematical and computational methods and techniques will have a profound impact. Its translational goals in cancer research range from experimentally-testable hypothesis generation and cross-scale data integration to patient-specific prediction of progression and treatment planning (in silico oncology). However, the scientific and technical expertise spectrum necessary to conduct such innovative multiscale modeling research often exceeds the resources of a single research department, institution, or even country. And so this is nothing less than the dawn of a new era of interdisciplinary and multi-institutional collaboration, and a unique opportunity for international exchange to accelerate progress. In recognizing both the considerable challenges and the enormous potential, on October 23–24, 2008, the European Commission and the U.S. National Cancer Institute (NCI) jointly funded the First Transatlantic Workshop on Multiscale Cancer Modeling in Brussels, Belgium. For the first time, this meeting brought together the majority of the top in silico modeling groups in the United States and in Europe. This textbook presents the best contributions of this groundbreaking event-the state of the art of multiscale cancer modeling.