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Molecular biology has rapidly advanced since the discovery of the basic flow of information in life, from DNA to RNA to proteins. While there are several important and interesting exceptions to this general flow of information, the importance of these biological macromolecules in dictating the phenotypic nature of living creatures in health and disease is paramount. In the last one and a half decades, and particularly after the completion of the Human Genome Project, there has been an explosion of technologies that allow the broad characterization of these macromolecules in physiology, and the perturbations to these macromolecules that occur in diseases such as cancer. In this volume, we will explore the modern approaches used to characterize these macromolecules in an unbiased, systematic way. Such technologies are rapidly advancing our knowledge of the coordinated and complicated changes that occur during carcinogenesis, and are providing vital information that, when correctly interpreted by biostatistical/bioinformatics analyses, can be exploited for the prevention, diagnosis, and treatment of human cancers. The primary purpose of this volume is to help bridge the gap between molecular biologists/ cancer researchers and bioinformatics/computational biology researchers by providing an overview of these technologies to those that are not yet familiar with them. With this in mind, we provide an introduction to these technologies and showcase how these have been used to gain an understanding of each of the major macromolecules that control the flow of information in normal and cancer cells: DNA, RNA, and Proteins. The first portion of the volume describes the use of microarrays and next generation sequencing for genome-wide analysis of genetic and epigenetic variation. The next portion provides an overview of these technologies in the study of gene expression at the RNA level. The final section details the use of mass spectrometry and tissue microarrays for high-throughput and parallel analysis of proteins. As these technologies are deployed in cancer research, and the analytical approaches for interpretation of the resulting data mature, we will greatly increase our fundamental understanding of carcinogenesis and be able to translate this understanding for development of biomarkers and therapeutic strategies in the dawning era of individualized medicine.
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