Cancer Genomics addresses how recent technological advances in genomics are shaping how we diagnose and treat cancer. Built on the historical context of cancer genetics over the past 30 years, the book provides a snapshot of the current issues and state-of-the-art technologies used in cancer genomics. Subsequent chapters highlight how these approaches have informed our understanding of hereditary cancer syndromes and the diagnosis, treatment and outcome in a variety of adult and pediatric solid tumors and hematologic malignancies. The dramatic increase in cancer genomics research and ever-increasing availability of genomic testing are not without significant ethical issues, which are addressed in the context of the return of research results and the legal considerations underlying the commercialization of genomic discoveries. Finally, the book concludes with "Future Directions", examining the next great challenges to face the field of cancer genomics, namely the contribution of non-coding RNAs to disease pathogenesis and the interaction of the human genome with the environment. - Tools such as sidebars, key concept summaries, a glossary, and acronym and abbreviation definitions make this book highly accessible to researchers from several fields associated with cancer genomics. - Contributions from thought leaders provide valuable historical perspective to relate the advances in the field to current technologies and literature.

Prostate cancer (CaP) is the most commonly diagnosed malignancy in men in the Western world. In North America, more than 275000 men are diagnosed annually whereby approximately 1 in 6 men will be diagnosed with CaP in their lifetime, and 1 in 34 men will die from castrate-resistant metastatic disease. Unfortunately, current clinical prognostic factors explain only a proportion of the observed variation in clinical outcome from patient to patient. Furthermore, over-treatment of indolent and low-risk cancers leads to inappropriate morbidity following radiotherapy or surgery. As such, better predictors of individualized prognosis and treatment response are urgently needed to triage patients to customized and intensified CaP treatment. Recent developments in next-generation sequencing have made it possible to identify prognostic and predictive signatures based on genomic profiles. Herein, we review the recent genetic data pertaining to prostate cancer carcinogenesis, progression, castrate-resistance and metastases. We discuss the genetic basis of CaP progression from localized to systemic disease (e.g. point mutations, copy number alterations and structural variants) and important considerations for CaP biology including intra- and inter-prostatic heterogeneity, multifocality and multiclonality, TMPRSS2–ERG and other ETS-family gene fusions and the role of the tumor microenvironment (e.g. hypoxia and the contribution of caner-associated stroma). Finally, we focus on the use of genomic markers as prognostic factors for local failure and for systemic disease, as novel risk stratification tools, in triaging patients to existing treatment options and, ultimately, the potential of genomics for the identification of molecular targets for CaP therapy. We conclude by summarizing selected outstanding questions in CaP biology that can be addressed effectively through international cooperation between genome sequencing projects such as The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC).

Cancer results from accumulated mutations in the genome. Sequencing is an accurate method to detect mutations. Second-generation sequencing technology, commonly referred to as next-generation sequencing technology, enables rapid, efficient and affordable DNA sequencing, and is transforming the scale and scope of cancer research. The technology is sufficiently flexible and affordable to allow sequencing of many cancer genomes, and thus facilitates both sequencing of samples from large patient cohorts and during disease progression in individual cancer patients. The high depths of redundant sequence coverage that can be obtained using some second-generation sequencing technologies, along with sequencing reads amplified from single DNA molecules, facilitate detection of subclones of cells in tumors. Large-scale genome sequencing of hundreds or even thousands of cancer samples is being conducted by several groups that aim to identify and characterize cancer driver mutations. Goals of such work, previously infeasible with Sanger sequencing instruments, are to use this information to improve cancer prognosis, diagnosis and therapeutic decision-making. The speed of data analysis is rate limiting, and investigators are struggling to accommodate and interpret the data deluge produced by second-generation technologies. In this chapter, we discuss cancer properties that are revealed by sequencing and the implication of such properties in experimental design and data interpretation. We describe past, current and upcoming sequencing technologies and the application of second-generation sequencing technologies in cancer genomics. Finally, we discuss the impact of second-generation sequencing technology in shaping personalized medicine.

The vast amount of genomic data being produced by the research community is becoming readily accessible to biomedical researchers and clinicians to apply to their cancer(s) of interest. The major cancer genome projects, among others, The Cancer Genome Atlas (TCGA), the International Cancer Genome Consortium (ICGC) and the Pediatric Cancer Genome Project (PCGP) are contributing to this genomic data goldmine by sequencing hundreds to thousands of cancer genomes and supplementing these data with analyses such as gene expression and methylation. In addition to the raw data that are being made available through large data warehouses, “Data Portals” are becoming the norm for accessing and analyzing these data by third parties. We describe key features of some of these portals and other tools for the analysis of next-generation sequencing and other genomic data.

Colorectal cancer (CRC) is the third most common form of cancer and a leading cause of cancer-related mortality in both men and women, particularly in Western and developed nations. The high mortality rate has been attributed to the fact that colon cancer is often diagnosed at a late stage. Three primary subtypes of CRC have been described based on their molecular pathology and their underlying genetics: chromosomal instability (CIN), microsatellite instability (MSI), and CpG island hypermethylation. Over the last 30 years, molecular and genetic studies have determined a number of key genetic pathways that are subverted in CRC, including those involving APC, KRAS, and the p53 tumor suppressor. More recently, high-throughput, genome-wide studies have begun to characterize the broader genomic features of CRC. These high-throughput studies provide an ever expanding, and increasingly complex view of the molecular underpinnings of CRC. The chief goal of these studies being the identification of new therapeutic targets, as well as the definition of prognostic and diagnostic biological markers of CRC. Here, we highlight the key genetic and molecular pathways underlying CRC, as well as more recent insights into this disease uncovered by genomic studies.

Breast cancer is the most common cancer in women worldwide and the second leading cause of cancer deaths. Although early diagnosis, outcome prediction and treatment options are the ultimate objectives when assessing breast cancer patients, the methodology behind this clinical assessment varies and has gradually evolved from using standard clinical criteria into incorporating high-throughput genome-wide analysis. Early methods involved evaluating tumor size and spread as well as histological assessment (tumor grade). Later, the expression of hormone/growth receptors (ER, PR, and HER2) was added to the standard stratification of breast cancer patients. More recently, molecular approaches, which are based on the expression of a well-defined set of genes, have subdivided patients into five clinically relevant subtypes which not only predict prognosis and dictate treatment choice but also complement standard assessment. The advent of genome-wide analysis has produced the most robust classification system of breast cancers by coupling specific genetic aberrations (single nucleotide mutations and gene copy number variations) with gene expression profiles. Although these genome-wide approaches offer a promising future for breast cancer prognosis and treatment options, they are still not clinically feasible for standard population-based screening. Nonetheless, these approaches are becoming faster and more reliable in understanding the molecular architecture of breast cancer and are slowly paving the way towards personalized treatments which are tailored to individual patients. In the light of a rapidly evolving field of breast cancer genomics, this chapter highlights key standard and upcoming approaches for diagnosis, prognosis and treatment and discusses the feasibility of genome-oriented personalized treatments.

The combination of molecular biology, engineering and bioinformatics has revolutionized our understanding of cancer revealing a tight correlation of the molecular characteristics of the primary tumor in terms of gene expression, structural alterations of the genome, epigenetics and mutations with its propensity to metastasize and to respond to therapy. It is not just one or a few genes, it is the complex alteration of the genome that determines cancer development and progression. Future management of cancer patients will therefore rely on thorough molecular analyses of each single case. Through this book, students, researchers and oncologists will obtain a comprehensive picture of what the first ten years of cancer genomics have revealed. Experts in the field describe, cancer by cancer, the progress made and its implications for diagnosis, prognosis and treatment of cancer. The deep impact on the clinics and the challenge for future translational research become evident.

Genome-wide association (GWA) studies and tumor-specific epigenome, transcriptome and genome sequencing projects are generating an ever-growing list of susceptibility alleles, as well as putative gain- and loss-of-function gene mutations associated with cancer. These genetic changes ultimately need to be validated to determine their contribution to the initiation, progression and likelihood of treatment response for various cancers. The bottle-neck is no longer obtaining sequence data or completion of the GWA studies, but rather the ability efficiently to validate candidate genes identified by these projects. In vivo studies in animal models are the “gold standard” for validation of these candidate drivers and modifiers of cancer. Furthermore, once a gene product or molecular pathway has been validated as playing an important role in the development or progression of cancer, animal models provide the necessary preclinical data for evaluation of the efficacy and toxicity of new therapeutics targeting that gene or pathway. As such, animal models play an essential role in cancer research by facilitating the translation of genomic discoveries into preclinical studies that precede new targeted therapies for cancer. In this chapter, we will discuss vertebrate and invertebrate animal models as they apply to cancer genomics, as well as key technologies employed. In particular, we will focus on the use of murine and zebrafish human tumor xenografts and transgenic models.

The number of people diagnosed with cancer each year will almost double to 21 million cases worldwide by 2030 because of the aging population. Studies of the human genome have demonstrated that as few as 5–10% of adult cancers are due to genetic inheritance. Over 90% of cancers are due to endogenous or exogenous exposure to chemicals and radiation; many of these carcinogenic exposures, to tobacco smoke, for example, are avoidable and thus the consequent disease is preventable. The “exposome” is the concept which captures all carcinogenic exposures across the lifetime, quantified by direct biomarker assessment. Exposomics is in its infancy, but if progress such as has occurred in the Human Genome project occurs in this field, it has the potential greatly to enhance our understanding of the complex interactions and mechanisms of action of environmental exposures. In particular, evidence is increasing that cancer is as much a disease of the epigenome as the genome and that many of these environmental factors act to alter gene expression through changes in the epigenome. Exposomics will enable us better to avoid carcinogenic exposures, to limit the carcinogenic effect of these exposures and to identify potential new targets for developmental therapeutics.

This work states that we are no longer satisfied to study a gene or gene product in isolation, but rather we strive to view each gene within the complex circuitry of a cell. It states that as a family of diseases, all cancer results from changes in the genome.