Understanding and Using Information about Cancer Genomes

The Emerging Cancer Genome Landscape

Genome aberrations found to be important in human cancers are illustrated in Figure 24-1 and include (1) somatic changes in copy number that increase or decrease the levels of important coding and noncoding RNA transcripts, (2) somatic mutations that alter gene expression, protein structure, or protein stability and/or change the way transcripts are spliced, (3) structural changes that affect transcript levels by altering gene-promoter associations or create new fusion genes, and (4) epigenomic events that alter transcription levels of diverse signaling pathways and that enable rapid emergence of therapeutically resistant subpopulations. Table 24-1 shows the number of gene aberrations catalogued in the Cancer Gene Census maintained by the Sanger Institute that have been implicated in one or more human cancer types (see http://www.sanger.ac.uk/genetics/CGP/Census ). These aberrations have been implicated in deregulation of pathways that influence all aspects of cancer progression including invasion, immortalization, DNA replication and repair, proliferation, apoptosis, angiogenesis, motility, and adhesion. However, the 487 genes implicated in the Cancer Gene Census are likely to be only a small fraction of the aberrant genetic events that play important roles in the form and function of human cancers. These genes have been selected primarily because they were implicated in model system studies or because they occur frequently in one or more cancer subtypes. However, recent genomic studies demonstrate that hundreds to thousands of genes may be affected by somatic mutations and epigenomic modifications in an individual tumor. These comprise a mix of “driver” aberrations and a usually larger number of “passenger” aberrations. Driver aberrations are genomic or epigenomic events that are selected during tumor progression because they alter one or more aspects of cell and tissue physiology to allow cancer initiation, progression, and/or dissemination. Table 24-2 , for example, illustrates several genes that might contribute to the deregulation of the cancer hallmarks designated by Weinberg and Hanahan. Some of these aberrations have been targeted by therapeutics, and others have been shown to influence clinical behavior, including response to targeted and nontargeted therapies. Passenger aberrations do not contribute to cancer pathophysiology but arise by chance during progression in a genomically unstable tumor and are carried along because they exist in cells carrying driver aberrations. Driver aberrations are identified either because they occur frequently in tumor subpopulations or because they have been identified as contributing to aspects of cancer pathophysiology in laboratory models of cancer—for example, cultured cancer cells or genetically manipulated nonmalignant cells, or cancer cells grown as xenografts in animals—or have been demonstrated to influence aspects of cancer in genetically engineered living organisms. Several general cancer genomic observations from international cancer genomics projects are summarized in the following paragraphs.

One important observation from many genomic studies is the existence of recurrent molecular features that allow cancers that occur in specific anatomic regions to be organized into subtypes. The subtypes likely arise in distinct cell types within each tissue and are different diseases that differ in clinical outcome and/or response to therapy. Early genomic studies relied on expression patterns for cancer subtype definition, but current strategies use multiple data types (e.g., genome copy number, mutation, and expression) for subtype definition. Interestingly, epithelial and mesenchymal subtypes appear to be present in tumors that are of epithelial origin. The mesenchymal-like cancers tend to be more rapidly proliferating and motile and associated with reduced survival duration. Some tumor types show remarkably high transcriptional similarity, for example, in triple-negative breast cancer and high-grade serous ovarian cancers. Many genomic aberrations also appear in multiple tumor subtypes. Some of the most common aberrations observed in multiple tumor types include amplifications of MYC and EGFR, deletion of CDKN2A and PTEN, and mutation of TP53 and PIK3CA. For a more comprehensive assessment, Kim and colleagues summarize recurrent genome copy number aberrations in 8000 cancers. Efforts are now under way to combine data types (e.g., expression, genome copy number, and mutations) to increase the number of subtypes in order to increase the precision with which patients can be stratified according to outcome and/or therapeutic response. Of course, this divides cancers into increasingly smaller subpopulations, so very large numbers of samples are needed to establish subtype differences in treatment response or overall outcome.

The number of aberrations that are present in an individual tumor can be remarkably high. The somatic mutation rate in human cancers varies between cancer types from about 0.1 to 10 mutations per megabase, but individual tumors may carry as few as a hundred to more than a million somatic aberrations. High genomic instability occurs because of loss of telomere function during progression in the absence of telomerase, diminished DNA repair capacity resulting from genomic and epigenomic deregulation of DNA repair pathways, increased damage resulting from oncogene-induced oxidative stress, and toxic environmental exposures. In some cases, the exact DNA sequence change in a mutation reflects the type of agent that causes the cancer—for example, mutations in sun-related cancers show CC to TT mutations caused by UV-induced cytosine dimers, whereas smoking-induced cancers in the lung are characterized by G→T transversions caused by the polycyclic aromatic hydrocarbons in tobacco smoke. Ultimately, the functions and/or expression levels of hundreds to thousands of genes may be altered in an individual tumor. An unknown number of these will be drivers. Among these, some will have a strong, possibly dominant influence on an individual tumor, whereas others may have a more modest or near-negligible impact. So far, most attention in the field has focused on the strong drivers. However, it seems likely that the ensemble of aberrations will have to be taken into account in explaining the overall behavior of an individual tumor, which is addressed in a later section.

The same drivers of genome instability that enable tumor development also operate during tumor progression. As a result, individual tumors become increasingly heterogeneous as distinct clonal populations within the tumor evolve in diverse microenvironments, producing highly branched lineages. For example, events that enable metastasis may occur late during the genetic evolution, whereas mutation of TP53, a key player in genome stability, can be an early event. These instabilities and the resultant intratumor heterogeneity in an individual tumor are likely responsible for the rapid evolution of therapeutic resistance. This heterogeneity complicates clinical decision making because the importance of a low-frequency but actionable aberration remains unclear. One possible way forward is to focus treatment on aberrations that occur early during tumor development. The order in which aberrations occur can be inferred by examining a tissue at various stages of disease progression by serial sampling of clinical tissue from individual patients, by computational methods that examine mutation frequency, or in some cases by analysis of the interactions between mutations and copy-number abnormalities.

Functional Assessment of Cancer Genomes

Transforming cancer genomic data into interpretable knowledge consists of finding the parts and learning how they work together to enable aspects of cancer pathophysiology. Hypothesis-driven research has gone quite far in this process, but full understanding will require systematic analysis, both computational and experimental, of the aberrations that occur within a tumor genome.