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humans. Mutations in other genes in the Hh signaling pathway are also associated with cancer. Some such mutations create oncogenes that turn on Hh target genes inappropriately; others are recessive mutations that affect negative regulators like Ptcl. As is the case for a number of other tumor-suppressor genes, complete loss of Ptcl function would lead to early fetal death, since it is needed for development, so it is only the tumor cells that are homozygous ptc1/ptc1.

Many of the signaling pathways described in other chapters play roles in controlling embryonic development and cell proliferation in adult tissues. In recent years mutations af-

fecting components of most of these signaling pathways have been linked to cancer (Figure 23-12). Indeed, once one gene in a developmental pathway has been linked to a type of human cancer, knowledge of the pathway gleaned from model organisms like worms, flies, or mice allows focused investigations of the possible involvement of additional pathway genes in other cases of the cancer. For example, APC, the critical first gene mutated on the path to colon carcinoma, is now known to be part of the Wnt signaling pathway, which led to the discovery of the involvement of p-catenin mutations in colon cancer. Mutations in tumor-suppressor developmental genes promote tumor formation in tissues where the affected gene normally helps restrain growth, and not in cells where the primary role of the developmental regulator is to control cell fate but not growth. Mutations in developmental proto-oncogenes may induce tumor formation in tissues where an affected gene normally promotes growth or in another tissue where the gene has become aberrantly active.

DNA Microarray Analysis of Expression Patterns Can Reveal Subtle Differences Between Tumor Cells

Traditionally the properties of tumor and normal cells have been assessed by staining and microscopy. The prognosis for many tumors could be determined, within certain limits, from their histology. However the appearance of cells alone has limited information content, and better ways to discern the properties of cells are desirable both to understand tumorigenesis and to arrive at meaningful and accurate decisions about prognosis and therapy.

As we've seen, genetic studies can identify the single initiating mutation or series of mutations that cause transforma-

► EXPERIMENTAL FIGURE 23-13 Differences in gene expression patterns determined by DNA microarray analysis can distinguish between otherwise phenotypically similar lymphomas. Samples of mRNA were extracted from normal lymphocytes at different stages of differentiation and from malignant lymphocytes obtained from patients with three types of lymphoma. DNA microarray analysis of the extracted RNA determined the transcription of about 18,000 genes by each of the 96 experimental samples of normal and malignant lymphocytes relative to a control, reference sample. (See Figures 9-35 and 9-36 for description of microarray analysis.) The cluster diagram shown here includes the data from a selected set of genes whose expression differs the most in the various lymphocyte samples. An intense red color indicates that the experimental cells transcribe the gene represented by a particular DNA spot at a much higher level than the reference cells; intense green indicates the opposite. Black indicates similar transcript levels in the samples compared; gray indicates missing or excluded data. Each vertical column contains the data for a particular lymphocyte sample (see sample key). Each horizontal row contains data for a single gene. The genes were grouped according to their similar patterns of hybridization. For example, genes indicated by the green bar on the right are active in proliferating cells, such as transformed cultured cells (pink bar at top) or lymphoma cells (purple bar at top). The different cell samples (along the top of the diagram) also were grouped according to their similar expression patterns. The resulting dendrogram (tree diagram) shows that the samples from patients with diffuse large B cell lymphoma (purple samples) fall into two groups. One group is similar to relatively undifferentiated B lymphocytes in germinal centers (orange samples); the other is similar to more differentiated B cells (light-purple samples). [From A. A. Alizadeh et al., 2000, Nature 403:505.]

tion of normal cells into tumor cells, as in the case of colon cancer. After these initial events, however, the cells of a tumor undergo a cascade of changes reflecting the interplay between the initiating events and signals from outside. As a result, tumor cells can become quite different, even if they arise from the same initiating mutation or mutations. Although these differences may not be recognized from the appearance of cells, they can be detected from the cells' patterns of gene expression. DNA microarray analysis can determine the expression of thousands of genes simultaneously, permitting complex phenotypes to be defined at the molecular genetic level. (See Figures 9-35 and 9-36 for an explanation of this technique.)

Microarray analysis recently has been applied to diffuse large B cell lymphoma, a disease marked by the presence of abnormally large B lymphocytes throughout lymph nodes. Affected patients have highly variable outcomes, so the disease has long been suspected to be,

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Aclrsalcf] B call in fact, multiple diseases. Microarray analysis of lymphomas from different patients revealed two groups distinguished by their patterns of gene expression (Figure 23-13). No morphological or visible criteria were found that could distinguish the two types of tumors. Patients with one tumor type defined by the microarray data survived much longer than those with the other type. Lymphomas whose gene expression is similar to that of B lymphocytes in the earliest stages of differentiation have a better prognosis; lymphomas whose gene expression is closer to that of more differentiated B lymphocytes have a worse prognosis. Similar analyses of the gene expression patterns, or "signatures," of other tumors are likely to improve classification and diagnosis, allowing informed decisions about treatments, and also provide insights into the properties of tumor cells. I

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