1. Chapter 7 Essential Concepts in Molecular Pathology Companion site for Molecular Pathology Author: William B. Coleman and Gregory J. Tsongalis

2. Companion site for Molecular Pathology Copyright © 2009 by Academic Press. All rights reserved. 2 FIGURE 7.1 Laboratory workflow of a typical microarray experiment.

3. Companion site for Molecular Pathology Copyright © 2009 by Academic Press. All rights reserved. 3 FIGURE 7.2 Two-color microarray experiment.

4. Companion site for Molecular Pathology Copyright © 2009 by Academic Press. All rights reserved. 4 FIGURE 7.3 Gene expression changes associated with increased culture density over time. In each of the arrays used to analyze gene expression during the diauxic shift, red spots represent genes that were induced relative to the initial time point, and green spots represent genes that were repressed. Note that distinct sets of genes are induced and repressed in the different experiments. Cell density as measured by optical density (OD) at 600 nm was used to monitor the growth of the culture. Reproduced with permission from AAAS, Science 1997;278:680–686.

5. Companion site for Molecular Pathology Copyright © 2009 by Academic Press. All rights reserved. 5 FIGURE 7.4 Analysis of regulatory modules within the promoters of co-regulated genes associated with the diauxic shift. (A) Growth curve of yeast cells shown as increasing optical density (black line) upon glucose consumption (red line). (B) Induction of a group of genes carrying a carbon source element (CSRE) within their promoters. The decreasing glucose level (red line) allows determination of a threshold for the onset of gene expression (grey and black lines) mediated by the CSRE. Reproduced by permission from AAAS, Science 1997;278:680–686.

6. Companion site for Molecular Pathology Copyright © 2009 by Academic Press. All rights reserved. 6 FIGURE 7.5 Hierarchical clustering of genes induced or repressed during serum response in human fibroblasts. Ten gene clusters (A–J) harboring 517 genes, which show significant alterations in gene expression over time, are depicted. For each gene, the ratio of mRNA levels in fibroblasts at the indicated time intervals after serum stimulation compared to their level in the serum-deprived (time zero) fibroblasts is represented by a color code, according to the scale for fold-induction and fold-repression shown at the bottom. The diagram at the right of each cluster depicts the overall tendency of the gene expression pattern within this cluster. The term unsync denotes exponentially growing cells. Reproduced with permission from AAAS, Science 1999;283:83–87.

7. Companion site for Molecular Pathology Copyright © 2009 by Academic Press. All rights reserved. 7 FIGURE 7.6 Differential breast cancer gene expression. Gene expression patterns of 85 experimental samples (78 carcinomas, 3 benign tumors, 4 normal tissues) analyzed by hierarchical clustering using a set of 476 cDNA clones. (A) Tumor specimens were divided into 6 subtypes based on their differences in gene expression: luminal subtype A, dark blue; luminal subtype B, yellow; luminal subtype C, light blue; normal breast-like, green; basal-like, red; and ERBB2+, pink. (B) The full cluster diagram obtained after two-dimensional clustering of tumors and genes. The colored bars on the right represent the characteristic gene groups named C to G and are shown enlarged in the right part of the graph: (C) ERBB2 amplification cluster, (D) novel unknown cluster, (E) basal epithelial cell-enriched cluster, (F) normal breast epithelial-like cluster, (G) luminal epithelial gene cluster containing ER (estrogen receptor). Reproduced with permission from the National Academy of Sciences USA, Proc Natl Acad Sci U S A 2001;98:10869–10874.

8. Companion site for Molecular Pathology Copyright © 2009 by Academic Press. All rights reserved. 8 FIGURE 7.7 Survival analysis (Kaplan-Meier plot) of patient groups distinguished according to gene expression profiling. The Y-axis shows the survival probability for each individual group; the X-axis represents the time scale according to patient follow-up data. All groups identified by gene expression profiling are shown. Luminal type A, dark blue; luminal type B, yellow; luminal type C, light blue; normal type, green; ERBB2-like type, pink; and basal type, red. Patients with ERBB2-like or basal type tumors had the shortest survival times; luminal-type A patients had the best prognosis. All others showed an intermediate probability and were not clearly distinguishable. Reproduced with permission from the National Academy of Sciences USA, Proc Natl Acad Sci U S A 2001;98:10869–10874.

9. Companion site for Molecular Pathology Copyright © 2009 by Academic Press. All rights reserved. 9 FIGURE 7.8 Identification of the prognostic breast cancer gene set using a supervised approach. The 231 genes identified as being most significantly correlated to disease outcome were used to recluster, as described in the text. Each row represents a tumor and each column a gene. The genes are ordered according to their correlation coefficient with the two prognostic groups. The tumors are ordered according to their correlation to the average profile of the good prognosis group. The solid line marks the prognostic classifier showing optimal accuracy; the dashed line marks the classifier showing optimized sensitivity. Patients above the dashed line have a good prognosis signature, while patients below the dashed line have a poor prognosis signature. The metastasis status for each patient is shown on the right. White bars indicate patients who developed distant metastases within 5 years after the primary diagnosis; black indicates disease-free patients. Reprinted with permission from van't Veer et al., Nature 2002;415:530-536.

10. Companion site for Molecular Pathology Copyright © 2009 by Academic Press. All rights reserved. 10 FIGURE 7.9 Gene signatures representing germinal center (GC)-like diffuse large B-cell lymphomas (DLBCL) and activated B-cell-like DLBCL. (A) Genes characteristic for normal germinal center B-cells were used to cluster the tumor samples. This process defines two distinct classes of B-cell lymphomas: GC-like DLBCL and activated B-cell-like DLBCL. (B) Genes that were selectively expressed either in GC-like DLBCL (yellow bar) or activated B-cell-like DLBCL (blue bar) were identified in the tumor samples. (C) Result of hierarchical clustering that generated GC-like and activated B-cell-like DLBCL gene signatures. Reprinted with permission from Alizadeh et al., Nature 2000;403:503–511.

11. Companion site for Molecular Pathology Copyright © 2009 by Academic Press. All rights reserved. 11 FIGURE 7.10 Survival analysis of diffuse large B-cell lymphoma patients distinguishable according to gene expression profiling, conventional clinical criteria, and a combination of both sets of criteria. (A) DLBCL patients grouped on the basis of gene expression profiling. The GC-like (germinal center-like) and the activated B-cell-like show clearly different survival probabilities. (B) DLBCL patients grouped according to the International Prognostic Index (IPI) form two groups with clearly different survival, independent of gene expression profiling. Low clinical risk patients (IPI score 0–2) and high clinical risk patients (IPI score 3–5) are plotted separately. (C) Low clinical risk DLBCL patients (IPI score 0–2) shown in B were grouped on the basis of their gene expression profiles and exhibited two distinct groups with different survival probabilities. Reprinted with permission from Alizadeh et al., Nature 2000;403:503–511.