Target Discovery and Validation Reviews and Protocols

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Molecular Profiling of Breast Cancer 107 distinguished luminal subtype B from subtype A, such as GGH, LAPTMB4, and MYBL2, were highly expressed in TP53-mutated tumors. Among the genes highly expressed in tumors with a wild-type TP53 gene, most of the genes in the luminal/ER+ cluster (ER, GATA-3, RERG, and so on) were found, which recapitulates the low mutation rate of the luminal subtype A. Further studies are needed to determine which of the genes are direct targets of TP53 and which are present only by association with a particular expression phenotype. 6. Genome-Wide Copy Number Changes The power of microarrays also is illustrated in their broad range of utility; the same types of DNA microarrays can be used to investigate both the structural and the expressed genome (68). Variations in gene expression measured by analyzing the tumor RNA may be caused by underlying genomic DNA copy number alterations, which are key genetic events in the development and progression of human cancers. A genome-wide aCGH analysis of a subset of the tumors described here was carried out using similar cDNA microarrays as for the gene expression studies. In total, a profile was generated across 6691 mapped genes in 45 primary breast tumors and 10 breast cancer cell lines (69). Numerous DNA copy number alterations were detected in the tumors despite the presence of euploid nontumor cell types; the magnitudes of the observed changes were generally lower in the tumor samples than the cell lines. DNA copy number alterations were identified in all cancer cell lines and nearly all (40/45) tumors, and on every human chromosome in at least one sample. Recurrent regions of DNA copy number gain and loss were readily identifiable; gains within 1q, 8q 17q, and 20q were observed in all breast cancer cell lines, and a large proportion of tumor samples (75, 48, 50, and 34%, respectively), consistent with published cytogenetic studies (70–72). The parallel measurements of mRNA levels and copy number alterations revealed a global impact of widespread DNA copy number alteration on gene expression in tumor cells. The overall patterns of gene amplification and elevated gene expression are concordant, i.e., a significant fraction of highly amplified genes seem to be correspondingly highly expressed (69,73). The concordance between high-level amplification and increased gene expression is best illustrated for genes on chromosome 17 (Fig. 6), where the amplicon containing the oncogene ERBB2 is located. A comprehensive analysis of nearly 150 breast tumors by using aCGH is underway with a specific emphasis on the distribution of genomic alterations across the subtypes. Preliminary data indicate specific genomic aberrations to be present in the different tumor subtypes, further supporting our results that these molecular subtypes of breast cancer represent biologically distinct disease entities.
108 Sørlie Fig. 6. Concordance between DNA copy number and gene expression across chromosome 17. DNA copy number alteration (top) and mRNA levels (bottom) are illustrated for breast cancer cell lines and tumors. Breast cancer cell lines and tumors are separately ordered by hierarchical clustering in the top panel, and the identical sample order is
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METHODS IN MOLECULAR BIOLOGY 360 T
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M E T H O D S I N M O L E C U L A R
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© 2007 Humana Press Inc. 999 River
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vi Preface get. Approaches to targe
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viii Contents 10 Transgenic Animal
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x Contributors SAHOHIME MATSUMOTO
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xii Contents of Volume 2 12 Validat
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2 Sioud disease pathogenesis and pe
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4 Sioud A more fruitful approach fo
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6 Sioud both transient and permanen
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8 Sioud serum biomarkers. This syne
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10 Sioud Fig. 2. Schematic of targe
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12 Sioud 13. Magin, T. M. (1998) Le
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Harnessing the Human Genome 15 The
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Harnessing the Human Genome 17 Fig.
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Harnessing the Human Genome 23 The
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Harnessing the Human Genome 27 repr
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Harnessing the Human Genome 29 14.
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Harnessing the Human Genome 31 45.
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34 Imoto et al. (4,5), and Bayesian
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36 Imoto et al. 2. Materials Two ty
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38 Imoto et al. Fig. 3. Graphical v
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40 Imoto et al. Fig. 5. Result of t
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42 Imoto et al. p(D |G) = ∫ p(D,
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44 Imoto et al. β k (k = 1,…,q j
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46 Imoto et al. Fig. 7. Partial res
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48 Imoto et al. Fig. 8. Strategy to
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50 Imoto et al. Fig. 9. (continued)
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52 Imoto et al. Table 3 List of Roo
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54 Imoto et al. 5. De Hoon, M. J. L
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Transfected Cell Arrays 157 Fig. 1.
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Transfected Cell Arrays 159 2. The
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Transfected Cell Arrays 161 5. Simp
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164 Houdebine Fig. 1. Different met
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166 Houdebine concentrations become
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168 Houdebine Fig. 2. Major methods
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170 Houdebine integrate into the me
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172 Houdebine 2.2.3. Knock-In Into
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174 Houdebine as insulators. The co
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176 Houdebine Fig. 5. Different met
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178 Houdebine systems. Moreover, st
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180 Houdebine contribute to generat
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182 Houdebine Fig.7. Example of a v
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184 Houdebine more extensively. Tra
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186 Houdebine and stroma. Several o
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188 Houdebine explained at the mole
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190 Houdebine of the intestinal epi
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192 Houdebine interference of the g
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194 Houdebine 17. Whitelaw, C. B. A
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196 Houdebine 51. Bell, A. C., West
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198 Houdebine 86. Carmichael, G. G.
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200 Houdebine 121. Pailhoux, E., Vi
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202 Houdebine 156. Auerbach, A. B.,
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204 Vijayaraj, Söhl, and Magin 1.
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206 Vijayaraj, Söhl, and Magin Fig
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208 Vijayaraj, Söhl, and Magin fil
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210 Table 1 Orthologous Human and M
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212 Table 2 Orthologous Human and M
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214 Vijayaraj, Söhl, and Magin ulc
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216 Vijayaraj, Söhl, and Magin of
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220 Vijayaraj, Söhl, and Magin abs
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222 Vijayaraj, Söhl, and Magin 1.2
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224 Vijayaraj, Söhl, and Magin Fig
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226 Vijayaraj, Söhl, and Magin gen
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230 Vijayaraj, Söhl, and Magin f.
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234 Vijayaraj, Söhl, and Magin b.
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240 Vijayaraj, Söhl, and Magin alt
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242 Table 3 Time Schedule For Aggre
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250 Vijayaraj, Söhl, and Magin 101
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12 The HUVEC/Matrigel Assay An In V
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256 Skovseth, Küchler, and Haralds
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270 Iversen and Sørensen witnessed
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274 Iversen and Sørensen the core
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14 An Overview of the Immune System
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Overview of Immune System 279 diffe
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Overview of Immune System 281 Fig.
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Overview of Immune System 283 then
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Overview of Immune System 285 expre
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Overview of Immune System 287 Once
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Overview of Immune System 289 solub
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Overview of Immune System 291 amino
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Overview of Immune System 293 (unre
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Overview of Immune System 297 the c
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Overview of Immune System 299 (44).
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Overview of Immune System 301 demon
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Overview of Immune System 307 some
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Overview of Immune System 309 sera
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Overview of Immune System 313 measu
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Overview of Immune System 315 42. H
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Overview of Immune System 317 74. D
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15 Potential Target Antigens for Im
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Tumor Antigen Discovery 321 develop
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Tumor Antigen Discovery 323 panel b
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Tumor Antigen Discovery 325 16. Joc
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16 Identification of Tumor Antigens
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Immunoproteomics 329 by “shot gun
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Immunoproteomics 331 isoelectric fo
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Immunoproteomics 333 3. 2D-PAGE is
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17 Protein Arrays A Versatile Toolb
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Protein Arrays 337 Table 1 Classifi
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Protein Arrays 339 fractions from c
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Protein Arrays 341 combinatorial sc
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Protein Arrays 343 The ideal proteo
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Protein Arrays 345 18. Cekaite, H.
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Protein Arrays 347 49. Yuko Kawahas
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Index 349 Index A Acetyl-CoA carbox
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Index 351 conditional by using FRT
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Index 353 Recombinant tumor antigen
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