Transcriptional Programs following Genetic Alterations in p53 , INK4A, and H-Ras Genes along Defined Stages of Malignant Transformation Michael Milyavsky, 1 Yuval Tabach, 1,2 Igor Shats, 1 Neta Erez, 1 Yehudit Cohen, 1 Xiaohu Tang, 1 Marina Kalis, 1 Ira Kogan, 1 Yosef Buganim, 1 Naomi Goldfinger, 1 Doron Ginsberg, 1 Curtis C. Harris, 3 Eytan Domany, 2 and Varda Rotter 1 Departments of 1 Molecular Cell Biology and 2 Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel and 3 Laboratory of Human Carcinogenesis, National Cancer Institute, NIH, Bethesda, Maryland Abstract The difficulty to dissect a complex phenotype of established malignant cells to several critical transcriptional programs greatly impends our understanding of the malignant trans- formation. The genetic elements required to transform some primary human cells to a tumorigenic state were described in several recent studies. We took the advantage of the global genomic profiling approach and tried to go one step further in the dissection of the transformation network. We sought to identify the genetic signatures and key target genes, which underlie the genetic alterations in p53 , Ras , INK4A locus, and telomerase , introduced in a stepwise manner into primary human fibroblasts. Here, we show that these are the minimally required genetic alterations for sarcomagenesis in vivo .A genome-wide expression profiling identified distinct genetic signatures corresponding to the genetic alterations listed above. Most importantly, unique transformation hallmarks, such as differentiation block, aberrant mitotic progression, increased angiogenesis, and invasiveness, were identified and coupled with genetic signatures assigned for the genetic alterations in the p53 , INK4A locus, and H-Ras , respectively. Furthermore, a transcriptional program that defines the cellular response to p53 inactivation was an excellent predictor of metastasis development and bad prognosis in breast cancer patients. Deciphering these transformation fingerprints, which are affected by the most common oncogenic mutations, provides considerable insight into regulatory circuits controlling malignant transformation and will hopefully open new avenues for rational therapeutic decisions. (Cancer Res 2005; 65(11): 4530-43) Introduction Human carcinogenesis can be divided into defined clinicopath- ologic stages. For example, colon cancer progression has been divided into distinct histologic stages directly correlated with genetic alterations in key tumor suppressors and oncogenes (1). Over the last two decades, the molecular nature of genes frequently mutated in human neoplasia was elucidated. Functionally, those genes can be divided to many categories. The most studied genes include signaling molecules (Ras , Src , Akt , tyrosine kinase receptors , etc.), core cell cycle regulators (pRb , p16 INK4A , cyclins , etc.), and transcription factors (p53 , E2F, NF-jB , etc.), This knowledge leads to the realization that neoplastic transformation involves aberrant signal transduction pathways intimately linked with the deregu- lated gene expression. Nevertheless, the underlying transcriptional changes, which arise as a consequence of sequential accumulation of genetic alterations and eventually drive the pathologic process, are still elusive. We addressed this challenge by the microarray technology. Monitoring gene expression changes on a genome-wide scale has proven to be a powerful method to study transcriptional programs involved in carcinogenesis (2). Comparisons between normal tissues and corresponding tumors or between various tumor types revealed significant differences in their mRNA profiles, including hundreds of differentially expressed genes (2). By combining classic supervised statistical methods with unsupervised techniques, such as hierarchical clustering and its advanced variants (3), analysis of microarray data can potentially identify specific biological signatures that reflect profound alterations in cellular pathways and processes. Indeed, molecular signatures that correlate with diagnosis and prognosis were discovered (2, 4–6). Yet, associations of those signatures with specific biological processes and genetic alterations acquired in vivo along transformation are not obvious. The difficulties stem largely from different genetic backgrounds of patients, variable and uncharacterized mutations, and undefined contributions to a resulting expression pattern of several cell types, such as inflammatory, endothelial, and stroma cells in addition to the bona fide tumor cells. Those considerations made it almost impossible to use established malignant cell lines or naturally occurring tumors to dissect the contribution of individual tumor suppressors or oncogenes to the observed changes in gene expression. Modeling of human carcinogenesis in vitro is an invaluable tool to examine the effects of individual oncogenes, tumor suppressors, and their combinations on the evolvement of the transformed phenotype. In this way, recently, the defined combinations of oncogenic events required to convert primary human cells into full-blown tumors were determined. Initially, full transformation was achieved by the combination of viral oncogenes, such as large and small T antigens together with cellular genes, such as mutant Ras and telomerase (7, 8). Later on, the cellular counterparts of viral oncogenes were showed to be sufficient to transform primary human fibroblasts. These include inactivation of p53 and either pRb or p16 INK4A tumor suppressors, overexpression of the catalytic Note: Supplementary data for this article are available at Cancer Research Online (http://cancerres.aacrjournals.org/). M. Milyavsky and Y. Tabach contributed equally to this work. V. Rotter holds the Norman and Helen Asher Professorial Chair in Cancer Research at the Weizmann Institute. E. Domany is the incumbent of the H.J. Leir Professorial Chair. Requests for reprints: Varda Rotter, Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel. Phone: 972-8-9344501; Fax: 972- 8-9465265; E-mail: varda.rotter@weizmann.ac.il. 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