Thirteenth annual pezcoller symposium: focusing analytical tools on complexity in cancer.
ABSTRACT The physiopathology of cancer cells is the result of very complex signaling networks that represent in many cases distortions of the orderly networks regulating the physiology of normal cells. These networks are the consequence of the expression of, or the lack of expression of, genes, mutated or not, which represent the genomic profile of different types of or of individual cancers. The complex signaling pathways, the cross-talks among them, and the redundancies existing for several of them mediate not only the transmission of signals from the cell environment to the nucleus but also that from the nucleus to the other cellular components whose function is involved in cell proliferation, apoptosis, or differentiation. Modern approaches to cancer therapy and also prevention are aimed at identifying new molecular targets, pivotal to the life of the cancer cell, which would provide for specific sites of intervention. In the face of the enormous complexity of the phenomena on which the life of cancer cells is based, it is both difficult to identify unique specific target for intervention and important to develop analytical tools and approaches capable to identify them for further exploitation. This was the main subject of the Symposium. Consideration was given to: (a) tumor genotypic analysis through expression array evaluation and definition of cancer transcriptomes in studies aimed at identifying determinants of specific characteristics of cancer cells; (b) approaches based on the knowledge gained in this analysis that would lead to the visualization of new targets exploitable for antitumor action; and (c) multifactorial analysis of the complex interactions regulating cancer cells and methods to comprehend the complexity of molecular models and validate their functional relevance.
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ABSTRACT: A central goal of cancer biology is to understand how cells from this family of genetic diseases undergo specific morphological and physiological changes and regress to a de-regulated state of the cell cycle. The fact that tumors are unable to perform most of the specific functions of the original tissue led us to hypothesize that the degree of specialization of the transcriptome of cancerous tissues must be less than their normal counterparts. With the aid of information theory tools, we analyzed four datasets derived from transcriptomes of normal and tumor tissues to quantitatively test the hypothesis that cancer reduces transcriptome specialization. Here, we show that the transcriptional specialization of a tumor is significantly less than the corresponding normal tissue and comparable with the specialization of dedifferentiated embryonic stem cells. Furthermore, we demonstrate that the drop in specialization in cancerous tissues is largely due to a decrease in expression of genes that are highly specific to the normal organ. This approach gives us a better understanding of carcinogenesis and offers new tools for the identification of genes that are highly influential in cancer progression.PLoS ONE 01/2010; 5(5):e10398. · 4.09 Impact Factor