02097nas a2200241   4500008004100000245015300041210006900194260000900263300001100272490000600283520122100289100002001510700002301530700002101553700002401574700002101598700001801619700002201637700002001659700002301679700002401702856012901726       2011                        eng d00aAnalysis of normal-tumour tissue interaction in tumours: prediction of prostate cancer features from the molecular profile of adjacent normal cells.0 aAnalysis of normaltumour tissue interaction in tumours predictio  c2011  ae164920 v63 a<p>Statistical modelling, in combination with genome-wide expression profiling techniques, has demonstrated that the molecular state of the tumour is sufficient to infer its pathological state. These studies have been extremely important in diagnostics and have contributed to improving our understanding of tumour biology. However, their importance in in-depth understanding of cancer patho-physiology may be limited since they do not explicitly take into consideration the fundamental role of the tissue microenvironment in specifying tumour physiology. Because of the importance of normal cells in shaping the tissue microenvironment we formulate the hypothesis that molecular components of the profile of normal epithelial cells adjacent the tumour are predictive of tumour physiology. We addressed this hypothesis by developing statistical models that link gene expression profiles representing the molecular state of adjacent normal epithelial cells to tumour features in prostate cancer. Furthermore, network analysis showed that predictive genes are linked to the activity of important secreted factors, which have the potential to influence tumor biology, such as IL1, IGF1, PDGF BB, AGT, and TGF&beta;.</p>1 aTrevino, Victor1 aTadesse, Mahlet, G1 aVannucci, Marina1 aAl-Shahrour, Fatima1 aAntczak, Philipp1 aDurant, Sarah1 aBikfalvi, Andreas1 aDopazo, Joaquin1 aCampbell, Moray, J1 aFalciani, Francesco  uhttps://www.clinbioinfosspa.es/content/analysis-normal-tumour-tissue-interaction-tumours-prediction-prostate-cancer-features