Whole genome expression analysis for biologic rational pathway modeling: application in cancer prognosis and therapy prediction.

摘要: Using semi-quantitative microarray technology, almost every one of the approximately 30 000 human genes can be analyzed simultaneously with a low rate false-positives, high specificity, and quantification accuracy. This is supported by data from comparative studies microarrays reverse-transcription PCR for established cancer including those epidermal growth factor receptor (EGFR), receptor-2 (HER2/ERBB2), estrogen (ESR1), progesterone (PGR), urokinase-type plasminogen activator (PLAU), inhibitor-1 (SERPINE1). As such, expression provide an completely comprehensive background biological knowledge that applied to diagnostics. In clinical terms, profiling may able significant information regarding (i) identification high-risk patients requiring aggressive chemotherapy; (ii) pathway control therapy predictive parameters (e.g. ESR1 HER2); (iii) discovery targets biologically rational therapeutics capecitabine trastuzumab); (iv) additional support decisions about switching therapy; (v) target discovery; (vi) prediction course new therapies in trials. conclusion, whole genome analysis might determine important related progression adjuvant chemotherapy resistance, especially context approaches involving primary systemic chemotherapy. this review, we will survey current progress analyses prognosis prediction. Special emphasis given approach combining biostatistical biochemical genetic pathways.