Whole Genome Expression Analysis for Biologic Rational Pathway Modeling

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