Selection of Personalized Patient Therapy through the Use of Knowledge-Based Computational Models That Identify Tumor-Driving Signal Transduction Pathways

Abstract

Increasing knowledge about signal transduction pathways as drivers of cancer growth has elicited the development of "targeted drugs," which inhibit aberrant signaling pathways. They require a companion diagnostic test that identifies the tumor-driving pathway; however, currently available tests like estrogen receptor (ER) protein expression for hormonal treatment of breast cancer do not reliably predict therapy response, at least in part because they do not adequately assess functional pathway activity. We describe a novel approach to predict signaling pathway activity based on knowledge-based Bayesian computational models, which interpret quantitative transcriptome data as the functional output of an active signaling pathway, by using expression levels of transcriptional target genes. Following calibration on only a small number of cell lines or cohorts of patient data, they provide a reliable assessment of signaling pathway activity in tumors of different tissue origin. As proof of principle, models for the canonical Wnt and ER pathways are presented, including initial clinical validation on independent datasets from various cancer types. Cancer Res; 74(11); 2936-45. Ó2014 AACR.

SOX9 drives WNT pathway activation in prostate cancer

“…Therefore, we also examined a gene set indicative of WNT pathway activation derived from colon cancer cells, which was also validated in breast cancer (43). GSEA with this WNT pathway activation gene set showed a strong correlation with SOX9 expression in both the TCGA and MSKCC data sets (SOX9 is in this gene set but was removed for this analysis to avoid artifactual inflation of the enrichment score) ( Figure 5, E and F).…”

Precision Medicine: From “Omics” to Economics towards Data-Driven Healthcare - Time for European Transformation

“…It would be ensured that patients have access to the most suitable trial for their disease with regard to the choice of the drug but also for technological measurement of the target [36]. …”

The application of antitumor drug-targeting models on liver cancer

“…Taken together, the investigation of animal models is an essential aspect of the study on antitumortargeting agents (Arap et al, 1998;Kukowska-Latallo et al, 2005). With the further studies of pharmacology, pharmacodynamics, biopharmaceutics and pharmacokinetics (Callegari et al, 2014;Denzler et al, 2014), it is expected that the research level of the antitumor-targeting models would attain a deeper level and accomplish more superior achievements (Chen & Calvisi, 2014;Verhaegh et al, 2014). …”