Development Of Quantitative Multi-Platform Tests For Easy Readout Of Ar, Er, Pi3k And Mapk Pathway Activity To Unravel Pathophysiology Across Cancer And Tissue Types

Introduction: Currently, the selection of targeted therapy is commonly based on genetic data, such as well-known gene mutations, but these mutations do not provide conclusive evidence for the functional activation of the affected pathway. For this reason, we have developed computational models to assess the molecular phenotype of individual tumors, determining the functional activity of oncogenic signaling pathways based on mRNA expression levels of the direct target genes of the respective pathway transcription factors (Verhaegh et al., Cancer Res 2014; Van Ooijen et al., Am J Pathol 2018; Van de Stolpe et al., Sci Rep 2019). For a broader application of these models, we translated them to RT-qPCR, RNA sequencing and microarray tests, for a quantitative and reproducible assessment of signaling pathway activity. Materials and methods: Focusing on the AR, ER, PI3K-FOXO and MAPK-AP1 pathways, we developed PCR primers and probes to assess mRNA expression levels of the pathways9 direct target genes. For model parameter calibration, we performed controlled cell line experiments in which the respective pathways were inactivated and activated, to have calibration samples with known pathway activity status. Per pathway, the same set of calibration samples and the same set of target genes were used to develop RT-qPCR, RNA sequencing and microarray tests, to maximize similarity. The resulting OncoSignal tests can be used for a quantitative assessment of pathway activity on individual samples, giving a score on a 0-100 scale. We verified these tests on independent samples with known pathway status. We ran repeat experiments to assess the reproducibility within each platform, and tested the same samples on all three platforms to assess cross-platform concordance. Results: Using the OncoSignal score, low activity test samples were clearly separated from highly active ones. For example, AR-PCR scores went from 19±3 on androgen-deprived LNCaP cell lines to 70±2 after stimulation with DHT, and went down again to 33±1 and 23±1 when subsequently treated with bicalutamide and enzalutamide, respectively. PI3K-FOXO-microarray scores went from 12±1 on control MCF7 experiments to 50±4 after alpelisib treatment. Measurements on 100+ samples on all three platforms showed Pearson correlations between 0.93 and 0.99 in OncoSignal scores, with absolute differences typically below 10. Conclusion: We developed broadly applicable tests to assess AR, ER, PI3K-FOXO and MAPK-AP1 pathway activity in a quantitative manner on individual samples, with good reproducibility on repeat experiments and good concordance between PCR, RNA sequencing and microarray measurements. These tests can be used to unravel disease pathophysiology in (pre-)clinical samples. The added value of OncoSignal for therapy response prediction is currently being evaluated in different studies. Citation Format: Martijn Akse, Henk van Ooijen, Anke Pierik, Sandra van den Bosch, Hans van Zon, Laurent Holtzer, Anne van Brussel, Marcia Inda, Yvonne Wesseling-Rozendaal, Wim Verhaegh, Eveline den Biezen-Timmermans. Development of quantitative multi-platform tests for easy readout of AR, ER, PI3K and MAPK pathway activity to unravel pathophysiology across cancer and tissue types [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4261.