Development Of A Pan-Cancer 15 Gene Expression Signature To Detect A Subgroup Drivers By Emt/Mapk Signalling.

11616 Background: Epithelial–mesenchymal transition (EMT) is the conversion of epithelial cells to mesenchymal cells and involves loss of cell–cell adhesion and cell polarity and increased motility, invasiveness and metastases. The EMT process has therefore been under investigation as a new target for anticancer drug discovery. The aim of this work was to develop an EMT biomarker suitable for formalin-fixed paraffin embedded (FFPE) tissue that could be used for patient treatment selection. Methods: Unsupervised hierarchical clustering of ovarian cancer gene expression data (TCGA. 2011) previously identified an EMT subgroup. We confirmed this EMT subgroup in FFPE tissue using 265 high grade serous ovarian cancer (HGSOC) FFPE samples. The analysis was extended to show existence of an EMT subgroup across a range of solid tumours including colon, lung, melanoma and prostate cancer. Further to this, a common gene list was generated to include only transcripts with high variability and expression across diseases, and used as a starting list for development of a 15 transcript assay which can be used to prospectively identify the EMT subgroup from archived tissue. Results: The 15 gene expression assay was a poor prognostic marker in Colorectal, (Relapse free survival: HR = 1.46 [95% CI:1.07-1.98]); Lung, (Relapse free survival: HR = 2.18 [95% CI:1.33-3.56]); Prostate cancer, (Biochemical recurrence: HR 2.49 CI: 1.43-4.34) and was associated with activated MAPK (phospho-MAPK) in preclinical models and clinical samples (p < 0.05). The assay score was reduced by MEK inhibition (p < 0.05) and elevated by KRAS, NRAS and MEK1 overexpression (p < 0.05). The assay predicted response to the MEK inhibitors Trametinib and Selumetinib in cell line models (p < 0.001). Conclusions: A 15 gene expression assay has been developed from FFPE samples across multiple diseases to detect an EMT molecular subgroup associated with MAPK signalling. The assay predicted sensitivity to MEK inhibitors in pre-clinical model systems. Further work aims to validate the assay as a predictive biomarker in clinical samples from patients treated with EMT or MEK targeted therapies.