Background: Unsupervised hierarchical clustering of gene expression data from 265 high grade serous ovarian cancer (HGSOC) patients identified 3 major molecular subgroups. One subgroup is driven by activation of the MAPK-pathway and is associated with a mesenchymal phenotype, poor prognosis and resistance to platinum.The MAPK pathway is currently being targeted by novel therapeutics and hence an assay to detect activation of the pathway across cancers would be highly valuable as a clinical trial enrichment tool. Methods: Using TCGA data we show the existence of the mesenchymal subgroup across a range of solid tumours including stomach, bladder 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 the development of a 15 transcript assay which can be used to prospectively identify the mesenchymal subgroup from archived tissue. The 15 gene expression assay was tested in preclinical model systems to assess its utility at predicting response to MEK inhibitors. Results: The 15 gene expression mesenchymal assay was a poor prognostic marker in 13 different solid tumours: overall HR = 1.78 [95% CI:1.65-1.92]) p < 0.0001. Additionally the assay was associated with a mesenchymal phenotype (migration, invasion) and activated MAPK (phospho-MAPK) signalling in preclinical cell line models. The assay also predicted phospho-MEK expression in 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 across cell line models from multiple diseases (p < 0.001) and to Trametinib in mouse xenograft studies of lung cancer cell lines. Conclusions: A 15 gene expression assay has been developed from FFPE samples across multiple diseases to detect a mesenchymal molecular subgroup associated with MAPK signalling. The assay predicted sensitivity to MEK inhibitors in pre-clinical cell line and mouse model systems. Further work aims to validate the assay as a predictive biomarker in clinical samples from patients treated with MEK targeted therapies.