The transcriptional atlas of co-targeted PIM/PI3K/mTOR ex-vivo patient-derived prostate cancer as revealed by spatial transcriptomics

PIM 1 and PI3K/mTOR pathways are frequently dysregulated in prostate cancer and may lead to decreased survival invasion and metastasis. Moreover, anti-tumour drug resistance has been associated with the interconnection of these pathways. Furthermore, current treatments exhibit issues with toxicity. Hence, these pathways were co-targeted with novel preclinical multikinase PIM/PI3K/mTOR inhibitor- AUM302, PI3K/mTOR inhibitor BEZ235 (Dactolisib) and PIM inhibitor, AZD-1208 in our laboratory using a cohort of cancer explants emanating from our PEOPLE: PatiEnt prOstate samPLes for rEsea ch study and our current SCREEN study. This cohort has a high Gleason grade score of ≥ 8. Therefore, this study aims to assess the effect of the combination therapy on the transcriptional landscape of ex vivo prostate cancer models derived from prostate cancer patients. Using the Nanostring GeoMX DSP technology, we aim to analyse the spatial transcriptomic profile of the co-targeted therapy treated ex vivo models to decipher the effects of heterogeneity on the co-targeted therapies' efficacy. Tissue microarrays of co-targeted treated twenty-five ex vivo 3mm cores derived from 4 patients will be analysed. Following RNA Scope analysis, morphology markers, including PAN CK positive and PAN CK negative, will be used to guide the selection of 270 regions of interest (ROI). ROI will be segmented and profiled using immunofluorescence. The morphological markers will define these segments into areas of illumination (AOIs) using a combination of the absence or presence of CD45 and pSTAT3. The AOIs will generate multiple expression profiles for the related ROI. We intend to use this flexible, high-dimensional spatial profiling to identify the spatial transcriptomic signatures and explore phosphorylation sites in cancer-targeted therapies. The spatial transcriptomics analysis of this study is in view. Our findings will contribute to understanding how the spatial landscape of the tumour microenvironment enhances the efficacy of anti-tumour drugs and what subset of patients are more likely to benefit from such therapy.