Abstract 1548: Examination of miRNA dysregulation in pancreatic cancer PDX models with parallel proteomic and transcriptomic investigations

Introduction: Pancreatic cancer is a high-fatality cancer. An estimated 57,600 new cases were diagnosed in the United States in 2020 with a corresponding 47,050 deaths. Despite improvements in the molecular understanding of pancreatic cancer, the prognosis for this disease has not improved in nearly 4 decades, largely because of the lack of early stage disease detection and limited efficiency of systemic therapies. MicroRNAs (miRNAs) are a class of non-coding RNAs approximately 22 nucleotides (nt) in length that regulate gene expression. in recent years, the dysregulation of miRNAs has been implicated in the development of various human cancers. Methods: Parallel analysis of global mRNA, miRNA and protein expression was conducted on pancreatic cancer patient-derived xenografts. The data from this analysis of these F1 tumours, was used to refine/identify miRNA targets of interest to generate 2 differential expression (DE) lists for miRNA; 1) Tumour vs Normal and 2) Tumour vs F1. Predictive software was used to identify targets and pathways of the DE priority miRNAs. These targets were further refined by integrating the targets with the global mRNA and proteomic profiling (unpublished data) performed on the same clinical samples. Alteration of cancer phenotype was investigated using overexpression and/or sponge vectors for each miRNA. Results: Analysis generated a list of priority miRNAs that had inverse interactions with predicted protein targets and were shown to be differentially expressed in our proteomic data. From 39 miRNAs investigated from the priority list, 7 miRNAs targeted 2 or more proteins across the 2 comparisons. These miRNAs - miRs-2467, -4742, -509, -615-3p, -4534, -222 and 2-06 when altered in expression MIA PaCa-2 and PANC-1 pancreatic cancer cells resulted in modulated cell proliferation, colony forming ability and anoikis resistance. Studies are ongoing on the changes to the chemotherapy and radiosensitivity of each cell line in response to changing these miRNA levels. Conclusions: The study identified miRNAs which displayed increased expression between normal and tumour and again increased between tumour and F1. From this list using predicative software and integration with additional global analysis of mRNA and Protein expression a priority list of 7 miRNAs were identified. The core concept in this study was to use differential expression of miRNAs as a tool to further unravel the biology of human pancreatic cancer, in the hope of unco