Abstract 2272: Unlocking the potential of miRNA sequencing for early detection and monitoring of pancreatic cancer progression and recurrence

Abstract Pancreatic cancer (PC) is an elusive and deadly disease. Many patients with PC are diagnosed with metastatic or locally advanced tumors, limiting surgical resection, and increasing the risk of relapse after treatment. Relapse is recorded to be as high as 75% in the first 2 years after clinical intervention, resulting in a mean 5-year survival of 12% in the US, and as low as 2% worldwide. It is vital to develop diagnostic and monitoring techniques for PC. MicroRNAs (miRNAs) are robustly expressed in patient tumors and provide a rich source of biomarkers for disease detection and status. miRNA are short nucleic acid strands that bind to catalytic proteins to guide the regulation of large RNAs within the cellular space. This system is altered in tumors, leading to abhorrent expression of miRNA. Due to significant advancements in sequencing technology, miRNA-seq has become more accurate and affordable in detecting profile changes. To identify biomarkers for PC progression, we developed from the Gemcitabine-sensitive MIA-PaCa-2 (MP2) cell line the Gemcitabine and FOLFIRINOX resistant MP2-GR cell line. MiRNA-seq was conducted on the parental MP2 and resistant MP2-GR cells to identify those miRNAs that were differentially expressed between the cell lines. These miRNAs were analyzed via pathway analysis and gene ontology to find predicted functions followed by annotations from the miRNA Enrichment Analysis and Annotation tool (miEAA) to identify differentially expressed miRNAs associated with PC progression. This comparison indicated several miRNAs related to PC resistance. This dataset was then compared to The Cancer Genome Atlas (TCGA), which contains data from over 300 PC patients. The miRNA set was used to predict both PC progression after treatment, and recurrence. We are currently refining this data set to increase its predictive sensitivity and widen our patient data set comparison to further elucidate this approach in a clinical setting. Citation Format: Ryan N. Fuller, Ann Morcos, Desirae Escalera, Nathan R. Wall. Unlocking the potential of miRNA sequencing for early detection and monitoring of pancreatic cancer progression and recurrence abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 2272.