A pilot study for single cell RNA-sequencing of patient-derived pancreatobiliary cancer organoid.

Abstract

739 Background: For precision medicine, patient-derived organoid (PDO) is regarded as one of the promising models. However, current PDOs were mainly derived from surgical specimens. We aimed to analyze the single cell RNA-sequencing (scRNA-seq) of PDO from various sampling methods with different pathologic outcomes. Methods: In 2021, three pancreatic cancer and one gallbladder cancer samples were collected from surgical specimen, endoscopic ultrasound guided-fine needle biopsy (EUS-FNB), and endoscopic retrograde cholangiopancreatography (ERCP)-guided biopsy. The samples were mechanically dissociated with dissociation buffer and incubated using shaking incubator. Dissociated cells were seeded into growth factor reduced Matrigel. From these PDOs, we generated scRNA-seq data in each experimental design, and corrected batch effects that could occur when multiple samples are considered simultaneously in downstream analysis. Marker genes representing each cell subcluster were identified, and statistical hypothesis tests were performed to identify genes differentially expressed according to differences in biopsy methods and/or pathological results. Results: We found the optimal 8 types of sub cell-type clusters with a resolution parameter of 0.3 in clustering analysis based on the Uniform Manifold Approximation and Projection (UMAP) algorithm in terms of silhouette score. As a result of examining the expression levels of KRT19, a marker gene for malignant ductal cells, and RGS5, a stellate marker gene, which showed the same pattern as the existing PDAC transcriptome studies, it was confirmed that most of the cells derived from PDOs were malignant ductal cells. Finally, we identified a heterogeneous effect on gene expression patterns in ductal cells depending on not only pathological positivity, but also biopsy methods for organoid. Conclusions: According to our scRNA-seq, most cells were malignant cells and EUS-FNB could be a good sampling method for PDOs. However, further analysis about a heterogeneous effect on gene expression patterns is necessary.[Table: see text]