There is an ongoing need for patient-specific chemotherapy for pancreatic cancer. Tumour cells isolated from human tissues can be used to predict patients' response to chemotherapy. However, the isolation and maintenance of pancreatic cancer cells is challenging because these cells become highly vulnerable after losing the tumour microenvironment. Therefore, we investigated whether the cells retained their original characteristics after lentiviral transfection and expansion. Three human primary pancreatic cancer cell lines were lentivirally transduced to create expandable (Ex) cells which were then compared with primary (Pri) cells. No obvious differences in the morphology or epithelial-mesenchymal transition (EMT) were observed between the primary and expandable cell lines. The two expandable cell lines showed higher proliferation rates in the 2D and 3D models. All three expandable cell lines showed attenuated migratory ability. Differences in gene expression between primary and expandable cell lines were then compared using RNA-Seq data. Potential target drugs were predicted by differentially expressed genes (DEGs), and differentially expressed pathways (DEPs) related to tumour-specific characteristics such as proliferation, migration, EMT, drug resistance, and reactive oxygen species (ROS) were investigated using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. We found that the two expandable cell lines expressed similar chemosensitivity and redox-regulatory capability to gemcitabine and oxaliplatin in the 2D model as compared to their counterparts. In conclusion, we successfully generated expandable primary pancreatic cancer cell lines using lentiviral transduction. These expandable cells not only retain some tumour-specific biological traits of primary cells but also show an ongoing proliferative capacity, thereby yielding sufficient material for drug response assays, which may provide a patient-specific platform for chemotherapy drug screening.
Keywords: RNA-Seq; chemosensitivity; chemotherapy; patient-tailored therapy; regression analysis; statistical comparison of populations.