Profiling of conditionally reprogrammed cell lines for in vitro chemotherapy response prediction of pancreatic cancer

BACKGROUND: The establishment of patient-derived models for pancreatic ductal adenocarcinoma (PDAC) using conventional methods has been fraught with low success rate, mainly because of the small number of tumour cells and dense fibrotic stroma. Here, we sought to establish patient-derived model of PDAC and perform genetic analysis with responses to anticancer drug by using the conditionally reprogrammed cell (CRC) methodology. METHODS: We performed in vitro and in vivo tumourigenicity assays and analysed histological characteristics by immunostaining. We investigated genetic profiles including mutation patterns and copy number variations using targeted deep sequencing and copy-number analyses. We assessed the responses of cultured CRCs to the available clinical anticancer drugs based on patient responsiveness. FINDINGS: We established a total of 28 CRCs from patients. Of the 28 samples, 27 showed KRAS mutations in codon 12/13 or codon 61. We found that somatic mutations were shared in the primary-CRC pairs and shared mutations included key oncogenic mutations such as KRAS (9 pairs), TP53 (8 pairs), and SMAD4 (3 pairs). Overall, CRCs preserved the genetic characteristics of primary tumours with high concordance, with additional confirmation of low-AF NPM1 mutation in CRC (35 shared mutations out of 36 total, concordance rate=97.2%). CRCs of the responder group were more sensitive to anticancer agents than those of the non-responder group (P < 0.001). INTERPRETATION: These results show that a pancreatic cancer cell line model can be efficiently established using the CRC methodology, to better support a personalized therapeutic approach for pancreatic cancer patients. FUNDING: 2014R1A1A1006272, HI19C0642-060019, 2019R1A2C2008050, 2020R1A2C209958611, and 2020M3E5E204028211