Conclusions
Our results suggest that patients with advanced CCA with pathogenic mutations of BRCA2, but not those with mutations of IDH1, ARID1A, or BAP1, are likely to benefit from PARPi therapy. This collection of CCA_PDXs provides new opportunities for evaluating drug response and prioritizing clinical trials.
Purpose
Cholangiocarcinoma (CCA) is usually diagnosed at advanced stages, with limited therapeutic options. Preclinical models focused on unresectable metastatic CCA are necessary to develop rational treatments. Pathogenic mutations in IDH1/2, ARID1A/B, BAP1, and BRCA1/2 have been identified in 30%-50% of patients with CCA. Several types of tumor cells harboring these mutations exhibit homologous recombination deficiency (HRD) phenotype with enhanced sensitivity to PARP inhibitors (PARPi). However, PARPi treatment has not yet been tested for effectiveness in patient-derived models of advanced CCA. Experimental design: We have established a collection of patient-derived xenografts from patients with unresectable metastatic CCA (CCA_PDX). The CCA_PDXs were characterized at both histopathologic and genomic levels. We optimized a protocol to generate CCA tumoroids from CCA_PDXs. We tested the effects of PARPis in both CCA tumoroids and CCA_PDXs. Finally, we used the RAD51 assay to evaluate the HRD status of CCA tissues.
Results
This collection of CCA_PDXs recapitulates the histopathologic and molecular features of their original tumors. PARPi treatments inhibited the growth of CCA tumoroids and CCA_PDXs with pathogenic mutations of BRCA2, but not those with mutations of IDH1, ARID1A, or BAP1. In line with these findings, only CCA_PDX and CCA patient biopsy samples with mutations of BRCA2 showed RAD51 scores compatible with HRD. Conclusions: Our results suggest that patients with advanced CCA with pathogenic mutations of BRCA2, but not those with mutations of IDH1, ARID1A, or BAP1, are likely to benefit from PARPi therapy. This collection of CCA_PDXs provides new opportunities for evaluating drug response and prioritizing clinical trials.