Identification of treatment-induced vulnerabilities in pancreatic cancer patients using functional model systems.

Despite the advance and success of precision oncology in gastrointestinal cancers, the frequency of molecular-informed therapy decisions in pancreatic ductal adenocarcinoma (PDAC) is currently neglectable. We present a longitudinal precision oncology platform based on functional model systems, including patient-derived organoids, to identify chemotherapy-induced vulnerabilities. We demonstrate that treatment-induced tumor cell plasticity in vivo distinctly changes responsiveness to targeted therapies, without the presence of a selectable genetic marker, indicating that tumor cell plasticity can be functionalized. By adding a mechanistic layer to precision oncology, adaptive processes of tumors under therapy can be exploited, particularly in highly plastic tumors, such as pancreatic cancer.

Mesenchymal Plasticity Regulated by Prrx1 Drives Aggressive Pancreatic Cancer Biology.

BACKGROUND & AIMS: Pancreatic ductal adenocarcinoma (PDAC) is characterized by a fibroblast-rich desmoplastic stroma. Cancer-associated fibroblasts (CAFs) have been shown to display a high degree of interconvertible states including quiescent, inflammatory, and myofibroblastic phenotypes; however, the mechanisms by which this plasticity is achieved are poorly understood. Here, we aim to elucidate the role of CAF plasticity and its impact on PDAC biology. METHODS: To investigate the role of mesenchymal plasticity in PDAC progression, we generated a PDAC mouse model in which CAF plasticity is modulated by genetic depletion of the transcription factor Prrx1. Primary pancreatic fibroblasts from this mouse model were further characterized by functional in vitro assays. To characterize the impact of CAFs on tumor differentiation and response to chemotherapy, various coculture experiments were performed. In vivo, tumors were characterized by morphology, extracellular matrix composition, and tumor dissemination and metastasis. RESULTS: Our in vivo findings showed that Prrx1-deficient CAFs remain constitutively activated. Importantly, this CAF phenotype determines tumor differentiation and disrupts systemic tumor dissemination. Mechanistically, coculture experiments of tumor organoids and CAFs showed that CAFs shape the epithelial-to-mesenchymal phenotype and confer gemcitabine resistance of PDAC cells induced by CAF-derived hepatocyte growth factor. Furthermore, gene expression analysis showed that patients with pancreatic cancer with high stromal expression of Prrx1 display the squamous, most aggressive, subtype of PDAC. CONCLUSIONS: Here, we define that the Prrx1 transcription factor is critical for tuning CAF activation, allowing a dynamic switch between a dormant and an activated state. This work shows that Prrx1-mediated CAF plasticity has significant impact on PDAC biology and therapeutic resistance.

Implementing cell-free DNA of pancreatic cancer patient-derived organoids for personalized oncology.

One of the major challenges in using pancreatic cancer patient-derived organoids (PDOs) in precision oncology is the time from biopsy to functional characterization. This is particularly true for endoscopic ultrasound-guided fine-needle aspiration biopsies, typically resulting in specimens with limited tumor cell yield. Here, we tested conditioned media of individual PDOs for cell-free DNA to detect driver mutations already early on during the expansion process to accelerate the genetic characterization of PDOs as well as subsequent functional testing. Importantly, genetic alterations detected in the PDO supernatant, collected as early as 72 hours after biopsy, recapitulate the mutational profile of the primary tumor, indicating suitability of this approach to subject PDOs to drug testing in a reduced time frame. In addition, we demonstrated that this workflow was practicable, even in patients for whom the amount of tumor material was not sufficient for molecular characterization by established means. Together, our findings demonstrate that generating PDOs from very limited biopsy material permits molecular profiling and drug testing. With our approach, this can be achieved in a rapid and feasible fashion with broad implications in clinical practice.