Generation of chemoresistant PDXs in the era of modern neoadjuvant therapy

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Conference Proceeding

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Ann Surg Oncol


Background: Patient-derived xenografts (PDXs) allow for patient cancer tissue amplification and downstream in vivo research applications. A majority of PDXs derive from treatment naïve (TN) tumors. We aimed to generate PDXs from surgically resected TN and neoadjuvant (NA) pancreatic (PDAC) cancers to compare engraftment outcomes and create modern agent chemoresistant models. Methods: We maintain a prospective GI cancer PDX program. With informed consent and IRB approval, resected PDAC tissue is implanted into immunocompromised mice. Tumor growth is monitored, viable tumor is passed into subsequent generations, and pathologists confirm PDX histopatholgy to original patient tumor. MatePair sequencing characterized generated PDXs. Outcomes include 1) ischemic time (IT-time from retrieval to implantation, and 2) engraftment (ER-% of successful engraftment). Patient clinical, pathologic, and follow-up data were abstracted. Grade III treatment response was considered chemoresistant. Results: During 1/2013-8/2017, 139 patients with histologically confirmed PDAC were implanted (48 naïve and 91 neoadjuvant) with successful PDX ER in 70 (51%) tumors that was higher for TN tumors. Mate-pair analysis demonstrated highly correlative genomic signatures to primary patient tumor and PDX. Median IT did not differ between treatment groups Table. In NA tumors successful PDX ER varied by therapy type: FOLFIRINOX (FFX) 51%, gemcitabine/nab-paclitaxel (GA) 62%, and combined FFX/GA 22%. Table compares clinicopathologic features and patient outcomes between therapy type and PDX ER. Patients with successful PDX ER had significantly worse clinical RFS and OS regardless of treatment status. In total, we generated 19 FFX, 6 GA, and 1 FFX/GA resistant PDX models for future work. Conclusion: PDX generation after NA therapy is feasible and allows for creation of chemoresistant models for future drug development. Engraftment is successful in patients with minimal treatment response. PDX growth correlates with outcomes and is a valuable translational model for any patient. These PDXs will accommodate and assess differential responses to current therapies and elucidate predictive markers of response or resistance.




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