Abstract 5831: Biopolymer β-brachytherapy delivered concomitantly with systemic paclitaxel outperforms traditional x-ray radiation to induce complete regression in multiple pancreatic tumor xenograft models

Pancreatic tumors remain one of the deadliest manifestations of cancer in clinical oncology. Even when tumors are diagnosed early, remain loco-regionalized, and receive cutting-edge cancer treatment, the 5-year survival rate remains less than 27%. This high mortality rate arises from the significant biologic barriers that inhibit drug delivery effectiveness in pancreatic tumors, as well as their underlying genetic mutations that confer resistance to traditional radiation and chemotherapeutic standards of care. In this work, we hypothesized that a new form of radiation brachytherapy might prove highly synergistic for overcoming the resistance native to pancreatic tumors. Utilizing the thermally stabilized biopolymer ELP, 131 iodine radionuclides can be delivered intratumorally to provide continuous, focalized, high-dose β-radiation to treat pancreatic cancer from the inside out. Dose-escalation studies revealed that the two important variables for improving outcomes were the 131 I-ELP radioactivity dose and the duration of concurrent paclitaxel therapy. 100% tumor regression was achieved across multiple genotypic models of pancreatic cancer models: MIA PaCa-2, AsPc-1, and BxPc3 (both subcutaneous and orthotopic). The potent synergistic results of 131 I-ELP brachytherapy were replicated using both a novel micelle formulation of paclitaxel and the clinical standard Abraxane. Multigroup analysis revealed true molecular synergy as assessed by the Bliss Independence framework (p Citation Format: Jeffrey L. Schaal, Jayanta Bhattacharyya, Xinghai Li, Samagya Banskota, Jeremy Brownstein, David Kirsch, Michael Zalutsky, Ashutosh Chilkoti. Biopolymer β-brachytherapy delivered concomitantly with systemic paclitaxel outperforms traditional x-ray radiation to induce complete regression in multiple pancreatic tumor xenograft models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5831.