# Addressing Chemoresistance in Pancreatic and Ovarian Cancers: Photodynamic Priming and Repurposing of Tetracyclines using Targeted Photo-Activable Multi-Inhibitor Liposome > **NIH NIH R01** · UNIV OF MARYLAND, COLLEGE PARK · 2021 · $673,220 ## Abstract ABSTRACT The prognosis for patients with advanced stage ovarian or pancreatic cancer has remained dismal for decades. The poor response rates result, in part, from resistance to salvage chemotherapies, including topoisomerase I (Top1) inhibitors such as irinotecan and topotecan. The full potential of Top1 inhibitors is hindered mainly by two mechanisms: (1) ATP-binding cassettes (ABC) transporters (i.e., P-glycoprotein and ABCG2) that actively pump drugs out of cancer cells, and (2) Upregulation of the DNA repair enzyme, tyrosyl- DNA phosphodiesterase 1, which resolves the topoisomerase I-DNA cleavable complexes to allow DNA religation and cell proliferation. It is becoming increasingly clear that no single treatment is likely to overcome this complex problem, and combination treatments of newly emerging modalities may offer the most promise. Here, we introduce a complementary, two-pronged approach to address chemoresistance: (i) Employing photodynamic priming (PDP) to damage ABC transporters, improve the delivery of Top1 inhibitors, and reduce the normal tissue toxicity, and (ii) Repurposing tetracycline antibiotics to inhibit the DNA damage repair enzyme tyrosyl-DNA phosphodiesterase 1. PDP is a clinically relevant, photochemistry-based modality that involves light activation of photosensitizers to modulate nearby tissues or biomolecules without killing the cells. This proposal leverages image-guided strategies and nanoscale engineering to develop Targeted Photo- Activable Multi-Inhibitor Liposome (TPMIL) that co-delivers PDP, Top1 inhibitors, and tetracycline antibiotics in the appropriate sequence with consideration of their mechanistic interactions. In addition to co-packaging Top1 inhibitors and antibiotics, TPMIL is surface modified with antibody-photosensitizer conjugates to target epidermal growth factor receptor, which is frequently amplified in pancreatic and ovarian cancer. Using a novel hyperspectral fluorescence microendoscope imaging system, we will longitudinally monitor photosensitizer delivery and changes in ABC transporter expression to improve PDP and chemosensitization in vivo (Aim 1). The mechanistic interactions between Top1 inhibitors and tetracycline antibiotics will be investigated in vivo, with and without PDP (Aim 2). Biomarkers predictive of chemosensitization will also be identified. TPMILs will be customized to target ovarian and pancreatic cancer cells while co-delivering photosensitizers, Top1 inhibitors, and tetracycline antibiotics (Aim 3). The safety and therapeutic efficacy of TPMIL will be determined in PDX mouse models (Aim 4). We have demonstrated the clinical feasibility of PDP in patients with locally advanced pancreatic cancer. For metastatic ovarian cancer, we envision a simple and feasible modification to the standard clinical framework. TPMILs will be delivered intraperitoneally after surgical debulking of ovarian tumors, and then light activated to trigger PDP and the release of chemotherapy and anti... ## Key facts - **NIH application ID:** 10197327 - **Project number:** 1R01CA260340-01 - **Recipient organization:** UNIV OF MARYLAND, COLLEGE PARK - **Principal Investigator:** Huang Chiao Huang - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $673,220 - **Award type:** 1 - **Project period:** 2021-04-01 → 2026-03-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10197327 ## Citation > US National Institutes of Health, RePORTER application 10197327, Addressing Chemoresistance in Pancreatic and Ovarian Cancers: Photodynamic Priming and Repurposing of Tetracyclines using Targeted Photo-Activable Multi-Inhibitor Liposome (1R01CA260340-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10197327. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*