Assistant Research Professor Houston Methodist Research Institute, United States
Disclosure(s):
Prashant Dogra, PhD: No financial relationships to disclose
Objectives: Non-small-cell lung cancer (NSCLC) remains a formidable challenge in oncology, particularly due to the emergence of cisplatin resistance and suboptimal treatment outcomes. Elevated expression of microRNA-155 (miR-155) has been implicated in promoting cisplatin resistance while concurrently exerting anti-tumor effects through the suppression of programmed death-ligand 1 (PD-L1) expression. In vivo therapeutic targeting of miR-155 through its antagonist, anti-miR-155, using nanoparticle (NP)-mediated delivery, has shown potential in controlling tumor growth and enhancing the efficacy of cisplatin [1]. However, anti-miR-155 is expected to negatively impact anti-cancer immunity by increasing PD-L1 expression, posing a challenge for its clinical development. Given that higher PD-L1 levels often correlate with better outcomes in NSCLC patients treated with immune checkpoint inhibitors (ICIs), we hypothesized that combining anti-miR-155 with ICIs could have synergistic effects. Careful evaluation of optimal dose ratios for the combination is necessary to avoid antagonistic effects. In this study, we utilized a multiscale mechanistic model to conduct a virtual clinical trial, investigating the translational potential of anti-miR-155, either alone or in combination with standard-of-care drugs, for early-stage NSCLC [2].
Methods: We developed a differential equations-based kinetic model of tumor growth dynamics integrated to a pharmacokinetic model to simulate the delivery and pharmacodynamics of systemic therapies in NSCLC. The model has been calibrated with in vivo data and extrapolated to humans for translationally relevant simulations and analyses. Sensitivity analyses identified determinants of tumor response, and we simulated clinically relevant treatment scenarios in a virtual patient cohort to establish dose-response relationships and evaluate drug combinations for potential synergistic effects.
Results: Our model-based simulations in virtual patients demonstrate that monotherapy with anti-miR-155 at a dose of 2.5 mg/kg administered once every three weeks exhibits significant anti-cancer activity, leading to a median progression-free survival (PFS) of 6.7 months. This compared favorably to the outcomes observed with cisplatin and immune checkpoint inhibitor antibodies pembrolizumab and atezolizumab. Furthermore, synergistic effects are observed with two- and three-drug combinations involving anti-miR-155, cisplatin, and pembrolizumab, culminating in substantial improvements in median PFS (11.3 months and 13.1 months, respectively). Our analyses also identified unfavorable dose ratios for drug combinations, highlighting the need for optimizing dose regimen to prevent antagonistic effects.
Conclusions: Our study bridges the translational gap between preclinical development and clinical application of anti-miR-155, providing insights into its potential as a standalone therapy and in synergistic combinations with existing treatments.
Citations: [1] Van Roosbroeck, Katrien, et al. "Combining anti-miR-155 with chemotherapy for the treatment of lung cancers." Clinical Cancer Research 23.11 (2017): 2891-2904. [2] P. Dogra et al. "Translational modeling-based evidence for enhanced efficacy of standard-of-care drugs in combination with anti-microRNA-155 in non-small-cell lung cancer." medRxiv (2024): 2024-03.
