Prioritizing Combinational Drug Screening: A Ranking System for In Vitro Drug Combinations in Neurofibromatosis Type 1

Abstract

Neurofibromatosis type 1 (NF1) is a genetic disorder characterized by benign tumors, including plexiform neurofibromas, which can be difficult to treat. Currently, only two FDA-approved therapies exist: selumetinib, approved for pediatric patients with inoperable tumors, and mirdametinib, approved for patients aged two and older with symptomatic peripheral neuropathy where surgical resection is not possible. These limited options highlight the urgent need for novel therapeutic strategies, including combination therapies and therapies applicable to adult populations. In this study, we introduce the Composite Matrix Reduction Score (CMRS), a novel algorithm designed to evaluate the in vitro efficacy of drug combinations for NF1-related plexiform neurofibromas. Using a high-throughput 6x6 combinatorial matrix, we screened three cell lines: ipnNF95.11c (NF1+/-, non-tumor reference), and two NF1-/- tumor lines: ipNF05.5mc and ipNF95.6. Cell viability responses to drug combinations were normalized to vehicle controls, and combination effects were compared to single-agent responses. Tumor-to-non-tumor response ratios were aggregated to generate a composite ranking for each drug pair. Our results show that certain drug combinations outperformed single agents in reducing tumor cell viability, consistent with findings in other cancers. A focused analysis on selumetinib combinations supported the CMRS algorithm and identified potential synergistic partners that may surpass a single-agent therapy, highlighting candidates for continued investigation. CMRS provides a scalable, standardized framework for prioritizing drug combinations in NF1 and potentially other cancers. By integrating multi-cell line analysis, this approach enhances the identification of promising therapeutic candidates and mechanisms of action for further preclinical development.