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Introduction: Recent colorectal cancer trials with KRAS G12C inhibitors have faced resistance challenges, and a preclinical model is needed to test resistance inhibition strategies. Experimental Methods: We have developed a novel culturing system, ResCu, that allows for long-term culture of cells without the need for passaging, enabling us to determine treatment resistance that can develop over time in a physiologically relevant system that conserves the resistance pathways found in patients. Using this system, we evolved resistance to a KRAS G12C inhibitor, sotorasib, after only two weeks of culture. The evolved cells were characterized for cross-resistance and cross-sensitivity by exposing these cells to a panel of drugs for seven days. Cell viability was assessed by luminescence. Based on the drug screen results, the sotorasib evolved cells were further evolved to additional drug classes to identify novel therapeutic combinations. Whole population and single-cell transcriptomic analysis were used to identify resistance mechanisms and synthetic lethality. Results: Using the ResCu system, we evolved resistance to sotorasib, a KRAS G12C inhibitor, and other drugs in combination with sotorasib. We identified a synergistic combination of sotorasib and a secondary inhibitor that initially suppressed resistance in the sotorasib evolved cells. We identified potential mechanisms underlying this synergy using transcriptomic analysis to enable future mechanistic characterization. Subsequently, the ResCu system drove resistance evolution to the sotarasib synergistic combination. We identified splicing alterations associated with this resistance. Conclusion: We have developed a novel resistance culturing system, ResCu, that allows for preclinical testing of KRAS G12C inhibitors and determines the most promising compounds for inhibiting specific resistance pathways. This system allows for long-term culturing of cells without passaging, thereby maintaining the various phenotypes of the original populations that are commonly lost in traditional passaging cultures. Citation Format: Victor M. Ruiz, Lindsay Hill, Manasa Gadde, Christopher Bulow, Maurizio Morri, Nicholas Goldner. Using the ResCu system for preclinical testing of KRAS G12C inhibitors [abstract]. In: Proceedings of the AACR Special Conference: Targeting RAS; 2023 Mar 5-8; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Res 2023;21(5_Suppl):Abstract nr B030.

Introduction: 3D cellular models have become of increasing interest in anti-cancer drug discovery as a bridge between clinical models and traditional in vitro methods. An important component of this research is the comparison of drug-to-cell interactions and morphological characteristics between cells in mono-layer culture and the cells in 3D spheroids. Materials and Methods:The ResCu system is a novel long term, physiologically relevant culture system that avoids the need for passaging. It propagates tumoroids in a microenvironment that resembleshuman tissue. Cells with KRAS G12C mutation were cultured in the ResCu system for three months, during which they were constantly exposed to G12C inhibitors (G12Ci) for the evolution of resistant cell populations. Cells were also cultured in traditional 2D cultures and exposed to G12Ci. Transcriptomics was performed to determine resistant networks and identify different resistant subclones in each group. Results: We applied the ResCu system to model clinical resistance. We captured 95% of clinically identified on-target and pathway bypass resistance changes, and in the 2D system, only a fraction of mechanisms were discovered. Additionally, we noticed certain cell populations could tolerate higher doses of the G12Ci after resistance evolution in ResCu compared to 2D. A few had similar responses suggesting that the origin of the cell line plays a role in the microenvironment's impact on cellular response. Conclusion: By comparatively analyzing resistance evolution data for KRAS G12Ci in traditional 2D and ResCu, we were able to collect physiologically relevant data that can more confidently be applied to clinical studies than mono-layer cell culture data alone. Citation Format: Manasa Gadde, Elizabeth Schwabe, Kshithija Mulam, Lindsay Hill, Christopher Bulow. Bridging gaps in treatment resistance 2D models with the incorporation of 3D models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1682.

The goal of this study is to calibrate a multiscale model of tumor angiogenesis with time-resolved data to allow for systematic testing of mathematical predictions of vascular sprouting. The multi-scale model consists of an agent-based description of tumor and endothelial cell dynamics coupled to a continuum model of vascular endothelial growth factor concentration. First, we calibrate ordinary differential equation models to time-resolved protein expression data to estimate the rates of secretion and consumption of vascular endothelial growth factor by endothelial and tumor cells, respectively. These parameters are then input into the multiscale tumor angiogenesis model, and the remaining model parameters are then calibrated to time resolved confocal microscopy images obtained within a 3D vascularized microfluidic platform. The microfluidic platform mimics a functional blood vessel with a surrounding collagen matrix seeded with inflammatory breast cancer cells, which induce tumor angiogenesis. Once the multi-scale model is fully parameterized, we forecast the spatiotemporal distribution of vascular sprouts at future time points and directly compare the predictions to experimentally measured data. We assess the ability of our model to globally recapitulate angiogenic vasculature density, resulting in an average relative calibration error of 17.7% ± 6.3% and an average prediction error of 20.2% ± 4% and 21.7% ± 3.6% using one and four calibrated parameters, respectively. We then assess the model’s ability to predict local vessel morphology (individualized vessel structure as opposed to global vascular density), initialized with the first time point and calibrated with two intermediate time points. To the best of our knowledge, this represents the first study to integrate well-controlled, experimental data into a mechanism-based, multiscale, mathematical model of angiogenic sprouting to make specific, testable predictions.