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This protocol describes the 3D drug screening assays that have been effectively used to assess drug vulnerabilities in spheroid models of glioma8. This 3D spheroid assay system was specifically designed to allow for a more accurate preclinical investigation of combinatorial chemotherapies for glioma cell lines grown in spheres. For HGG, this method provides a framework for identifying prospective drug vulnerabilities for this devastating disease. However, the potential applications of this system are not limited to glioma and this protocol can be used to evaluate novel therapeutics in 3D models of various other conditions.
The goal of this study is to enhance the predictability of in vitro drug screens to prioritize those drug combinations that have the highest likelihood for success in preclinical studies and, eventually, the clinic. Especially in glioma, the identification of potent drug combinations using in vitro drug screens that translate well to the clinic has remained limited. This is in part due to the use of less ideal serum-grown glioma cell lines13, the use of 2D monolayer assays4, and a focus on IC50 (50% reduced growth) instead of LD50 (50% fewer cells compared to the beginning of the assay) values14. In vitro spheroid growth assays of glioma stem cells are used to prioritize drug combinations to evaluate in our preclinical models. In our prioritization of drug combinations, a few measures are taken into account: 1) Low LD50 values, a focus on cell death rather than reduced proliferation elevates the potential success; 2) Ideally, these LD50 values are below the Cmax value, the maximum serum concentration that can be safely attained during pharmacokinetic drug studies for clinical trials, if available; 3) A high synergy score, if both drugs work synergistically this points to mechanistic cooperation between both drugs. Although this last point is not required to identify potent drug combinations, synergy can enhance drug efficacy without increasing drug toxicities.
Importantly, in vitro assessments of drug sensitivities remain an important tool for discovering novel therapies or drug combinations that can shrink tumors. The protocol presented here allows us to determine drug sensitivity and synergy with a 3D spheroid growth assay system which can be used to prioritize drug combinations to evaluate in preclinical models.
The protocol involves several critical steps. We are measuring the growth of single colonies in each well of a 96 well plate. The use of low attachment round bottom well plates is critical to ensure that cells do not attach to the well and that the sphere formation is stimulated. The round bottom well ensures that the single sphere is always located in the same spot of the 96 well plate.
After plating the cells, plates must be centrifuged to ensure that all plated cells come together at the lowest point of the round bottom well and that a single 3D sphere is formed. The total volume of each well must be 140 µL. This will ensure the correct final concentrations of respective drugs in each well.
When pipetting into the 96 well plate, use the reverse pipetting technique, this reduces the risk of generating air bubbles in the wells. Air bubbles impede the live imager from correctly imaging each well, and the intensity of the fluorescence will be incorrect, affecting downstream analysis of the results.
The provided plate layout and spreadsheets are specific to the protocol described. If one deviates from the plating, incorrect IC50 and LD50 values will be calculated. The spreadsheet automatically calculates the dilutions when the highest concentration is provided. For each experiment, update the highest concentration otherwise, incorrect IC50 and LD50 values will be calculated.
Graphpad uses logarithmic concentrations to calculate IC50 and LD50 values. These logarithmic concentrations are automatically calculated in the provided spreadsheet and can be directly copied to software. Not using logarithmic concentrations will result in incorrect IC50 and LD50 values.
We are using cell lines that naturally grow as spheres. One can force adherent cells into a sphere using this protocol; however, it is not guaranteed they will be able to proliferate. The number of cells plated in each well may be cell line-dependent and rely on the unique growth characteristics of individual cell lines, which can be easily adjusted. The proposed dilution curves are suggestions only. Modifications to drug concentrations and dilution series can be made. However, it is important to list the correct drug concentrations in Supplementary File 1 if the dilution series is changed; otherwise, the calculated IC50 and LD50 values will be incorrect. One can choose to use a different plate layout; for example, only use one replicate instead of two. For this, the user must update the spreadsheet to reflect this change.
Following plating, multiple 3D spheres form in a single well on rare occasions. In such a case, repeating the centrifugation step (150 x g) causes these spheres to merge into a single sphere. If a plating error is made, resulting in a different plate layout, the provided spreadsheet can be modified to reflect the new plate map. If a data point is an outlier and needs to be removed from the analysis, the provided spreadsheet can be updated.
The main limitation of this system is that it utilizes cell lines naturally grown as spheres and not adherent lines grown in monolayers. If cell lines cannot form spheres, traditional 2D proliferation assays should be used. The advantage of utilizing 3D organoid-like growth assays such as this one when compared to conventional 2D monolayers is that the architecture and activated signaling pathways more accurately reflect those observed in in vivo models of human disease, emphasizing the translational potential and applicability of these methods.