Advancements in the Metabolic Profiling of Three-Dimensional Brain Tumor Spheroids for Drug Screening

Summary

Here, we establish a metabolic profiling platform integrating three-dimensional (3D) glioma spheroids and imaging-based normalization via extracellular flux analysis. This approach enables more accurate assessment of tumor metabolic responses to drug treatments and provides insights into potential mechanisms of resistance.

Abstract

Brain tumors, especially gliomas, are challenging to treat because of their aggressive nature, complex tumor microenvironment, and resistance to conventional therapies. Traditional two-dimensional (2D) cell cultures often fail to replicate the true tumor environment, leading to inaccurate predictions of drug efficacy. Extracellular flux analysis technology, typically used for real-time metabolic analysis in 2D cultures, measures key metabolic parameters, such as the extracellular acidification rate (ECAR) and oxygen consumption rate (OCR), providing insights into cellular metabolism. The use of 3D models represents a significant advancement, as they more accurately mimic the in vivo tumor environment. The extracellular flux analyzer was adapted to three-dimensional (3D) glioma cell models, enabling the analysis of critical metabolic pathways, including glycolysis and oxidative phosphorylation, in a more physiologically relevant context.

U87 cells were seeded at appropriate densities in a 96-well low-attachment plate and cultured for 5 days. On day 5, 3D spheroid formation was observed via high-content imaging. The successfully formed spheroids were then transferred to a metabolic assay plate coated with poly-L-lysine for metabolic analysis. To improve the accuracy of these measurements, high-content imaging systems assess 3D cell size, allowing for precise normalization of extracellular flux data and minimizing metabolic variations due to differences in cell size. This integrated approach provides a more reliable analysis of glioma cell metabolic responses to drug treatments, revealing potential mechanisms of drug resistance. Ultimately, this methodology offers valuable insights into the metabolic dynamics of gliomas and supports the development of novel, clinically relevant therapeutic strategies.

Introduction

Gliomas, a prevalent and aggressive form of brain tumor, pose significant clinical challenges because of their rapid progression, highly heterogeneous tumor microenvironment, and marked resistance to conventional therapies¹. These complexities necessitate more physiologically relevant experimental models to improve the accuracy of therapeutic evaluations. Traditional two-dimensional (2D) cell culture systems fail to recapitulate the in vivo tumor architecture and cell-cell interactions², often leading to misleading conclusions regarding drug efficacy and tumor biology³.

Protocol

NOTE: The complete specifications of all reagents and consumables are detailed in the Table of Materials.

1. 2D cell culture

1. Maintain U87 cells in minimum essential medium (MEM) supplemented with 10% (v/v) fetal bovine serum (FBS) under sterile conditions. Perform standard passaging procedures once the cells reach 80% confluence.
   NOTE: Throughout the culture process, closely monitor the cell status and exclude cells exhibiting abnormal growth or morphological changes from subsequent experiments.
2. Seed U87 cells into 10 cm cell culture dishes and incubate in a sterile cell culture....

Results

The three most critical steps in the energy metabolism detection process of 3D cell spheroids are the culture of 3D cell spheroids, the spheroid transfer process, and the imaging and quantification of spheroids after detection (Figure 1). Additionally, observing the state of the cell spheroids is highly important. When the experiments were conducted according to the abovementioned experimental procedures, spheroids were detected on the 5^th day (Figure 2

Discussion

The adaptation of extracellular flux analysis to 3D glioma models represents a critical methodological advancement in the study of tumor cell metabolism. While traditional 2D cultures have long served as the foundation for in vitro experimentation, they fail to capture the spatial architecture, cell-cell and cell-matrix interactions, and oxygen and nutrient gradients characteristic of in vivo tumors¹². These features are especially relevant in gliomas, where metabolic reprogrammi.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
10 cm dish	Corning	430167
15 mL centrifuge tube	Corning	430791
50 mL centrifuge tube	Corning	430828
Calcein, AM	Invitrogen	C1430
Countess 3	Thermo Fisher		Automatic Cell Counter
Fetal Bovine Serum	Gibco	A5669701
Harmony 5.2	PerkinElmer		Imaging software
Hoechst 33342	Solarbio	C0031
MEM EBSS Medium	HyClone	SH30024.01
Operetta CLS	PerkinElmer		High-content imaging analysis system
PBS	HyClone	SH30256.01
Poly-D Lysine hydrobromide	Sigma	P7280
Round-bottom ultra-low attachment 96-well plates	Corning	4515
Seahorse Wave Desktop software	Agilent
Seahorse XFe96	Agilent		Extracorporeal metabolic testing machine
Sorvall ST8R	Thermo Fisher		Centrifuge
TRYPSIN 0.25% EDTA	Gibco	25200072
U87MG cell line	National Infrastructure of Cell Resource
XF 1.0 M Glucose Solution, 50 mL	Agilent	103577-100
XF 100 mM Pyruvate Solution, 50 mL	Agilent	103578-100
XF 200 mM Glutamine Solution, 50 mL	Agilent	103579-100
XF Calibrant Solution 500 mL	Agilent	100840-000
XF Cell Mito Stress Test Kit	Agilent	103015-100
XF DMEM Medium, pH 7.4, 500 mL	Agilent	103575-100
XFe96/XF Pro Fluxpak-Detection Probe Array	Agilent	103792-100
XFe96/XF Pro Fluxpak-Metabolic Assay Plates	Agilent	103792-100