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An Optimized Workflow for the Analysis of Metabolic Fluxes in Cancer Spheroids Using Seahorse Technology

Authors :
Gloria Campioni
Valentina Pasquale
Stefano Busti
Giacomo Ducci
Elena Sacco
Marco Vanoni
Campioni, G
Pasquale, V
Busti, S
Ducci, G
Sacco, E
Vanoni, M
Source :
Cells, Cells; Volume 11; Issue 5; Pages: 866
Publication Year :
2022

Abstract

Three-dimensional cancer models, such as spheroids, are increasingly being used to study cancer metabolism because they can better recapitulate the molecular and physiological aspects of the tumor architecture than conventional monolayer cultures. Although Agilent Seahorse XFe96 (Agilent Technologies, Santa Clara, CA, United States) is a valuable technology for studying metabolic alterations occurring in cancer cells, its application to three-dimensional cultures is still poorly optimized. We present a reliable and reproducible workflow for the Seahorse metabolic analysis of three-dimensional cultures. An optimized protocol enables the formation of spheroids highly regular in shape and homogenous in size, reducing variability in metabolic parameters among the experimental replicates, both under basal and drug treatment conditions. High-resolution imaging allows the calculation of the number of viable cells in each spheroid, the normalization of metabolic parameters on a per-cell basis, and grouping of the spheroids as a function of their size. Multivariate statistical tests on metabolic parameters determined by the Mito Stress test on two breast cancer cell lines show that metabolic differences among the studied spheroids are mostly related to the cell line rather than to the size of the spheroid. The optimized workflow allows high-resolution metabolic characterization of three-dimensional cultures, their comparison with monolayer cultures, and may aid in the design and interpretation of (multi)drug protocols.

Details

ISSN :
20734409
Database :
OpenAIRE
Journal :
Cells
Accession number :
edsair.doi.dedup.....7668554d4a2b3f0ee686108f4072945f
Full Text :
https://doi.org/10.3390/cells11050866