3D Modeling: Insights into the Metabolic Reprogramming of Cholangiocarcinoma Cells

Developing accurate in vitro models that replicate the in vivo tumor environment is essential for advancing cancer research and therapeutic development. Traditional 2D cell cultures often fail to capture the complex structural and functional heterogeneity of tumors, limiting the translational relevance of findings. In contrast, 3D culture systems, such as spheroids, provide a more physiologically relevant context by replicating key aspects of the tumor microenvironment. This study aimed to compare the metabolism of three intrahepatic cholangiocarcinoma cell lines in 2D and 3D cultures to identify metabolic shifts associated with spheroid formation. Cells were cultured in 2D on adhesion plates and in 3D using ultra-low attachment plates. Metabolic exchange rates were measured using NMR, and intracellular metabolites were analyzed using LC-MS. Significant metabolic differences were observed between 2D and 3D cultures, with notable changes in central carbon and glutathione metabolism in 3D spheroids. The results suggest that 3D cultures, which more closely mimic the in vivo environment, may offer a more accurate platform for cancer research and drug testing.

Authors

Institutions

Publication Details

Journal
Cells
Published
2024-09-13
DOI
https://doi.org/10.3390/cells13181536
Citations
4
Primary Topic
Cancer, Hypoxia, and Metabolism
Type
article
Field-Weighted Citation Impact
1.14

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

3D Modeling: Insights into the Metabolic Reprogramming of Cholangiocarcinoma Cells

Simona Cesaroni, Elena Sacco, Daniel O. Cicero, Daniela Gaglio et al.
4 citations
Cells
Cancer, Hypoxia, and Metabolism
1.14
article

3D Modeling: Insights into the Metabolic Reprogramming of Cholangiocarcinoma Cells

Simona Cesaroni, Elena Sacco, Daniel O. Cicero, Daniela Gaglio, Greta Petrella, Mirella Pastore, Valentina Pasquale, Marco Vanoni, Chiara Raggi, Fabio Marra, Marcella Bonanomi, Giorgia Ciufolini, Serena Zampieri
article en
4 citations

Abstract

Developing accurate in vitro models that replicate the in vivo tumor environment is essential for advancing cancer research and therapeutic development. Traditional 2D cell cultures often fail to capture the complex structural and functional heterogeneity of tumors, limiting the translational relevance of findings. In contrast, 3D culture systems, such as spheroids, provide a more physiologically relevant context by replicating key aspects of the tumor microenvironment. This study aimed to compare the metabolism of three intrahepatic cholangiocarcinoma cell lines in 2D and 3D cultures to identify metabolic shifts associated with spheroid formation. Cells were cultured in 2D on adhesion plates and in 3D using ultra-low attachment plates. Metabolic exchange rates were measured using NMR, and intracellular metabolites were analyzed using LC-MS. Significant metabolic differences were observed between 2D and 3D cultures, with notable changes in central carbon and glutathione metabolism in 3D spheroids. The results suggest that 3D cultures, which more closely mimic the in vivo environment, may offer a more accurate platform for cancer research and drug testing.

CellsVol. 13(18)
University of Rome Tor Vergata (IT), Institute of Molecular Bioimaging and Physiology (IT), University of Florence (IT), University of Milano-Bicocca (IT)
European Commission, Associazione Italiana per la Ricerca sul Cancro, Universität Regensburg, Fondazione Italiana per la Ricerca sul Cancro
Openalex Percentile: Top 21%
Cancer, Hypoxia, and Metabolism
1.14
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.