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Media type:
E-Article
Title:
A high‐throughput imaging platform to characterize extracellular pH in organotypic three‐dimensional in vitro models of liver cancer
Contributor:
Savic, Lynn Jeanette;
Schobert, Isabel Theresa;
Hamm, Charlie Alexander;
Adam, Lucas Christoph;
Hyder, Fahmeed;
Coman, Daniel
Published:
Wiley, 2021
Published in:
NMR in Biomedicine, 34 (2021) 3
Language:
English
DOI:
10.1002/nbm.4465
ISSN:
0952-3480;
1099-1492
Origination:
Footnote:
Description:
Given the extraordinary nature of tumor metabolism in hepatocellular carcinoma and its impact on oncologic treatment response, this study introduces a novel high‐throughput extracellular pH (pHe) mapping platform using magnetic resonance spectroscopic imaging in a three‐dimensional (3D) in vitro model of liver cancer. pHe mapping was performed using biosensor imaging of redundant deviation in shifts (BIRDS) on 9.4 T and 11.7 T MR scanners for validation purposes. 3D cultures of four liver cancer (HepG2, Huh7, SNU475, VX2) and one hepatocyte (THLE2) cell line were simultaneously analyzed (a) without treatment, (b) supplemented with 4.5 g/L d‐glucose, and (c) treated with anti‐glycolytic 3‐bromopyruvate (6.25, 25, 50, 75, and 100 μM). The MR results were correlated with immunohistochemistry (GLUT‐1, LAMP‐2) and luminescence‐based viability assays. Statistics included the unpaired t‐test and ANOVA test. High‐throughput pHe imaging with BIRDS for in vitro 3D liver cancer models proved feasible. Compared with non‐tumorous hepatocytes (pHe = 7.1 ± 0.1), acidic pHe was revealed in liver cancer (VX2, pHe = 6.7 ± 0.1; HuH7, pHe = 6.8 ± 0.1; HepG2, pHe = 6.9 ± 0.1; SNU475, pHe = 6.9 ± 0.1), in agreement with GLUT‐1 upregulation. Glucose addition significantly further decreased pHe in hyperglycolytic cell lines (VX2, HepG2, and Huh7, by 0.28, 0.06, and 0.11, respectively, all p < 0.001), whereas 3‐bromopyruvate normalized tumor pHe in a dose‐dependent manner without affecting viability. In summary, this study introduces a non‐invasive pHe imaging platform for high‐yield screening using a translational 3D liver cancer model, which may help reveal and target mechanisms of therapy resistance and inform personalized treatment of patients with hepatocellular carcinoma.