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Updated: Jun 22, 2026

Induction and Testing of Hypoxia in Cell Culture
Published on: August 12, 2011
Hypoxia and the metabolic phenotype of prostate cancer cells
L H Higgins1, H G Withers, A Garbens
1Department of Biology, Queen's University, Kingston, ON, Canada K7L 3N6.
Abstract:
Many cancer cells have an unusual ability to grow in hypoxia, but the origins of this metabolic phenotype remain unclear. We compared the metabolic phenotypes of three common prostate cancer cell models (LNCaP, DU145, PC3), assessing energy metabolism, metabolic gene expression, and the response to various culture contexts (in vitro and xenografts). LNCaP cells had a more oxidative phenotype than PC3 and DU145 cells based upon respiration, lactate production, [ATP], metabolic gene expression, and sensitivity of these parameters to hypoxia. PC3 and DU145 cells possessed similar Complex II and mtDNA levels, but lower Complex III and IV activities, and were unresponsive to dinitrophenol or dichloroacetate, suggesting that their glycolytic phenotype is due to mitochondrial dysfunction rather than regulation. High passage under normoxia converted LNCaP from oxidative to glycolytic cells (based on respiration and lactate production), and altered metabolic gene expression. Though LNCaP-derived cells differed from the parental line in mitochondrial enzyme activities, none differed in mitochondrial content (assessed as cardiolipin levels). When LNCaP-derived cells were grown as xenografts in immunodeficient mice, there were elements of a hypoxic response (e.g., elevated VEGF mRNA) but line-specific changes in expression of select glycolytic, mitochondrial and fatty acid metabolic genes. Low oxygen in vitro did not influence the mRNA levels of SREBP axis, nor did it significantly alter triglyceride production in any of the cell lines suggesting that the pathway of de novo fatty acid synthesis is not directly upregulated by hypoxic conditions. Collectively, these studies demonstrate important differences in the metabolism of these prostate cancer models. Such metabolic differences would have important ramifications for therapeutic strategies involving metabolic targets.
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