James D Barnett1, Santosh K Bharti1, Balaji Krishnamachary1, Flonne Wildes1, Yelena Mironchik1, Marie-France Penet1,2, and Zaver Bhujwalla 1,2,3
1Division of Cancer Imaging Research, The Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, MD, United States, 2Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD, United States, 3Department of Radiation Oncology and Molecular Radiation Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
Synopsis
Cyclooxygenase-2 (COX-2) is an
inducible enzyme that mediates the inflammatory response of cells. COX-2 overexpression is associated with poor
prognosis in breast cancers. Here we
have investigated the effect of tumor COX-2 overexpression on spleen metabolism,
using 1H magnetic resonance spectroscopy (MRS), as part of an
overall focus on understanding the impact of cancers on inducing metabolic
changes in critical organs. We focused
on the spleen since it plays a critical role in the immune response and
detected distinct differences in glutamate and lactate with COX-2
overexpression.
Introduction
Cyclooxygenase-2
(COX-2) is an inducible enzyme that catalyzes synthesis of proinflammatory mediators
such as prostaglandins, thromboxanes, and cytokines. COX-2 overexpression is
frequently observed in human cancers and is associated with poor prognosis and
progression [1]. We generated genetically modified human triple negative breast
cancer (TNBC) cells to overexpress COX-2 to better investigate the role of
COX-2 in promoting cancer aggressiveness [2]. Previously, we found that
modulation of COX-2 expression alters the choline and lipid metabolism in
breast cancer cells [3]. We used 1H magnetic resonance spectroscopy
(MRS) to investigate the effects of tumor COX-2 overexpression on spleen
metabolism. This will provide a broader understanding of how COX-2 expressing cancers
can impact the metabolic profile of vital organs that form the tumor
macroenvironment. Methods
A vector
expressing the COX-2 gene was cloned and constructed to establish triple
negative SUM-149 cells stably overexpressing COX-2 (SUM-149-COX-2) or cells with
an empty vector (SUM-149-EV) as previously reported [2]. These cells were
inoculated in the mammary fat pad of SCID mice. Mouse organs were harvested
once tumor volumes were approximately 500 mm3. Spleen samples were
cryopulverized in liquid nitrogen followed by dual-phase extraction using
methanol, chloroform and water.
Water-soluble metabolites were identified through 1H MRS
performed on a 750 MHz spectrometer. Data were acquired on a Bruker Avance III
750 MHz (17.6T) MR spectrometer equipped with a 5 mm broad band inverse (BBI)
probe. Data processing, analysis and quantification were performed with Topspin
3.5 software. Results
Representative spleen 1H MR spectra obtained from a
SUM-149-COX-2 tumor-bearing mouse and a SUM-149-EV tumor-bearing mouse are
shown in Figure 1 for (A) the glutamate region and (B) for the lactate region. Data
summarized from the spleens of four mice in the SUM-149-EV group and five mice
in the SUM-149-COX-2 group are shown in Figure 2 for (A) glutamate, (B)
glutamine, (C) glutamine/glutamate, (D) lactate, (E) glucose and (F)
glucose/lactate. These data demonstrate the significant effects of tumor COX-2
overexpression on glutamine/glutamate and glucose metabolism in the spleen. Discussion
Our data identified a significant increase of glutamate and lactate and
a significant decrease of the glutamine/glutamate and glucose/lactate ratios in
the spleens of mice with COX-2 overexpressing SUM-149 tumors compared to SUM-EV
tumors. These metabolic changes must have been affected by the tumor secretome
and highlight the impact cancers may have on critical organs. The spleen is a
secondary lymphoid organ important for immunometabolism and T cell activation. Transport
of glutamine and its conversion are required for metabolic homeostasis during
sepsis and inflammation [4]. The metabolic changes observed here suggest that
the COX-2 tumor secretome may be affecting spleen metabolism and may
systemically contribute to the poor prognosis associated with these cancers. These
insights can, in part, be applied in metabolic strategies to improve quality of
life and treatment outcome.Acknowledgements
Supported by
NIH R01CA193365 and R35CA209960.References
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al., Anticancer research. 2011;31(12):4359-67. 2. Krishnamachary B et al.,
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