31P-Magnetic resonance spectra of ovarian cancer cells exposed to chemotherapy within a three-dimensional Matrigel construct

Abramov,Yoram; Carmi,Shani; Cohen,Jack  S.; Anteby,Shaoul  O.; Ringel,Israel

doi:10.3892/or.2012.1810

31P-Magnetic resonance spectra of ovarian cancer cells exposed to chemotherapy within a three-dimensional Matrigel construct

Authors:
- Yoram Abramov
- Shani Carmi
- Jack S. Cohen
- Shaoul O. Anteby
- Israel Ringel
View Affiliations

Affiliations: Department of Obstetrics and Gynecology, Carmel Medical Center, Technion University, Rappaport Faculty of Medicine, Haifa, Israel, Department of Pharmacology, Hadassah Hebrew University Medical School, Jerusalem, Israel, Department of Obstetrics and Gynecology, Hadassah Hebrew University Medical School, Jerusalem, Israel
Published online on: May 10, 2012 https://doi.org/10.3892/or.2012.1810
Pages: 735-741

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )

Metrics: Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )

Cited By (CrossRef): 0 citations Loading Articles...

Abstract

We aimed to determine the metabolic profile and effects of chemotherapy on ovarian cancer cell metabolism in a three-dimensional (3D) vs. a two-dimensional (2D) construct using 31P-magnetic resonance spectroscopy (MRS). Three ovarian cancer cell lines were embedded in a 3D perfused Matrigel construct or grown in a 2D monolayer. Metabolic differences between the three cell lines were determined using 31P-MRS both in the 3D and in the 2D constructs. Cells were incubated with three different cytotoxic drugs at LC50 for 44 h and evaluated for metabolic changes using 31P-MRS. While the 3D construct allowed MRS assessment of viable cells, the 2D monolayer permitted evaluation of non-viable cell extracts. In both cells embedded in Matrigel (CEM) and cells grown in monolayers (CGM) different cancer cell lines showed characteristic metabolic fingerprints, which differed significantly between CEM and CGM. In contrast to the cell monolayer, CEM allowed continuous monitoring of the changes in 31P-MRS spectra over time following exposure to chemotherapy, demonstrating a progressive decrease in specific phosphorylated metabolites. The metabolic response of CEM and CGM to various antimitotic agents was significantly different. We conclude that different ovarian cancer cell lines show characteristic 31P-MRS fingerprints and specific metabolic changes in response to cytotoxic drug treatment. The perfused 3D Matrigel construct is superior to the 2D tissue monolayer for 31P-MRS studies, because it simulates the in vivo conditions more closely and facilitates MRS evaluation of viable cells as well as continuous monitoring of metabolic changes in response to chemotherapy over time.

View Figures

View References

1	National Cancer Institute. www.cancer.gov/cancertopics/types/ovarianurisimplewww.cancer.gov/cancertopics/types/ovarian. A snapshot of ovarian cancer. Last updated, October 2011.
2	Jemal A, Siegel R, Ward E, Hao Y, Xu J and Thun MJ: Cancer statistics 2009. CA Cancer J Clin. 59:225–249. 2009. View Article : Google Scholar
3	Bast RC, Hennessy B and Mills GB: The biology of ovarian cancer: new opportunities for translation. Nat Rev Cancer. 9:415–428. 2009. View Article : Google Scholar : PubMed/NCBI
4	Chi DS, Eisenhauer EL, Zivanovic O, et al: Improved progression-free and overall survival in advanced ovarian cancer as a result of a change in surgical paradigm. Gynecol Oncol. 114:26–31. 2009. View Article : Google Scholar
5	Ng TC and Glickson JD: Shielded solenoidal probe for in vivo NMR studies of solid tumors. Magnet Reson Med. 2:169–175. 1985. View Article : Google Scholar : PubMed/NCBI
6	Glickson JD, Evanochko WT, Sakai TT and Ng TC: In vivo NMR studies of RIF-1 tumors. Magnetic Resonance in Cancer. Allen PS, Boisvert DPJ and Lentie BC: Pergamon Press; Toronto: pp. 71–82. 1986
7	Maris JM, Evans AE, McLaughlin AC, D’Angio GJ, Bolinger L, Manos H and Chance B: 31P nuclear magnetic resonance spectroscopic investigation of human neuroblastoma in situ. N Engl J Med. 312:1500–1505. 1985. View Article : Google Scholar : PubMed/NCBI
8	Evanochko WT, Ng TC, Lilly MB, Lawson AJ, Corbett TH, Durant JR and Glickson JD: In vivo ³¹P NMR study of the metabolism of murine mammary 16/C adenocarcinoma and its response to chemotherapy, x-radiation, and hyperthermia. Proc Natl Acad Sci USA. 80:334–338. 1983.
9	Okunieff PG, Koutcher JA, Gerweck L, McFarland E, Hitzig B, Urano M, Brady T, Neuringer L and Suit HD: Tumor size dependent changes in a murine fibrosarcoma: use of in vivo ³¹P NMR for non-invasive evaluation of tumor metabolic status. Int J Radiat Oncol Biol Phys. 12:793–799. 1986. View Article : Google Scholar : PubMed/NCBI
10	Ng TC, Evanochko WT, Hiramoto RN, Chanta VK, Lilly MB, Lawson AJ, Corbett TH, Durant JR and Glickson JD: P NMR spectroscopy of in vivo tumors. J Magnet Res. 49:271–286. 1986.
11	Sterin M, Cohen JS, Mardor Y, Berman E and Ringel I: Levels of phospholipid metabolites in breast cancer cells treated with antimitotic drugs: a ³¹P-magnetic resonance spectroscopy study. Cancer Res. 61:7536–7543. 2001.PubMed/NCBI
12	Massuger LFAG, van Vierzen PBJ, Engelke U, Heerschap A and Wevers R: 1H-magnetic resonance spectroscopy: a new technique to discriminate benign from malignant ovarian tumors. Cancer. 82:1726–1730. 1998. View Article : Google Scholar : PubMed/NCBI
13	Boss EA, Moolenaar SH, Massuger LF, Boonstra H, Engelke UF, de Jong JG and Wevers RA: High-resolution proton nuclear magnetic resonance spectroscopy of ovarian cyst fluid. NMR Biomed. 13:297–305. 2000. View Article : Google Scholar : PubMed/NCBI
14	Yamada KM and Cukierman E: Modeling tissue morphogenesis and cancer in 3D. Cell. 130:601–610. 2007. View Article : Google Scholar : PubMed/NCBI
15	Ritter CA, Perez-Torres M, Rinehart C, Guix M, Dugger T, Engelman JA, et al: Human breast cancer cells selected for resistance to trastuzumab in vivo overexpress epidermal growth factor receptor and ErbB ligands and remain dependent on the ErbB receptor network. Clin Cancer Res. 13:4909–4919. 2007. View Article : Google Scholar
16	Cohen JS, Jaroszewski JW, Kaplan O, Ruiz-Cabello J and Collier S: A history of biological applications of NMR spectroscopy. J Prog Nucl Magn Reson Spectrosc. 28:53–85. 1995. View Article : Google Scholar
17	Maymon R, Bar-Shira Maymon B, Holzinger M, Tartakovsky B and Leibovici J: Augmentative effects of intracellular chemotherapy penetration combined with hyperthermia in human ovarian cancer cells lines. Gynecol Oncol. 55:265–270. 1994. View Article : Google Scholar
18	Podo F: Tumor phospholipid metabolism. NMR Biomed. 12:413–439. 1999. View Article : Google Scholar
19	Nakayama S and Clark JF: Smooth muscle and NMR review: an overview of smooth muscle metabolism. Mol Cell Biochem. 244:17–30. 2003. View Article : Google Scholar : PubMed/NCBI
20	Cho KR and Shih IeM: Ovarian cancer. Annu Rev Pathol. 4:287–313. 2009. View Article : Google Scholar
21	Berek JS and Bast RCJ: Ovarian cancer. Cancer Medicine. Kufe DW, Pollack RE, Weichselbaum RR, Bast RCJ, Gansler TS, Holland JF and Frei EI: 6th edition. BC Decker; Hamilton, Ontario: pp. 1831–1861. 2003
22	Mackinnon WB, Russell P, May GL and Mountford CE: Characterization of human ovarian epithelial tumors (ex vivo) by proton magnetic resonance spectroscopy. Int J Gynecol Cancer. 5:211–221. 1995. View Article : Google Scholar : PubMed/NCBI
23	Wallace JC, Raaphorst GP, Somorjai RL, Ng CE, Fung Kee Fung M, Senterman M and Smith IC: Classification of ¹H MR spectra of biopsies from untreated and recurrent ovarian cancer using linear discriminant analysis. Magn Reson Med. 38:569–576. 1997.
24	Kim JB: Three-dimensional tissue culture models in cancer biology. Semin Cancer Biol. 15:365–377. 2005. View Article : Google Scholar : PubMed/NCBI
25	Debnath J and Brugge JS: Modelling glandular epithelial cancers in three-dimensional cultures. Nat Rev Cancer. 5:675–688. 2005. View Article : Google Scholar : PubMed/NCBI
26	Lee GY, Kenny PA, Lee EH and Bissell MJ: Three-dimensional culture models of normal and malignant breast epithelial cells. Nat Methods. 4:359–365. 2007. View Article : Google Scholar : PubMed/NCBI
27	Streuli CH, Schmidhauser C, Bailey N, et al: Laminin mediates tissue-specific gene expression in mammary epithelia. J Cell Biol. 129:591–603. 1995. View Article : Google Scholar : PubMed/NCBI
28	Debnath J, Mills KR, Collins NL, Reginato MJ, Muthuswamy SK and Brugge JS: The role of apoptosis in creating and maintaining luminal space within normal and oncogene-expressing mammary acini. Cell. 111:29–40. 2002. View Article : Google Scholar : PubMed/NCBI
29	Ohmori T, Yang JL, Price JO and Arteaga CL: Blockade of tumor cell transforming growth factor-beta enhances cell cycle progression and sensitizes human breast carcinoma cells to cytotoxic chemotherapy. Exp Cell Res. 245:350–359. 1998. View Article : Google Scholar : PubMed/NCBI
30	Ruiz-Cabello J, Berghmans K, Kaplan O, Lippman ME, Clarke R and Cohen JS: Hormone dependence of breast cancer cells and the effects of tamoxifen and estrogen: ³¹P NMR studies. Breast Cancer Res Treat. 33:209–217. 1995. View Article : Google Scholar : PubMed/NCBI
31	Pike MC, Kredich NM and Snyderman R: Influence of cytoskeletal assembly on phosphatidylcholine synthesis in intact phagocytic cells. Cell. 20:373–379. 1980. View Article : Google Scholar : PubMed/NCBI