Modulation of the cancer cell transcriptome by culture media formulations and cell density

Kim,Seung Wook; Kim,Sun‑Jin; Langley,Robert R.; Fidler,Isaiah J.

doi:10.3892/ijo.2015.2930

Modulation of the cancer cell transcriptome by culture media formulations and cell density

Authors:
- Seung Wook Kim
- Sun‑Jin Kim
- Robert R. Langley
- Isaiah J. Fidler
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Affiliations: Department of Cancer Biology, Metastasis Research Laboratory, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
Published online on: March 17, 2015 https://doi.org/10.3892/ijo.2015.2930
Pages: 2067-2075

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Abstract

We investigated how varying the composition of cell culture formulations and growing cancer cells at different densities might affect tumor cell genotype. Specifically, we compared gene expression profiles generated by human MDA‑MB‑231 breast cancer cells cultured in different media [minimum essential medium (MEM), Dulbecco's modified Eagle's medium (DMEM), or Roswell Park Memorial Institute (RPMI)‑1640 medium] containing different concentrations of fetal bovine serum (FBS) or different sera (equine or bovine) that were grown at different cell densities. More than 2,000 genes were differentially modulated by at least a 2‑fold difference when MDA‑MB‑231 cancer cells were 90% confluent and compared with cultures that were 50% confluent. Altering the concentration of serum produced an even more pronounced effect on MDA‑MB‑231 cancer cell gene expression in that 2,981 genes were differentially expressed in a comparison between cells cultured in 0.1% FBS and same cell density cultures that were maintained in 10% FBS. A comparison between MDA‑MB‑231 cancer cells that were 90% confluent in MEM, DMEM, or RPMI‑1640 media, all containing 10% FBS, resulted in 8,925 differentially expressed genes. Moreover, one‑quarter (25.6%) of genes from our genome‑wide expression analysis were expressed at significantly different levels by cells grown in MEM, DMEM, or RPMI‑1640 media. Genes associated with epithelial‑mesenchymal transition (EMT) were among the genes that were differentially modulated by cells grown in different cell culture formulations and these genes were verified at the protein level. Collectively, these results underscore the importance of accurate reporting and maintenance of uniform culture conditions to ensure reproducible results.

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1	Begley CG and Ellis LM: Drug development: raise standards for preclinical cancer research. Nature. 483:531–533. 2012. View Article : Google Scholar : PubMed/NCBI
2	Prinz F, Schlange T and Asadullah K: Believe it or not: how much can we rely on published data on potential drug targets? Nat Rev Drug Discov. 10:7122011. View Article : Google Scholar : PubMed/NCBI
3	Ioannidis JP: Why most published research findings are false. PLoS Med. 2:e1242005. View Article : Google Scholar : PubMed/NCBI
4	Bissell M: Reproducibility: the risks of the replication drive. Nature. 503:333–334. 2013. View Article : Google Scholar : PubMed/NCBI
5	Davies H, Bignell GR, Cox C, et al: Mutations of the BRAF gene in human cancer. Nature. 417:949–954. 2002. View Article : Google Scholar : PubMed/NCBI
6	Druker BJ, Tamura S, Buchdunger E, et al: Effects of a selective inhibitor of the Abl tyrosine kinase on the growth of Bcr-Abl positive cells. Nat Med. 2:561–566. 1996. View Article : Google Scholar : PubMed/NCBI
7	Engelman JA, Zejnullahu K, Mitsudomi T, et al: MET amplification leads to gefitinib resistance in lung cancer by activating ERBB3 signaling. Science. 316:1039–1043. 2007. View Article : Google Scholar : PubMed/NCBI
8	Gazdar AF, Gao B and Minna JD: Lung cancer cell lines: useless artifacts or invaluable tools for medical science? Lung Cancer. 68:309–318. 2010. View Article : Google Scholar : PubMed/NCBI
9	Gazdar AF, Girard L, Lockwood WW, Lam WL and Minna JD: Lung cancer cell lines as tools for biomedical discovery and research. J Natl Cancer Inst. 102:1310–1321. 2010. View Article : Google Scholar : PubMed/NCBI
10	Langley RR and Fidler IJ: The seed and soil hypothesis revisited - the role of tumor-stroma interactions in metastasis to different organs. Int J Cancer. 128:2527–2535. 2011. View Article : Google Scholar : PubMed/NCBI
11	Cascone T, Herynk MH, Xu L, et al: Upregulated stromal EGFR and vascular remodeling in mouse xenograft models of angiogenesis inhibitor-resistant human lung adenocarcinoma. J Clin Invest. 121:1313–1328. 2011. View Article : Google Scholar : PubMed/NCBI
12	Kim SJ, Kim JS, Park ES, Lee JS, et al: Astrocytes upregulate survival genes in tumor cells and induce protection from chemotherapy. Neoplasia. 13:286–298. 2011.PubMed/NCBI
13	Simon R, Lam A, Li MC, Ngan M, Menenzes S and Zhao Y: Analysis of gene expression data using BRB-ArrayTools. Cancer Inform. 3:11–17. 2007.PubMed/NCBI
14	Livak KJ and Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C(T)) method. Methods. 25:402–408. 2001. View Article : Google Scholar
15	Eisen MB, Spellman PT, Brown PO and Botstein D: Cluster analysis and display of genome-wide expression patterns. Proc Nat Acad Sci USA. 95:14863–14868. 1998. View Article : Google Scholar : PubMed/NCBI
16	Druker BJ and Lydon NB: Lessons learned from the development of an abl tyrosine kinase inhibitor for chronic myelogenous leukemia. J Clin Invest. 105:3–7. 2000. View Article : Google Scholar : PubMed/NCBI
17	American Type Culture Collection Standards Development Organization Workgroup ASN- 0002. Cell line misidentification: the beginning of the end. Nat Rev Cancer. 10:441–448. 2010. View Article : Google Scholar : PubMed/NCBI
18	Barallon R, Bauer SR, Butler J, et al: Recommendation of short tandem repeat profiling for authenticating human cell lines, stem cells, and tissues. In Vitro Cell Dev Biol Anim. 46:727–732. 2010. View Article : Google Scholar : PubMed/NCBI
19	Thiery JP, Acloque H, Huang RY and Nieto MA: Epithelial-mesenchymal transitions in development and disease. Cell. 139:871–890. 2009. View Article : Google Scholar : PubMed/NCBI
20	Tam WL and Weinberg RA: The epigenetics of epithelial-mesenchymal plasticity in cancer. Nat Med. 19:1438–1449. 2013. View Article : Google Scholar : PubMed/NCBI
21	Scheel C and Weinberg RA: Cancer stem cells and epithelial-mesenchymal transition: concepts and molecular links. Semin Cancer Biol. 22:396–403. 2012. View Article : Google Scholar : PubMed/NCBI
22	Tang L, Li H, Gou R, Cheng G, Guo Y, Fang Y and Chen F: Endothelin-1 mediated high glucose-induced epithelial-mesenchymal transition in renal tubular cells. Diabetes Res Clin Pract. 104:176–182. 2014. View Article : Google Scholar : PubMed/NCBI
23	Yu MA, Shin KS, Kim JH, et al: HGF and BMP-7 ameliorate high glucose-induced epithelial-to-mesenchymal transition of peritoneal mesothelium. J Am Soc Nephrol. 20:567–581. 2009. View Article : Google Scholar : PubMed/NCBI
24	Liu PP, Liao J, Tang ZJ, et al: Metabolic regulation of cancer cell side population by glucose through activation of the Akt pathway. Cell Death Differ. 21:124–135. 2014. View Article : Google Scholar
25	Kim TH, Kim HI, Soung YH, Shaw LA and Chung J: Integrin (alpha6beta4) signals through Src to increase expression of S100A4, a metastasis-promoting factor: implications for cancer cell invasion. Mol Cancer Res. 7:1605–1612. 2009. View Article : Google Scholar : PubMed/NCBI
26	Hoffmann E, Dittrich-Breiholz O, Holtmann H and Kracht M: Multiple control of interleukin-8 gene expression. J Leukoc Biol. 72:847–855. 2002.PubMed/NCBI
27	Waugh DJ and Wilson C: The interleukin-8 pathway in cancer. Clin Cancer Res. 14:6735–6741. 2008. View Article : Google Scholar : PubMed/NCBI
28	Singh JK, Simões BM, Howell SJ, Farnie G and Clarke RB: Recent advances reveal IL-8 signaling as a potential key to targeting breast cancer stem cells. Breast Cancer Res. 15:2102013. View Article : Google Scholar : PubMed/NCBI