Transitions from mono- to co- to tri-culture uniquely affect gene expression in breast cancer, stromal, and immune compartments

Biomedical Microdevices

Volumn 18, Issue 4, 2016, Pages

  Regier, Mary C ^a,b   Maccoux, Lindsey J ^a,b,c   Weinberger, Emma M ^a,b   Regehr, Keil J ^a,b   Berry, Scott M ^a,b   Beebe, David J ^a,b,d   Alarid, Elaine T ^a,c,d  

^a University of Wisconsin Health   (United States)

^b University of Wisconsin Madison   (United States)

^c UNIVERSITY OF WISCONSIN MADISON   (United States)

^d UNIVERSITY OF WISCONSIN   (United States)

Author keywords

Compartmentalization; Heterotypic interactions; Microfluidic; Multi culture; Principal component analysis

Indexed keywords

CELLS; CYTOLOGY; DISEASES; GENES; MICROFLUIDICS; PRINCIPAL COMPONENT ANALYSIS; TUMORS;

COMPARTMENTALIZATION; CULTURE PARAMETERS; DISEASE INITIATIONS; FUNCTIONAL RELEVANCE; GENE EXPRESSION DATA; GENE EXPRESSION PATTERNS; ITERATIVE APPROACH; PARACRINE INTERACTIONS;

GENE EXPRESSION;

ARTICLE; BREAST CANCER; CELL COMMUNICATION; CELL COMPARTMENTALIZATION; COCULTURE; CONTROLLED STUDY; GENE EXPRESSION; HUMAN; HUMAN CELL; IN VITRO STUDY; MCF 7 CELL LINE; MICROFLUIDIC ANALYSIS; MICROFLUIDICS; MONOCULTURE; PARACRINE SIGNALING; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; STROMA CELL; TRICULTURE; TUMOR MICROENVIRONMENT; BREAST TUMOR; FEMALE; GENE EXPRESSION REGULATION; GENETICS; METABOLISM; TUMOR CELL LINE;

BREAST NEOPLASMS; CELL LINE, TUMOR; COCULTURE TECHNIQUES; FEMALE; GENE EXPRESSION REGULATION, NEOPLASTIC; HUMANS; PRINCIPAL COMPONENT ANALYSIS; STROMAL CELLS; TUMOR MICROENVIRONMENT;

EID: 84979031905     PISSN: 13872176     EISSN: 15728781     Source Type: Journal    
DOI: 10.1007/s10544-016-0083-x     Document Type: Article

References (82)

1. H. Abdi, L. J. Williams, Principal component analysis. Wiley Interdisciplinary Reviews: Computational Statistics 2(4), 433–459 (2010)
2. K. Amornsupak et al., Cancer-associated fibroblasts induce high mobility group box 1 and contribute to resistance to doxorubicin in breast cancer cells. BMC Cancer 14, 955 (2014)
3. R. E. Bachelder et al., Vascular endothelial growth factor is an autocrine survival factor for neuropilin-expressing breast carcinoma cells. Cancer Res. 61(15), 5736–5740 (2001)
4. F. R. Balkwill, T. Hagemann, The tumor microenvironment at a glance. J. Cell Sci. 125(23), 5591–5596 (2012)
5. N. Beliakova-Bethell et al., The effect of cell subset isolation method on gene expression in leukocytes. Cytometry Part A 85(1), 94–104 (2014)
6. S. M. Berry et al., Streamlining gene expression analysis: integration of co-culture and mRNA purification. Integrative Biology 6(2), 224–231 (2014)Available at: http://www.ncbi.nlm.nih.gov/pubmed/24413730
7. S. Bersini et al., A microfluidic 3D invitro model for specificity of breast cancer metastasis to bone. Biomaterials 35(8), 2454–2461 (2014)
8. J. Bin Kim, R. Stein, M. O’Hare, Three-dimensional in vitro tissue culture models of breast cancer - a review. Breast Cancer Res. Treat. 85, 281–291 (2004)Available at: http://discovery.ucl.ac.uk/36475/
9. L. L. Bischel, D. J. Beebe, K. E. Sung, Microfluidic model of ductal carcinoma in situ with 3D, organotypic structure. BMC Cancer 15(1), 1–10 (2015)Available at: http://www.biomedcentral.com/1471-2407/15/12
10. P. Boström et al., MMP-1 expression has an independent prognostic value in breast cancer. BMC Cancer 11(1), p. 1 (2011)
11. S. Busch et al., TGF-beta receptor type-2 expression in cancer-associated fibroblasts regulates breast cancer cell growth and survival and is a prognostic marker in pre-menopausal breast cancer. Oncogene 34(1), 27–38 (2015)
12. S. P. Cavnar et al., Microfluidic source-sink model reveals effects of biophysically distinct CXCL12 isoforms in breast cancer chemotaxis. Integr. Biol. 6(5), 564–576 (2014). doi:10.1039/C4IB00015C
13. S. Chandrasekaran et al., Effect of homotypic and heterotypic interaction in 3D on the E-selectin mediated adhesive properties of breast cancer cell lines. Biomaterials 33(35), 9037–9048 (2012). doi:10.1016/j.biomaterials.2012.08.052
14. Z. M. Che et al., Collagen-based co-culture for invasive study on cancer cells-fibroblasts interaction. Biochem. Biophys. Res. Commun. 346(1), 268–275 (2006)
15. S. Y. C. Choi et al., Lessons from patient-derived xenografts for better in vitro modeling of human cancer. Adv. Drug Deliv. Rev. 79-80, 222–237 (2014)Available at: http://linkinghub.elsevier.com/retrieve/pii/S0169409X14002075
16. Y. Choi et al., A microengineered pathophysiological model of early-stage breast cancer. Lab Chip 15(16), 3350–3357 (2015). doi:10.1039/C5LC00514K
17. G. S. DeLassus, H. Cho, G. L. Eliceiri, New signaling pathways from cancer progression modulators to mRNA expression of matrix metalloproteinases in breast cancer cells. J. Cell. Physiol. 226(12), 3378–3384 (2011)
18. M. Domenech et al., Cellular observations enabled by microculture: paracrine signaling and population demographics. Integrative biology: quantitative biosciences from nano to macro 1(3), 267–274 (2009)
19. M. Domenech et al., Hedgehog signaling in myofibroblasts directly promotes prostate tumor cell growth. Integrative Biology 4(2), p.142 (2012)
20. C. L. Downey et al., The prognostic significance of tumour – stroma ratio in oestrogen receptor-positive breast cancer. Br. J. Cancer 110(7), 1744–1747 (2014). doi:10.1038/bjc.2014.69
21. D. C. Duffy et al., Rapid prototyping of microfluidic systems in poly (dimethylsiloxane). Analytical … 70(23), 4974–4984 (1998). doi:10.1021/ac980656z
22. G. Edakuni et al., Expression of the hepatocyte growth factor/c-met pathway is increased at the cancer front in breast carcinoma. Pathol. Int. 51(3), 172–178 (2001)
23. B. Fernandez-Garcia et al., Expression and prognostic significance of fibronectin and matrix metalloproteases in breast cancer metastasis. Histopathology 64(4), 512–522 (2014)
24. T. Fiaschi et al., Reciprocal metabolic reprogramming through lactate shuttle coordinately influences tumor-stroma interplay. Cancer Res. 72(19), 5130–5140 (2012)
25. G. Finak et al., Stromal gene expression predicts clinical outcome in breast cancer. Nat. Med. 14(5), 518–527 (2008)
26. J. M. Fleming et al., Paracrine interactions between primary human macrophages and human fibroblasts enhance murine mammary gland humanization in vivo. Breast Cancer Res 14(3), p.R97 (2012)
27. O. Frings et al., Prognostic significance in breast cancer of a Gene signature capturing stromal PDGF signaling. Am. J. Pathol. 182(6), 2037–2047 (2013)Available at: http://www.sciencedirect.com/science/article/pii/S000294401300196X
28. H. Fujita et al., Tumor-stromal interactions with direct cell contacts enhance proliferation of human pancreatic carcinoma cells. Cancer Sci. 100(12), 2309–2317 (2009)
29. M. Furukawa et al., Lung epithelial cells induce both phenotype alteration and senescence in breast cancer cells. PloS one 10(1), p.e0118060 (2015)
30. S. Goswami et al., Macrophages promote the invasion of breast carcinoma cells via a Colony-stimulating factor-1 / epidermal growth factor paracrine loop. Cancer Res. 65(12), 5278–5284 (2005)
31. C. Guido et al., Metabolic reprogramming of cancer-associated fibroblasts by TGF-β drives tumor growth: connecting TGF-β signaling with “Warburg-like” cancer metabolism and L-lactate production. Cell Cycle 11(16), 3019–3035 (2012)
32. S. Guo et al., Vascular endothelial growth factor receptor-2 in breast cancer. Biochimica et Biophysica Acta (BBA)-Reviews on Cancer 1806(1), 108–121 (2010)
33. T. Hagemann et al., Enhanced invasiveness of breast cancer cell lines upon co-cultivation with macrophages is due to TNF-α dependent up-regulation of matrix metalloproteases. Carcinogenesis 25(8), 1543–1549 (2004)
34. T. Hagemann et al., Ovarian cancer cells polarize macrophages toward a tumor-associated phenotype. J. Immunol. 176(8), 5023–5032 (2006)
35. A. C. Hielscher, C. Qiu, S. Gerecht, Breast cancer cell-derived matrix supports vascular morphogenesis. American journal of physiology. Cell physiology 302(8), C1243–C1256 (2012)Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3774551{&}tool=pmcentrez{&}rendertype=abstract
36. A. Hielscher et al., Hypoxia affects the structure of breast cancer cell-derived matrix to support Angiogenic responses of endothelial cells. J Carcinog Mutagen 18(9), 1199–1216 (2013)
37. M. Hollmén et al., Characterization of macrophage-cancer cell crosstalk in estrogen receptor positive and triple-negative breast cancer. Scientific reports 5 (2015)
38. H. Hotelling, Analysis of a complex of statistical variables into principal components. J. Educ. Psychol. 24(6), 417–441 (1933)
39. C.-H. Hsu et al., TET1 suppresses cancer invasion by activating the tissue inhibitors of metalloproteinases. Cell Rep. 2(3), 568–579 (2012)
40. J. Jacquemier et al., Expression of the FGFR1 gene in human breast-carcinoma cells. Int. J. Cancer 59(3), 373–378 (1994)
41. J. S. Jeon et al., Human 3D vascularized organotypic microfluidic assays to study breast cancer cell extravasation. Proc. Natl. Acad. Sci. 112(1), 214–219 (2015). doi:10.1073/pnas.1417115112
42. I. T. Jolliffe, Principal component analysis 2nd ed (Springer-Verlag, New York, Available at: https://search.library.wisc.edu/catalog/9999358336021212002)
43. S. Kim et al., Engineering of functional, perfusable 3D microvascular networks on a chip. Lab Chip 13(8), 1489–1500 (2013a)Available at: http://pubs.rsc.org.globalproxy.cvt.dk/en/content/articlehtml/2013/lc/c3lc41320a
44. S. Kim et al., FGFR2 promotes breast tumorigenicity through maintenance of breast tumor-initiating cells. PloS one 8(1), p.e51671 (2013b)
45. V. Krishnan et al., Dynamic interaction between breast cancer cells and osteoblastic tissue: comparison of two-and three-dimensional cultures. J. Cell. Physiol. 226(8), 2150–2158 (2011)
46. W. J. Krzanowski, 2000. Principles of multivariate analysis: a user’s perspective, rev. ed. Oxford [Oxfordshire] (Oxford University Press, New York, 2000) Available at: https://search.library.wisc.edu/catalog/999932692202121
47. J. D. Lang et al., Hormonally responsive breast cancer cells in a microfluidic co-culture model as a sensor of microenvironmental activity. Integrative Biology 5(5), pp.807–pp.816 (2013)Available at: http://www.ncbi.nlm.nih.gov/pubmed/23559098
48. H. Luo et al., Cancer-associated fibroblasts: a multifaceted driver of breast cancer progression. Cancer Lett. 361(2), 155–163 (2015). doi:10.1016/j.canlet.2015.02.018
49. M. Luo, et al., VEGF/NRP-1axis promotes progression of breast cancer via enhancement of epithelial-mesenchymal transition and activation of NF-κB and β-catenin. Cancer letters. 373(1), 1–11 (2016)
50. C. C. Maley et al., An ecological measure of immune-cancer colocalization as a prognostic factor for breast cancer. Breast Cancer Research 17(1), 1 (2015). doi:10.1186/s13058-015-0638-4
51. R. S. Muraoka et al., Blockade of TGF-β inhibits mammary tumor cell viability, migration, and metastases. J. Clin. Invest. 109(12), 1551–1559 (2002)
52. S. Nagalla et al., Interactions between immunity, proliferation and molecular subtype in breast cancer prognosis. Genome Biology 14, p.R34 (2013)
53. D. P. Nanda et al., Matrix metalloproteinase-9 as a potential tumor marker in breast cancer. J. Environ. Pathol. Toxicol. Oncol. 32(2), 115–129 (2013)
54. S. Nozaki, G. W. Sledge, H. Nakshatri, Cancer cell-derived interleukin 1α contributes to autocrine and paracrine induction of pro-metastatic genes in breast cancer. Biochem. Biophys. Res. Commun. 275(1), 60–62 (2000)
55. F. Penault-Llorca et al., Expression of FGF and FGF receptor genes in human breast cancer. Int. J. Cancer 61(2), 170–176 (1995)
56. L. Peng et al., A fine balance between CCNL1 and TIMP1 contributes to the development of breast cancer cells. Biochem. Biophys. Res. Commun. 409(2), 344–349 (2011)
57. M. Pisano et al., An in vitro model of the tumor-lymphatic microenvironment with simultaneous transendothelial and luminal flows reveals mechanisms of flow enhanced invasion. Integrative biology 26(1), p.B5 (2015). doi:10.1039/c5ib00085h
58. Y. I. Rattigan et al., Lactate is a mediator of metabolic cooperation between stromal carcinoma associated fibroblasts and glycolytic tumor cells in the tumor microenvironment. Exp. Cell Res. 318(4), 326–335 (2012)Available at: http://www.sciencedirect.com/science/article/pii/S001448271100471X
59. M. C. Regier, E. T. Alarid, D. Beebe, Progress towards understanding heterotypic interactions in multi-culture models of breast cancer. Integr. Biol. 8, 684–692 (2016)
60. P. B. Rozenchan et al., Reciprocal changes in gene expression profiles of cocultured breast epithelial cells and primary fibroblasts. Int. J. Cancer 125(12), 2767–2777 (2009)
61. Z.-M. Shao, M. Nguyen, S. H. Barsky, Human breast carcinoma desmoplasia is PDGF initiated. Oncogene 19(38) (2000)
62. M. Stadler et al., Increased complexity in carcinomas: analyzing and modeling the interaction of human cancer cells with their microenvironment. Semin. Cancer Biol. 35, 107–124 (2015). doi:10.1016/j.semcancer.2015.08.007
63. D. A. Stewart et al., Basal-like Breast Cancer Cells Induce Phenotypic and Genomic Changes in Macrophages. Mol. Cancer Res. 10(6), pp.727–pp.739 (2012)
64. R. Straussman et al., Tumour micro-environment elicits innate resistance to RAF inhibitors through HGF secretion. Nature 487(7408), 500–504 (2012)
65. K. E. Sung et al., Understanding the impact of 2D and 3D fibroblast cultures on in vitro breast cancer models. PLoS One 8(10), 1–13 (2013)
66. S. Tabariès et al., Granulocytic immune infiltrates are essential for the efficient formation of breast cancer liver metastases. Breast Cancer Res. 17(1), 1 (2015). doi:10.1186/s13058-015-0558-3
67. C. R. Thoma et al., 3D cell culture systems modeling tumor growth determinants in cancer target discovery. Adv. Drug Deliv. Rev. 69-70, 29–41 (2014). doi:10.1016/j.addr.2014.03.001
68. J.-W. Tjiu et al., Tumor-associated macrophage-induced invasion and angiogenesis of human basal cell carcinoma cells by cyclooxygenase-2 induction. The Journal of investigative dermatology 129(4), 1016–1025 (2009)
69. S. W. Tobin et al., Consequences of altered TGF-beta expression and responsiveness in breast cancer: evidence for autocrine and paracrine effects. Oncogene 21(1), 108–118 (2002)
70. Y.-S. Torisawa et al., Microfluidic platform for chemotaxis in gradients formed by CXCL12 source-sink cells. Integrative biology: quantitative biosciences from nano to macro 2(11–12), 680–686 (2010)
71. S.-W. Tyan et al., Breast cancer cells induce cancer-associated fibroblasts to secrete hepatocyte growth factor to enhance breast tumorigenesis. PLoS One 6(1), 1–9 (2011)
72. T. Ueno et al., Characteristic Gene expression profiles of human fibroblasts and breast cancer cells in a newly developed bilateral Coculture system. BioMed Research International 2015, 960840 (2015)
73. G. M. Walker, D. J. Beebe, A passive pumping method for microfluidic devices. Lab Chip 2(3), 131–134 (2002)
74. S. Wan et al., BMP9 regulates cross-talk between breast cancer cells and bone marrow-derived mesenchymal stem cells. Cell. Oncol. 37(5), 363–375 (2014). doi:10.1007/s13402-014-0197-1
75. C. Wang et al., Human Adipocytes Stimulate Invasion of Breast Cancer MCF-7 Cells by Secreting IGFBP-2. PloS one 10(3), p.e0119348 (2015)
76. M. Weigand et al., Autocrine vascular endothelial growth factor signalling in breast cancer. Evidence from cell lines and primary breast cancer cultures in vitro. Angiogenesis 8(3), 197–204 (2005)
77. B. Weigelt, C. M. Ghajar, M. J. Bissell, The need for complex 3D culture models to unravel novel pathways and identify accurate biomarkers in breast cancer. Adv. Drug Deliv. Rev. 69-70, 42–51 (2014). doi:10.1016/j.addr.2014.01.001
78. Y. N. Xia, G. M. Whitesides, Soft lithography. Annu. Rev. Mater. Sci. 37(5), 551–575 (1998)Available at: http://apps.isiknowledge.com/InboundService.do?product=WOS&action=retrieve&SrcApp=Papers&UT=000075395600009&SID=4AeDcEnmon6P1nPEIJo&Init=Yes&SrcAuth=mekentosj&mode=FullRecord&customersID=mekentosj&DestFail=http://access.isiproducts.com/custom_images/wok_f
79. N. Yoshimura et al., The expression and localization of fibroblast growth factor-1 (FGF-1) and FGF receptor-1 (FGFR-1) in human breast cancer. Clin. Immunol. Immunopathol. 89(1), 28–34 (1998)
80. E. W. K. Young et al., Microscale functional cytomics for studying hematologic cancers. Blood 119(10), 76–86 (2012)
81. G. Yu et al., FoxM1 promotes breast tumorigenesis by activating PDGF-A and forming a positive feedback loop with the PDGF/AKT signaling pathway. Oncotarget 6(13), p.11281 (2015)
82. I. K. Zervantonakis et al., Three-dimensional microfluidic model for tumor cell intravasation and endothelial barrier function. Proc. Natl. Acad. Sci. 109(34), 13515–13520 (2012)