Collagen reorganization at the tumor-stromal interface facilitates local invasion
© Provenzano et al; licensee BioMed Central Ltd. 2006
Received: 18 June 2006
Accepted: 26 December 2006
Published: 26 December 2006
Stromal-epithelial interactions are of particular significance in breast tissue as misregulation of these interactions can promote tumorigenesis and invasion. Moreover, collagen-dense breast tissue increases the risk of breast carcinoma, although the relationship between collagen density and tumorigenesis is not well understood. As little is known about epithelial-stromal interactions in vivo, it is necessary to visualize the stroma surrounding normal epithelium and mammary tumors in intact tissues to better understand how matrix organization, density, and composition affect tumor formation and progression.
Epithelial-stromal interactions in normal mammary glands, mammary tumors, and tumor explants in three-dimensional culture were studied with histology, electron microscopy, and nonlinear optical imaging methodologies. Imaging of the tumor-stromal interface in live tumor tissue ex vivo was performed with multiphoton laser-scanning microscopy (MPLSM) to generate multiphoton excitation (MPE) of endogenous fluorophores and second harmonic generation (SHG) to image stromal collagen.
We used both laser-scanning multiphoton and second harmonic generation microscopy to determine the organization of specific collagen structures around ducts and tumors in intact, unfixed and unsectioned mammary glands. Local alterations in collagen density were clearly seen, allowing us to obtain three-dimensional information regarding the organization of the mammary stroma, such as radiating collagen fibers that could not have been obtained using classical histological techniques. Moreover, we observed and defined three tumor-associated collagen signatures (TACS) that provide novel markers to locate and characterize tumors. In particular, local cell invasion was found predominantly to be oriented along certain aligned collagen fibers, suggesting that radial alignment of collagen fibers relative to tumors facilitates invasion. Consistent with this observation, primary tumor explants cultured in a randomly organized collagen matrix realigned the collagen fibers, allowing individual tumor cells to migrate out along radially aligned fibers.
The presentation of these tumor-associated collagen signatures allowed us to identify pre-palpable tumors and see cells at the tumor-stromal boundary invading into the stroma along radially aligned collagen fibers. As such, TACS should provide indications that a tumor is, or could become, invasive, and may serve as part of a strategy to help identify and characterize breast tumors in animal and human tissues.
Tissue microenvironments play an important role in maintaining normal cell behavior [1–3]. Moreover, type I collagen is a prevalent component of the stromal extracellular matrix; its expression being spatially and temporally regulated during mammary ductal formation, suggesting it plays important roles in development . Consistent with this idea, decreasing the levels of α2β1 integrin, a primary type I collagen receptor, disrupts mammary epithelial tubulogenesis in vitro  and alters branching morphogenesis in vivo , respectively. Furthermore, inappropriate stromal-epithelial interactions can promote tumorigenesis [6–8], and in breast cancer, metastatic epithelial cells migrate in direct contact along stromal collagen fibers . The importance of studying stromal interactions in breast tissue is further reinforced by the fact that patients with collagen-dense breast tissue possess a greater than fourfold increased risk of breast carcinoma [10, 11]. Although the mechanisms mediating the effects of the extracellular matrix (ECM) on breast carcinoma development in vivo are largely unknown, contributing factors may be adhesion mediated signaling and mechanical signals imparted on mammary epithelial cells from surrounding type-I collagen-rich stroma, either directly or across basement membrane proteins. One important step to elucidating these signaling interactions is to determine the organization of the collagenous stroma surrounding both normal mammary glands and tumors within intact tissue so as to better understand the cell-matrix interaction and how matrix organization, density, and composition affect tumor formation and progression.
Nonlinear microscopy techniques such as multiphoton laser-scanning microscopy (MPLSM) and second harmonic generation (SHG) provide powerful tools to image cellular autofluorescence and extracellular matrix structure in intact tissues [12–15]. Both techniques are well suited for high-resolution in vivo imaging, and second harmonic generation is particularly adept at imaging collagen structure. Specifically, multiphoton microscopy results from the nonlinear excitation of molecular fluorescence and can produce images deep into thick tissues [16, 17], while SHG signals depend on non-linear interactions of illumination with a non-centrosymmetric environment (e.g. fibrillar collagen) that can provide submicron resolution [13–15]. The most commonly utilized multiphoton process is two-photon excitation (2PE) of fluorescence, in which two low-energy (usually near-infrared) photons simultaneously excite a fluorophore, which later decays to produce a single fluorescent photon of lower energy than the corresponding one-photon (half wavelength of 2PE) excitation [13, 18, 19]. In this 2PE process the fluorescence is dependent upon the square of the intensity (see Methods), producing optical sectioning that makes it equivalent to confocal imaging in terms of restricting excitation to the plane of focus, but facilitates a much greater effective imaging depth and better cell viability [16, 20]. SHG imaging, on the other hand, does not arise from an absorptive process, but instead the laser field suffers a nonlinear, second-order, polarization when passing through certain ordered structures resulting in a coherent signal at exactly half the wavelength of the excitation . Great utility arises from the fact that MPLSM and SHG can be implemented simultaneously in live tissue to provide complementary information and a powerful experimental and diagnostic tool.
The purpose of this study was to characterize collagen morphology in intact tissues so as to understand the structure-function relationship of epithelial- and tumor-stromal interactions in the mammary gland with particular emphasis on local tumor cell invasion during carcinoma progression. We used both MPLSM and SHG imaging, in conjunction with additional correlative microscopy techniques, to detect differences in local collagen density near normal glands and mammary tumors, and identify distinct collagen fiber organization around tumors, with characteristic collagen structures such as radially aligned collagen fibers associated with tumor-cell invasion. Identification and characterization of these collagen signatures sheds insight into the process of tumor cell invasion, and may serve a diagnostic capacity for determining the invasive potential of tumors.
Mouse mammary tissues and tumors
This study was approved by the institutional animal use and care committee and meets N.I.H. guidelines for animal welfare. To study non-tumor bearing mammary glands, tissue was obtained from B6129SF2/J mice or Col1a1tmJae mice (The Jackson Laboratory, Bar Harbor, ME, USA). To study tumor-stromal interactions in intact tissue, two mouse breast tumor models were utilized: MMTV-Wnt-1 (colony founder mice provided by Dr. Caroline Alexander, University of Wisconsin, Madison, WI, USA) and MMTV-polyoma middle-T (abbreviated PyVT following the Jackson Laboratory title but is also commonly abbreviated as PyMT or PyV-MT; colony founder mice originally obtained from Jackson Laboratory were provided by Dr. Amy Moser, University of Wisconsin, Madison, WI, USA).
Tumor explants and collagen gel culture
To study tumor-mediated collagen reorganization and tumor cell invasion in vitro, tumor explants were obtained and cultured in a manner similar to a previous report by Friedl and co-workers . Small pieces of tumor were harvested from the central region of palpable PyVT tumors (that were confirmed by histology) with a 3 mm biopsy punch and were cultured in type I collagen gels. Following removal, tumors were rinsed in DMEM containing penicillin/streptomycin/fungizone solution (Cellgro, Herndon, VA). A single tumor explant was then cultured within a 2.0 mg/ml collagen gel (8.0 mg/ml rat-tail collagen solution (BD Biosciences, San Jose, CA) neutralized with 100 mM HEPES in 2 × PBS). Following Gel polymerization for 1 hr, the tumor explant containing collagen gels were released from the culture dish and floated in DMEM containing penicillin/streptomycin solution supplemented with 10% heat inactivated FBS. Imaging was performed on live (non-fixed) cells in intact three-dimensional collagen gels.
Multiphoton microscopy and second harmonic generation
Multiphoton excitation (MPE) with MPLSM allows imaging of endogenous fluorophores from deep inside live biological tissues with the fluorescence excitation primarily restricted to the plane of focus due to a quadratic dependence on the laser light intensity and a low probability of multiple low-energy photons being absorbed outside the focal plane [16, 17, 23]. For the case of a pulsed laser excitation, the time averaged fluorescent intensity is a function of the molecular cross-section δ 2(λ) and the square of the laser intensity, I(t)2, and can be expressed as [23, 24]:
In Equation 1, δ 2 is defined as a molecular cross section that represents the dependence for the probability of two-photon excitation on the square of photon density, P is the laser power, τ p is the laser pulse width, f p is the laser repetition rate, NA is the numerical aperture, h is Planck's constant, c is the speed of light, and λ is the wavelength.
In contrast to multiphoton excitation, which obeys the fundamental physical relationship of energy loss following excitation, SHG is a conserved polarization process that follows the relationship [21, 25, 26]:
P = χ (1) * E + χ (2) * E * E + χ (3) * E * E * E + … (2)
where the polarization (P) and electric field (E) are vectors, and the nonlinear susceptibilities, χ(i), are tensors. Therefore, SHG arises from the laser field suffering a conserved nonlinear, second-order, polarization when passing through non-centrosymmetric ordered structures that is described by term 2 of Equation 2.
For MPE and SHG imaging of live unfixed, intact (not sectioned), non-stained glands, and tumor explants within collagen gels, as well as hematoxylin and eosin stained histology slides, we used an optical workstation  that was constructed around a Nikon Eclipse TE300. For live tissue imaging, twenty mammary tissues including nine from the Col1a1tmJae strain (three each of wild type, heterozygous and homozygous), and tumors from Wnt-1 (n = 10, plus wild type controls) and PyVT (n = 20) mice were harvested and live tissue maintained in buffered media at 37°C. All tissues were imaged immediately following tissue harvest and a Ti:sapphire laser (Spectra-Physics-Millennium/Tsunami, Mountain View CA) excitation source producing around 100 fs pulse widths and tuned to 890–900 nm was utilized to generate both multiphoton excitation (cellular autofluorescence from FAD) and SHG. The beam was focused onto the sample with either a Nikon 40× Plan Fluor oil-immersion lens (N.A. = 1.4) or a Nikon 60× Plan Apo water-immersion lens (N.A. = 1.2). All SHG imaging was detected from the back-scattered SHG signal , and the presence of collagen confirmed in our tissues using fluorescence lifetime imaging microscopy, or FLIM , on the same optical workstation, as the SHG from collagen has no lifetime. Additionally, due to the fundamental differences between MPE and SHG signals, filtering can separate the emission signals. Using a 464 nm (cut-on) long pass filter, MPE was discriminated from the total emission while a 445 nm narrow band pass filters was used to separate SHG (filters from TFI Technologies, Greenfield, MA). For 3D imaging in intact tissues, 2D (x-y) images were acquired at various serial depths (z) into the samples.
Acquisition was performed with WiscScan  a software acquisition package developed at LOCI (Laboratory for Optical and Computational Instrumentation, University of Wisconsin, Madison, WI, USA). Image analysis for combined MPE-SHG was performed with ImageJ  and VisBio  software. Using ImageJ, differences in collagen density were quantified by measuring the area of collagen signal following density slicing from a constant threshold, and local and mean intensity were measured within these normalized areas. For TACS-1 image analysis additional surface rendering plug-ins for ImageJ were utilized. For TACS-2 and -3, ImageJ was used to quantify the collagen fiber angle relative to the tumor. The tumor boundary was defined and the angle relative to the tangent of tumor boundary was measured every 10 microns.
Histology and electron microscopy
For histology, formalin-fixed paraffin-embedded samples from eight B6129SF2/J mice and eight Col1a1tmJae mice were sectioned and stained for hematoxylin and eosin, trichrome, and picrosirius red using standard techniques. Additionally, all tissues imaged with MPLSM were subsequently fixed and processed for histology to confirm the presence of tumors and characterize the tumor morphology. Sample preparation for scanning and transmission electron microscopy (SEM and TEM, respectively) was performed by fixing whole mammary glands in 2.5% formaldehyde/2.5% glutaraldehyde in 0.1 M sodium cacodylate buffer for 1 hr at room temperature (RT), after which sample were placed in fresh fixative overnight at 4°C. Samples were then washed in cacodylate buffer and postfixed in 1.5% osmium tetroxide at RT for 1.5 hrs. Samples (SEM n = 8 glands and TEM n = 6 glands) from B6129 mice were again washed in buffered solution and dehydrated, fractured, critical point dried, sputter coated, and imaged with SEM, or stained, dehydrated and cleared, embedded, and then sectioned for imaging with TEM .
The normal mammary gland
Detecting dense mammary tissue
Tumor-associated collagen signatures (TACS)
Tumor-associated collagen signature-1
Tumor-associated collagen signatures-2 and -3
As the size of the tumor increased, we identified a second collagen signature, TACS-2: "taut" collagen fibers stretched around the tumor (Figure 4B). This collagen morphology likely arose from stretching of the stroma due to tumor growth, which may act to constrain portions of the tumor (i.e. compressive restraint) as well as provide a stretch induced tensile stress in expanded fibrils (and larger resistance to cell contraction in the stroma) that stimulates and activates fibroblasts. Evidence for tumor restraint in Wnt-t mice can be seen in Figure 4B, a–c, where collagen fibers are stretched around a relatively smooth tumor boundary as indicated by the fact that the fiber angle is primarily distributed tangentially (0° relative to the tumor boundary) along the tumor boundary (see histogram in Figure 4B).
In regions of tumor masses that are undergoing growth and invasion (Figure 4C: a–c), a third tumor-associated collagen signature, TACS-3, was identified: collagen fibers aligned normal to tumor boundary regions that display an irregular shape – indicative of local invasion through collective epithelial cell migration [22, 40]. This invasive tumor morphology was seen in regions of tumors where collagen fibers are primarily aligned in the direction of cell invasion (see histogram in Figure 4C, in which the angle of the collagen fibers relative to the tumor boundary distributes around 90°). Furthermore, at regions where TACS-3 is noted, we observed groups of cells advancing from the tumor boundary in a collective manner that appear to be undergoing collective invasion [22, 40, 41], as well as individual invading cells that may relate to single cell migration similar to what has been observed along collagen fibers in an in vivo xenograft model .
Intrinsic fluorescence detection with multiphoton excitation in combination with SHG facilitates three-dimensional, high resolution, imaging in unfixed, unsectioned, unstained mammary tissues. This imaging provides information commonly obtained with classical histology and EM without the need for complex and destructive sample preparation, and with additional structural information in four dimensions. With MPE/SHG, mammary gland tissue could be clearly imaged at depths of 440 nm, and changes in collagen density could be reliably detected. Furthermore, three-dimensional imaging of tumors in situ revealed three now defined TACS, which provide standard hallmarks to locate and characterize tumors: TACS-1, the presence of dense collagen, indicated by increased signal intensity at a region around the tumor as a standard hallmark for locating small tumor regions; TACS-2, the presence of taut (straightened) collagen fibers stretched around the tumor, indicating growth leading to increased tumor volume; and TACS-3, the identification of radially aligned collagen fibers facilitating invasion, which may be indicative of the invasive and metastatic growth potential of a tumor. Together these signatures may serve a mechanism to help identify and characterize breast tumors in experimental animal models as well as human cancers and fresh tumor biopsies.
The breast epithelial cell-ECM interaction is responsible for influencing cell polarity, proliferation, differentiation, adhesion, and migration [44, 45] and type I collagen is an important regulator of mammary ductal formation during development . Analysis of normal mammary glands reveals collagen fibers wrapping around, as well as radiating away from, the duct (Figure 2A: b). This organization is remarkably consistent with the observation that in fixed whole mounts of developing mammary gland, analyzed with multiphoton microscopy, collagen fibers are "pulled in" perpendicular to the terminal end bud , similar to what we observe for radially aligned collagen fibers near tumors (TACS-3). Combined, these morphologies provide insight into the structure-function relationship in the mammary gland and imply that collagen may provide directional cues during development that also influence changes in the normal mammary gland. For instance, the crimped (wavy) collagen structure (i.e. Figure 2A: a,b,e,g) is consistent with numerous reports of crimped collagen fibers in connective tissue that allow normal tissue deformation with a strain-stiffening behavior [47, 48]. This behavior may hold true for the mammary gland as well, allowing for tissue deformation and normal ductal growth and involution without over constraining the system, yet providing adequate levels of tensile resistance to contracting cells and resisting large deformations that can damage the tissue. The less numerous taut fibers may serve a different purpose. They may act as locally constraining structures at the single cell level and may act to interconnect various ducts in the tissue together and to the nipple structure (Figure 2A: f), which may transmit mechanical signals to the ducts during activities such as nursing to elicit mechanotransductive signaling related to lactation. Furthermore, such mechanical signals acting directly on epithelial cells or transmitting stress across the basement membrane would be amplified by increased breast tissue density. Hence, increased breast tissue density in vivo may promote carcinoma formation by increased mechanical signaling events in dense tissue, consistent with in vitro work showing that increased matrix density alters breast epithelial cell signaling .
The importance of matrix composition and morphology around the mammary epithelium is illustrated by studies showing that misregulated stromal-epithelial interactions can promote tumorigenesis [6–8] and the fact that breast carcinomas often exhibit desmoplasia (excessive collagen surrounding an invasive tumor ). Moreover, cancer cells can locally invade across basement membrane and collagenous stroma to spread into neighboring ECM environments, where they can migrate further to enter lymphatic and blood vessels, resulting in metastatic growth in distant tissues [40, 51]. Therefore, understanding the mechanisms of invasion in vivo is of great importance. Yet, to our knowledge, no study has visualized local invasion in endogenous tumors in vivo in relation to stromal organization. Consequently, it is noteworthy that we observe alignment of collagen fibers, and association of individual cells with those fibers at regions of local invasion in live tissue (TACS-3), which is similar to observations of individual cell migration along collagen fibers in a xenograft model , and confirms and expands upon in vitro studies in 3D matrices that have identified collagen reorganization (alignment) at the front of invading cells [22, 40, 41]. Moreover, the concept of alignment-facilitated invasion appears to be of significance in collective cell migration (e.g. tubulogenesis in the mammary gland; ) as collagen alignment is noted at the terminal end bud during invasion of the mammary ductal tree . Thus, collagen alignment may facilitate motility and migration during normal development, while tumor invasion may resemble misregulated developmental processes.
The data presented indicate that tumor cells often localize near dense collagen or promote a desmoplastic response and contract and localize collagen, followed by tumor growth and expansion (stretching) of the collagen matrix leading to matrix reorganization (possibly assisted by proteolytic cleavage [40, 43] to release collagen fibers) to help facilitate local invasion. This matrix reorganization would require enhanced contractility and motility of the tumor cells, which may explain the increased presence of Rho and ROCK, in invasive cancers (, and references therein). Although a number of mechanisms, such as growth factor and integrin signaling and protease secretion and activity, are associated with invasion and metastasis, it seems likely that GTPase-regulated motility events are also involved these processes. Hence, the mechanisms behind local invasion may include matrix reorganization through GTPase-mediated tumor cell contractility (P.P.P. and P.J.K unpublished observations), leading to an aligned matrix that facilitates local invasion.
The authors thank Drs Caroline Alexander and Amy Moser for providing colony founder mice, Curtis Rueden for assistance with VisBio, and the Materials Science Center and BBPIC for EM resources. This work was supported by grants from the DOD-CDMRP/BCRP: W81XWH-04-1-0428 to PPP, the S.G. Komen Foundation: BCTR02-1841 and NIH: CA076537 to P.J.K. and NIH NIBIB: R01-EB000184 to J.G.W and K.W.E.
- Barcellos-Hoff MH, Aggeler J, Ram TG, Bissell MJ: Functional differentiation and alveolar morphogenesis of primary mammary cultures on reconstituted basement membrane. Development. 1989, 105 (2): 223-235.PubMedPubMed CentralGoogle Scholar
- Keely P, Fong A, Zutter M, Santoro S: Alteration of collagen-dependent adhesion, motility, and morphogenesis by the expression of antisense α2 integrin mRNA in mammary cells. J Cell Science. 1995, 108: 595-607.PubMedGoogle Scholar
- Roskelley CD, Srebrow A, Bissell MJ: A hierarchy of ECM-mediated signalling regulates tissue-specific gene expression. Curr Opin Cell Biol. 1995, 7 (5): 736-747. 10.1016/0955-0674(95)80117-0.View ArticlePubMedPubMed CentralGoogle Scholar
- Keely PJ, Wu JE, Santoro SA: The spatial and temporal expression of the alpha 2 beta 1 integrin and its ligands, collagen I, collagen IV, and laminin, suggest important roles in mouse mammary morphogenesis. Differentiation. 1995, 59 (1): 1-13. 10.1046/j.1432-0436.1995.5910001.x.View ArticlePubMedGoogle Scholar
- Chen J, Diacovo TG, Grenache DG, Santoro SA, Zutter MM: The alpha(2) integrin subunit-deficient mouse: a multifaceted phenotype including defects of branching morphogenesis and hemostasis. Am J Pathol. 2002, 161 (1): 337-344.View ArticlePubMedPubMed CentralGoogle Scholar
- Ronnov-Jessen L, Petersen OW, Koteliansky VE, Bissell MJ: The origin of the myofibroblasts in breast cancer. Recapitulation of tumor environment in culture unravels diversity and implicates converted fibroblasts and recruited smooth muscle cells. J Clin Invest. 1995, 95 (2): 859-873.View ArticlePubMedPubMed CentralGoogle Scholar
- Tlsty TD, Hein PW: Know thy neighbor: stromal cells can contribute oncogenic signals. Curr Opin Genet Dev. 2001, 11 (1): 54-59. 10.1016/S0959-437X(00)00156-8.View ArticlePubMedGoogle Scholar
- Elenbaas B, Spirio L, Koerner F, Fleming MD, Zimonjic DB, Donaher JL, Popescu NC, Hahn WC, Weinberg RA: Human breast cancer cells generated by oncogenic transformation of primary mammary epithelial cells. Genes Dev. 2001, 15 (1): 50-65. 10.1101/gad.828901.View ArticlePubMedPubMed CentralGoogle Scholar
- Wang W, Wyckoff JB, Frohlich VC, Oleynikov Y, Huttelmaier S, Zavadil J, Cermak L, Bottinger EP, Singer RH, White JG, Segall JE, Condeelis JS: Single cell behavior in metastatic primary mammary tumors correlated with gene expression patterns revealed by molecular profiling. Cancer Res. 2002, 62 (21): 6278-6288.PubMedGoogle Scholar
- Boyd NF, Martin LJ, Stone J, Greenberg C, Minkin S, Yaffe MJ: Mammographic densities as a marker of human breast cancer risk and their use in chemoprevention. Curr Oncol Rep. 2001, 3 (4): 314-321.View ArticlePubMedGoogle Scholar
- Boyd NF, Lockwood GA, Byng JW, Tritchler DL, Yaffe MJ: Mammographic densities and breast cancer risk. Cancer Epidemiol Biomarkers Prev. 1998, 7 (12): 1133-1144.PubMedGoogle Scholar
- Provenzano PP, Eliceiri KW, Yan L, Ada-Nguema A, Conklin MW, Inman DR, Keely PJ: Nonlinear optical imaging of cellular processes in breast cancer. Microscopy and Microanalysis. accepted – to appear 2007.
- Zipfel WR, Williams RM, Christie R, Nikitin AY, Hyman BT, Webb WW: Live tissue intrinsic emission microscopy using multiphoton-excited native fluorescence and second harmonic generation. Proc Natl Acad Sci USA. 2003, 100 (12): 7075-7080. 10.1073/pnas.0832308100.View ArticlePubMedPubMed CentralGoogle Scholar
- Cox G, Kable E, Jones A, Fraser I, Manconi F, Gorrell MD: Three-dimensional imaging of collagen using second harmonic generation. J Struct Biol. 2003, 141 (1): 53-62. 10.1016/S1047-8477(02)00576-2.View ArticlePubMedGoogle Scholar
- Zoumi A, Yeh A, Tromberg BJ: Imaging cells and extracellular matrix in vivo by using second-harmonic generation and two-photon excited fluorescence. Proc Natl Acad Sci USA. 2002, 99 (17): 11014-11019. 10.1073/pnas.172368799.View ArticlePubMedPubMed CentralGoogle Scholar
- Centonze VE, White JG: Multiphoton excitation provides optical sections from deeper within scattering specimens than confocal imaging. Biophys J. 1998, 75 (4): 2015-2024.View ArticlePubMedPubMed CentralGoogle Scholar
- Denk W, Strickler JH, Webb WW: Two-photon laser scanning fluorescence microscopy. Science. 1990, 248 (4951): 73-76. 10.1126/science.2321027.View ArticlePubMedGoogle Scholar
- Zipfel WR, Williams RM, Webb WW: Nonlinear magic: multiphoton microscopy in the biosciences. Nat Biotechnol. 2003, 21 (11): 1369-1377. 10.1038/nbt899.View ArticlePubMedGoogle Scholar
- Helmchen F, Denk W: New developments in multiphoton microscopy. Curr Opin Neurobiol. 2002, 12 (5): 593-601. 10.1016/S0959-4388(02)00362-8.View ArticlePubMedGoogle Scholar
- Squirrell JM, Wokosin DL, White JG, Bavister BD: Long-term two-photon fluorescence imaging of mammalian embryos without compromising viability. Nat Biotechnol. 1999, 17 (8): 763-767. 10.1038/11698.View ArticlePubMedGoogle Scholar
- Mohler W, Millard AC, Campagnola PJ: Second harmonic generation imaging of endogenous structural proteins. Methods. 2003, 29 (1): 97-109. 10.1016/S1046-2023(02)00292-X.View ArticlePubMedGoogle Scholar
- Hegerfeldt Y, Tusch M, Brocker EB, Friedl P: Collective cell movement in primary melanoma explants: plasticity of cell-cell interaction, beta1-integrin function, and migration strategies. Cancer Res. 2002, 62 (7): 2125-2130.PubMedGoogle Scholar
- Diaspro A, Sheppard CJR: Two-photon excitation fluorescence microscopy. Confocal and Two-Photon Microscopy: Foundations, Applications, and Advances. Edited by: Diaspro A. 2002, New York: Wiley-Liss, Inc, 39-73.Google Scholar
- So PTC, Kim KH, Buehler C, Masters BR, Hsu L, Dong CY: Basic principle of multi-photon excitation microscopy. Methods in Cellular Imaging. Edited by: Periasamy A. 2001, New York: Oxford University Press, 152-161.Google Scholar
- Stoller P, Kim BM, Rubenchik AM, Reiser KM, Da Silva LB: Polarization-dependent optical second-harmonic imaging of a rat-tail tendon. J Biomed Opt. 2002, 7 (2): 205-214. 10.1117/1.1431967.View ArticlePubMedGoogle Scholar
- Williams RM, Zipfel WR, Webb WW: Interpreting second-harmonic generation images of collagen I fibrils. Biophys J. 2005, 88 (2): 1377-1386. 10.1529/biophysj.104.047308.View ArticlePubMedGoogle Scholar
- Wokosin DL, Squirrell JM, Eliceiri KE, White JG: An optical workstation with concurrent, independent multiphoton imaging and experimental laser microbeam capabilities. Rev Sci Inst. 2003, 74 (1): 193-201. 10.1063/1.1524716.View ArticleGoogle Scholar
- Nazir MZ, Eliceiri KW, Ahmed A, Hashmi A, Agarwal V, Rao Y, Kumar S, Lukas T, Nasim M, Rueden C, Gunawan R, White JG: WiscScan: a software defined laser-scanning microscope. Scanning. 2006.Google Scholar
- Abramoff MD, Magelhaes PJ, Ram SJ: Image processing with ImageJ. Biophotonics International. 2004, 11 (7): 36-42.Google Scholar
- Rueden C, Eliceiri KW, White JG: VisBio: a computational tool for visualization of multidimensional biological image data. Traffic. 2004, 5 (6): 411-417. 10.1111/j.1600-0854.2004.00189.x.View ArticlePubMedGoogle Scholar
- Glauert AM: Fixation, dehydration and embedding of biological specimens. Practical Methods in Electron Microscopy. Edited by: Glauert AM. 1980, New York: Am Elsevier Pub. Co, 3.Google Scholar
- Parry DA, Craig AS: Growth and development of collagen fibrils in connective tissue. Ultrastructure of the Connective Tissue Matrix. Edited by: Ruggeri A, Motta A. 1984, The Hague, Martinus Nijhoff, 34-62.View ArticleGoogle Scholar
- Zutter MM, Santoro SA, Wu JE, Wakatsuki T, Dickeson SK, Elson EL: Collagen receptor control of epithelial morphogenesis and cell cycle progression. Am J Pathol. 1999, 155 (3): 927-940.View ArticlePubMedPubMed CentralGoogle Scholar
- Monaghan P, Warburton MJ, Perusinghe N, Rudland PS: Topographical arrangement of basement membrane proteins in lactating rat mammary gland: Comparison of the distribution of type IV collagen, laminin, fibronectin, and Thy-1 at the ultrastructural level. Proc Natl Acad Sci USA. 1983, 80: 3344-3348. 10.1073/pnas.80.11.3344.View ArticlePubMedPubMed CentralGoogle Scholar
- Li Y, Hively WP, Varmus HE: Use of MMTV-Wnt-1 transgenic mice for studying the genetic basis of breast cancer. Oncogene. 2000, 19 (8): 1002-1009. 10.1038/sj.onc.1203273.View ArticlePubMedGoogle Scholar
- Alowami S, Troup S, Al-Haddad S, Kirkpatrick I, Watson PH: Mammographic density is related to stroma and stromal proteoglycan expression. Breast Cancer Res. 2003, 5 (5): R129-135. 10.1186/bcr622.View ArticlePubMedPubMed CentralGoogle Scholar
- Boyd NF, Dite GS, Stone J, Gunasekara A, English DR, McCredie MR, Giles GG, Tritchler D, Chiarelli A, Yaffe MJ, Hopper JL: Heritability of mammographic density, a risk factor for breast cancer. N Engl J Med. 2002, 347 (12): 886-894. 10.1056/NEJMoa013390.View ArticlePubMedGoogle Scholar
- Liu X, Wu H, Byrne M, Jeffrey J, Krane S, Jaenisch R: A targeted mutation at the known collagenase cleavage site in mouse type I collagen impairs tissue remodeling. J Cell Biol. 1995, 130 (1): 227-237. 10.1083/jcb.130.1.227.View ArticlePubMedGoogle Scholar
- Brown E, McKee T, diTomaso E, Pluen A, Seed B, Boucher Y, Jain RK: Dynamic imaging of collagen and its modulation in tumors in vivo using second-harmonic generation. Nat Med. 2003, 9 (6): 796-800. 10.1038/nm879.View ArticlePubMedGoogle Scholar
- Friedl P, Wolf K: Tumour-cell invasion and migration: diversity and escape mechanisms. Nat Rev Cancer. 2003, 3 (5): 362-374. 10.1038/nrc1075.View ArticlePubMedGoogle Scholar
- Friedl P, Hegerfeldt Y, Tusch M: Collective cell migration in morphogenesis and cancer. Int J Dev Biol. 2004, 48 (5–6): 441-449. 10.1387/ijdb.041821pf.View ArticlePubMedGoogle Scholar
- Lin EY, Jones JG, Li P, Zhu L, Whitney KD, Muller WJ, Pollard JW: Progression to malignancy in the polyoma middle T oncoprotein mouse breast cancer model provides a reliable model for human diseases. Am J Pathol. 2003, 163 (5): 2113-2126.View ArticlePubMedPubMed CentralGoogle Scholar
- Wolf K, Friedl P: Functional imaging of pericellular proteolysis in cancer cell invasion. Biochimie. 2005, 87 (3–4): 315-320. 10.1016/j.biochi.2004.10.016.View ArticlePubMedGoogle Scholar
- Hagios C, Lochter A, Bissell MJ: Tissue architecture: the ultimate regulator of epithelial function?. Philos Trans R Soc Lond B Biol Sci. 1998, 353 (1370): 857-870. 10.1098/rstb.1998.0250.View ArticlePubMedPubMed CentralGoogle Scholar
- Fata JE, Werb Z, Bissell MJ: Regulation of mammary gland branching morphogenesis by the extracellular matrix and its remodeling enzymes. Breast Cancer Res. 2004, 6 (1): 1-11.PubMedGoogle Scholar
- Ingman W, Wyckoff J, Xue C, Lin EY, Wang W, Goswami S, Pollard JW, Condeelis J, Segall JE: Imaging invasion and metastasis in vivo. Cell Motility in Cancer Invasion and Metastasis. Edited by: Wells A. 2006, Kluwer Academic PublishersGoogle Scholar
- Hurschler C, Provenzano PP, Vanderby R: Application of a probabilistic microstructural model to determine reference length and toe-to-linear region transition in fibrous connective tissue. ASME J Biomech Eng. 2003, 125 (3): 415-422. 10.1115/1.1579046.View ArticleGoogle Scholar
- Diamant J, Keller A, Baer E, Litt M, Arridge RGC: Collagen; ultrastructure and its relation to mechanical properties. Proc Royal Soc Lond. 1972, 180B: 293-315.View ArticleGoogle Scholar
- Wozniak MA, Desai R, Solski PA, Der CJ, Keely PJ: ROCK-generated contractility regulates breast epithelial cell differentiation in response to the physical properties of a three-dimensional collagen matrix. J Cell Biol. 2003, 163 (3): 583-595. 10.1083/jcb.200305010.View ArticlePubMedPubMed CentralGoogle Scholar
- Barsky SH, Rao CN, Grotendorst GR, Liotta LA: Increased content of type V collagen in desmoplasia of human breast carcinoma. Am J Pathol. 1982, 108 (3): 276-283.PubMedPubMed CentralGoogle Scholar
- Wang W, Goswami S, Sahai E, Wyckoff JB, Segall JE, Condeelis JS: Tumor cells caught in the act of invading: their strategy for enhanced cell motility. Trends Cell Biol. 2005, 15 (3): 138-145. 10.1016/j.tcb.2005.01.003.View ArticlePubMedGoogle Scholar
- Croft DR, Sahai E, Mavria G, Li S, Tsai J, Lee WM, Marshall CJ, Olson MF: Conditional ROCK activation in vivo induces tumor cell dissemination and angiogenesis. Cancer Res. 2004, 64 (24): 8994-9001. 10.1158/0008-5472.CAN-04-2052.View ArticlePubMedGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1741-7015/4/38/prepub
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