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  • 1
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 114, No. 40 ( 2017-10-03), p. 10542-10547
    Abstract: Skeletal metastases, the leading cause of death in advanced breast cancer patients, depend on tumor cell interactions with the mineralized bone extracellular matrix. Bone mineral is largely composed of hydroxyapatite (HA) nanocrystals with physicochemical properties that vary significantly by anatomical location, age, and pathology. However, it remains unclear whether bone regions typically targeted by metastatic breast cancer feature distinct HA materials properties. Here we combined high-resolution X-ray scattering analysis with large-area Raman imaging, backscattered electron microscopy, histopathology, and microcomputed tomography to characterize HA in mouse models of advanced breast cancer in relevant skeletal locations. The proximal tibial metaphysis served as a common metastatic site in our studies; we identified that in disease-free bones this skeletal region contained smaller and less-oriented HA nanocrystals relative to ones that constitute the diaphysis. We further observed that osteolytic bone metastasis led to a decrease in HA nanocrystal size and perfection in remnant metaphyseal trabecular bone. Interestingly, in a model of localized breast cancer, metaphyseal HA nanocrystals were also smaller and less perfect than in corresponding bone in disease-free controls. Collectively, these results suggest that skeletal sites prone to tumor cell dissemination contain less-mature HA (i.e., smaller, less-perfect, and less-oriented crystals) and that primary tumors can further increase HA immaturity even before secondary tumor formation, mimicking alterations present during tibial metastasis. Engineered tumor models recapitulating these spatiotemporal dynamics will permit assessing the functional relevance of the detected changes to the progression and treatment of breast cancer bone metastasis.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    RVK:
    RVK:
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2017
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
    Location Call Number Limitation Availability
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  • 2
    Online Resource
    Online Resource
    Proceedings of the National Academy of Sciences ; 2020
    In:  Proceedings of the National Academy of Sciences Vol. 117, No. 51 ( 2020-12-22), p. 32251-32259
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 117, No. 51 ( 2020-12-22), p. 32251-32259
    Abstract: Organisms rely on mechanosensing mechanisms to adapt to changes in their mechanical environment. Fluid-filled network structures not only ensure efficient transport but can also be employed for mechanosensation. The lacunocanalicular network (LCN) is a fluid-filled network structure, which pervades our bones and accommodates a cell network of osteocytes. For the mechanism of mechanosensation, it was hypothesized that load-induced fluid flow results in forces that can be sensed by the cells. We use a controlled in vivo loading experiment on murine tibiae to test this hypothesis, whereby the mechanoresponse was quantified experimentally by in vivo micro-computed tomography (µCT) in terms of formed and resorbed bone volume. By imaging the LCN using confocal microscopy in bone volumes covering the entire cross-section of mouse tibiae and by calculating the fluid flow in the three-dimensional (3D) network, we could perform a direct comparison between predictions based on fluid flow velocity and the experimentally measured mechanoresponse. While local strain distributions estimated by finite-element analysis incorrectly predicts preferred bone formation on the periosteal surface, we demonstrate that additional consideration of the LCN architecture not only corrects this erroneous bias in the prediction but also explains observed differences in the mechanosensitivity between the three investigated mice. We also identified the presence of vascular channels as an important mechanism to locally reduce fluid flow. Flow velocities increased for a convergent network structure where all of the flow is channeled into fewer canaliculi. We conclude that, besides mechanical loading, LCN architecture should be considered as a key determinant of bone adaptation.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    RVK:
    RVK:
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2020
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
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