Publications by authors named "David R Inman"

In breast cancer, the extracellular matrix (ECM) undergoes remodeling and changes the tumor microenvironment to support tumor progression and metastasis. Fibronectin (FN) assembly is an important step in the regulation of the tumor microenvironment since the FN matrix precedes the deposition of various other ECM proteins, controls immune cell infiltration, and serves as a reservoir for cytokines and growth factors. Therefore, FN is an attractive target for breast cancer therapy and imaging.

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The ability to visualize complex and dynamic physiological interactions between numerous cell types and the extracellular matrix (ECM) within a live tumor microenvironment is an important step toward understanding mechanisms that regulate tumor progression. While this can be accomplished through current intravital imaging techniques, it remains challenging due to the heterogeneous nature of tissues and the need for spatial context within the experimental observation. To this end, we have developed an intravital imaging workflow that pairs collagen second harmonic generation imaging, endogenous fluorescence from the metabolic co-factor NAD(P)H, and fluorescence lifetime imaging microscopy (FLIM) as a means to non-invasively compartmentalize the tumor microenvironment into basic domains of the tumor nest, the surrounding stroma or ECM, and the vasculature.

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Exosomes are small extracellular vesicles (EVs) secreted by all cells and found in biological fluids, which can serve as minimally invasive liquid biopsies with extremely high therapeutic and diagnostic potential. Mass spectrometry (MS)-based proteomics is a powerful technique to profile and quantify the protein content in exosomes, but the current methods require laborious and time-consuming multistep sample preparation that significantly limit throughput. Herein, we report a one-pot exosome proteomics method enabled by a photocleavable surfactant, Azo, to simplify exosomal lysis, effectively extract proteins, and expedite digestion.

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It is well established that collagen alignment in the breast tumor microenvironment provides biophysical cues to drive disease progression. Numerous mechanistic studies have demonstrated that tumor cell behavior is driven by the architecture and stiffness of the collagen matrix. However, the mechanical properties within a 3D collagen microenvironment, particularly at the scale of the cell, remain poorly defined.

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This study uses dynamic hyperpolarized [1-C]pyruvate magnetic resonance spectroscopic imaging (MRSI) to estimate differences in glycolytic metabolism between highly metastatic (4T1, = 7) and metastatically dormant (4T07, = 7) murine breast cancer models. The apparent conversion rate of pyruvate-to-lactate (k) and lactate-to-pyruvate area-under-the-curve ratio (AUC) were estimated from the metabolite images and compared with biochemical metabolic measures and immunohistochemistry (IHC). A non-significant trend of increasing k ( = 0.

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Quantification of fibrillar collagen organization has given new insight into the possible role of collagen topology in many diseases and has also identified candidate image-based bio-markers in breast cancer and pancreatic cancer. We have been developing collagen quantification tools based on the curvelet transform (CT) algorithm and have demonstrated this to be a powerful multiscale image representation method due to its unique features in collagen image denoising and fiber edge enhancement. In this paper, we present our CT-based collagen quantification software platform with a focus on new features and also giving a detailed description of curvelet-based fiber representation.

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In response to chemical stimuli from cancer cells, mesenchymal stem cells (MSC) can differentiate into cancer-associated fibroblasts (CAF) and promote tumor progression. How mechanical stimuli such as stiffness of the extracellular matrix (ECM) contribute to MSC phenotype in cancer remains poorly understood. Here, we show that ECM stiffness leads to mechano-signal transduction in MSC, which promotes mammary tumor growth in part through secretion of the signaling protein prosaposin.

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Macrophage infiltration and recruitment in breast tumors has been correlated with poor prognosis in breast cancer patients and has been linked to tumor cell dissemination. Much of our understanding comes from animal models in which macrophages are labeled by expression of an extrinsic fluorophore. However, conventional extrinsic fluorescence labeling approaches are not readily applied to human tissue and clinical use.

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Background: High mammographic density has been correlated with a 4-fold to 6-fold increased risk of developing breast cancer, and is associated with increased stromal deposition of extracellular matrix proteins, including collagen I. The molecular and cellular mechanisms responsible for high breast tissue density are not completely understood.

Methods: We previously described accelerated tumor formation and metastases in a transgenic mouse model of collagen-dense mammary tumors (type I collagen-α1 (Col1α1)(tm1Jae) and mouse mammary tumor virus - polyoma virus middle T antigen (MMTV-PyVT)) compared to wild-type mice.

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Second-harmonic generation (SHG) imaging can help reveal interactions between collagen fibers and cancer cells. Quantitative analysis of SHG images of collagen fibers is challenged by the heterogeneity of collagen structures and low signal-to-noise ratio often found while imaging collagen in tissue. The role of collagen in breast cancer progression can be assessed post acquisition via enhanced computation.

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Breast epithelial cells sense the stiffness of the extracellular matrix through Rho-mediated contractility. In turn, matrix stiffness regulates RhoA activity. However, the upstream signaling mechanisms are poorly defined.

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Cell invasion requires that cells navigate complex three-dimensional matrices in vivo. Topological cues are provided and three-dimensional cell migration and invasion facilitated by the alignment of collagen fibers proximal to tumors. In order to better understand the molecular mechanisms by which cells recognize and migrate along aligned matrices, in vitro assays are needed that recapitulate topological features of the in vivo matrix.

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Nonlinear optical imaging techniques such as multiphoton and second harmonic generation (SHG) microscopy used in conjunction with novel signal analysis techniques such as spectroscopic and fluorescence excited state lifetime detection have begun to be used widely for biological studies. This is largely due to their promise to noninvasively monitor the intracellular processes of a cell together with the cell's interaction with its microenvironment. Compared to other optical methods these modalities provide superior depth penetration and viability and have the additional advantage in that they are compatible technologies that can be applied simultaneously.

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Focal adhesion kinase (FAK) is a central regulator of the focal adhesion, influencing cell proliferation, survival, and migration. Despite evidence demonstrating FAK overexpression in human cancer, its role in tumor initiation and progression is not well understood. Using Cre/LoxP technology to specifically knockout FAK in the mammary epithelium, we showed that FAK is not required for tumor initiation but is required for tumor progression.

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Cells generate mechanical force to organize the extracellular matrix (ECM) and drive important developmental and reparative processes. Likewise, tumor cells invading into three-dimensional (3D) matrices remodel the ECM microenvironment. Importantly, we previously reported a distinct radial reorganization of the collagen matrix surrounding tumors that facilitates local invasion.

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Multiphoton laser scanning microscopy (MPLSM) utilizing techniques such as multiphoton excitation (MPE), second harmonic generation (SHG), and multiphoton fluorescence lifetime imaging and spectral lifetime imaging (FLIM and SLIM, respectively) are greatly expanding the degree of information obtainable with optical imaging in biomedical research. The application of these nonlinear optical approaches to the study of breast cancer holds particular promise. These noninvasive, multidimensional techniques are well suited to image exogenous fluorophores that allow relevant questions regarding protein localization and signaling to be addressed both in vivo and in vitro.

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Background: Mammographically dense breast tissue is one of the greatest risk factors for developing breast carcinoma. Despite the strong clinical correlation, breast density has not been causally linked to tumorigenesis, largely because no animal model has existed for studying breast tissue density. Importantly, regions of high breast density are associated with increased stromal collagen.

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Background: 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.

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One of the most misunderstood concepts in progressive educational curricula is that of problem-based learning (PBL). Often confused with problem solving, the two are quite different. Courses conducted in a PBL format use problems as a launch pad for resulting study.

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E2F6 contains a DNA binding domain that is very similar to that of the other members of the E2F family of transcriptional regulators. However, E2F6 cannot bind to all promoters that contain consensus E2F-binding sites. Therefore, we used a combination of chromatin immunoprecipitation and genomic microarrays to identify promoters bound by E2F6 in human cells.

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