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\n@article{fereshteh_e-selectin_2023,\n\ttitle = {E-{Selectin} {Targeted} {Gold} {Nanoshells} to {Inhibit} {Breast} {Cancer} {Cell} {Binding} to {Lung} {Endothelial} {Cells}},\n\tvolume = {6},\n\tissn = {2574-0970, 2574-0970},\n\turl = {https://pubs.acs.org/doi/10.1021/acsanm.2c04967},\n\tdoi = {10.1021/acsanm.2c04967},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2024-02-13},\n\tjournal = {ACS Applied Nano Materials},\n\tauthor = {Fereshteh, Z. and Dang, M.N. and Wenck, C. and Day, E.S. and Slater, J.H.},\n\tmonth = jan,\n\tyear = {2023},\n\tpages = {1315--1324},\n}\n\n\n
@article{farino_reyes_tuning_2022,\n\ttitle = {Tuning {Hydrogel} {Adhesivity} and {Degradability} to {Model} the {Influence} of {Premetastatic} {Niche} {Matrix} {Properties} on {Breast} {Cancer} {Dormancy} and {Reactivation}},\n\tvolume = {6},\n\tissn = {2701-0198, 2701-0198},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/adbi.202200012},\n\tdoi = {10.1002/adbi.202200012},\n\tabstract = {Abstract \n \n Dormant, disseminated tumor cells (DTCs) can persist for decades in secondary tissues before being reactivated to form tumors. The properties of the premetastatic niche can influence the DTC phenotype. To better understand how matrix properties of premetastatic niches influence DTC behavior, three hydrogel formulations are implemented to model a permissive niche and two nonpermissive niches. Poly(ethylene glycol) (PEG)‐based hydrogels with varying adhesivity ([RGDS]) and degradability ([N‐vinyl pyrrolidinone]) are implemented to mimic a permissive niche with high adhesivity and degradability and two nonpermissive niches, one with moderate adhesivity and degradability and one with no adhesivity and high degradability. The influence of matrix properties on estrogen receptor positive (ER \n + \n ) breast cancer cells (MCF7s) is determined via a multimetric analysis. MCF7s cultured in the permissive niche adopted a growth state, while those in the nonpermissive niche with reduced adhesivity and degradability underwent tumor mass dormancy. Complete removal of adhesivity while maintaining high degradability induced single cell dormancy. The ability to mimic reactivation of dormant cells through a dynamic increase in [RGDS] is also demonstrated. This platform provides the capability of inducing growth, dormancy, and reactivation of ER \n + \n breast cancer and can be useful in understanding how premetastatic niche properties influence cancer cell fate.},\n\tlanguage = {en},\n\tnumber = {5},\n\turldate = {2024-02-13},\n\tjournal = {Advanced Biology},\n\tauthor = {Farino Reyes, Cindy J. and Slater, John H.},\n\tmonth = may,\n\tyear = {2022},\n\tpages = {2200012},\n}\n\n\n
@article{millarhaskell_secretion_2022,\n\ttitle = {Secretion of the disulphide bond generating catalyst {QSOX1} from pancreatic tumour cells into the extracellular matrix: {Association} with extracellular vesicles and matrix proteins},\n\tvolume = {1},\n\tissn = {2768-2811, 2768-2811},\n\tshorttitle = {Secretion of the disulphide bond generating catalyst {QSOX1} from pancreatic tumour cells into the extracellular matrix},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/jex2.48},\n\tdoi = {10.1002/jex2.48},\n\tabstract = {Abstract \n \n Quiescin sulfhydryl oxidase 1 (QSOX1) is a disulphide bond generating catalyst that is overexpressed in solid tumours. Expression of QSOX1 is linked to cancer cell invasion, tumour grade, and aberrant extracellular matrix (ECM) protein deposition. While the secreted version of QSOX1 is known to be present in various fluids and secretory tissues, its presence in the ECM of cancer is less understood. To characterize secreted QSOX1, we isolated extracellular vesicles (and particles) (EV(P)s) from conditioned media using ultracentrifugation and separated the supernatant using tangential flow filtration. We discovered that most of the secreted QSOX1 resides in the EVP‐depleted supernatant and in the soluble protein fraction. Very little QSOX1 could be detected in the EVP fraction. We used immunofluorescence to image subpopulations of EVs and found QSOX1 in Golgi‐derived vesicles and medium/large vesicles, but in general, most extracellular QSOX1 was not attributed to these vesicles. Next, we quantified QSOX1 co‐localization with the EV marker Alix. For the medium/large EVs, ∼98\\% contained QSOX1 when fibronectin was used as a coating. However, on collagen coatings, only ∼60\\% of these vesicles contained QSOX1, suggesting differences in EV cargo based on ECM coated surfaces. About 10\\% of small EVs co‐localized with QSOX1 on every ECM protein surface except for collagen (0.64\\%). We next investigated adhesion of QSOX1 to ECM proteins \n in vitro \n and \n in situ \n and found that QSOX1 preferentially adheres to fibronectin, laminins, and Matrigel compared to gelatin and collagen. This mechanism was found to be, in part, mediated by the formation of mixed disulphides between QSOX1 and cysteine‐rich ECM proteins. In summary, we found that QSOX1 (1) is in subpopulations of medium/large EVs, (2) seems to interact with small Alix+ EVs, and (3) adheres to cysteine‐rich ECM proteins, potentially through the formation of intermediate disulphides. These observations offer significant insight into how enzymes, such as QSOX1, can facilitate matrix remodelling events in solid tumour progression.},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2024-02-13},\n\tjournal = {Journal of Extracellular Biology},\n\tauthor = {Millar‐Haskell, Catherine S. and Sperduto, John L. and Slater, John H. and Thorpe, Colin and Gleghorn, Jason P.},\n\tmonth = jul,\n\tyear = {2022},\n\tpages = {e48},\n}\n\n\n
@misc{trompeter_extracellular_2021,\n\ttitle = {Extracellular {Matrix} {Stiffness} {Alters} {TRPV4} {Regulation} in {Chondrocytes}},\n\tcopyright = {© 2021, Posted by Cold Spring Harbor Laboratory. This pre-print is available under a Creative Commons License (Attribution-NonCommercial-NoDerivs 4.0 International), CC BY-NC-ND 4.0, as described at http://creativecommons.org/licenses/by-nc-nd/4.0/},\n\turl = {https://www.biorxiv.org/content/10.1101/2021.09.14.460172v1},\n\tdoi = {10.1101/2021.09.14.460172},\n\tabstract = {During the progression of osteoarthritis (OA), degradation of the extracellular matrix alters the biomechanical properties of cartilage, especially the compressive modulus. The mechanosensitive ion channel transient receptor potential vanilloid 4 (TRPV4) is required for chondrocyte mechanotransduction However, how OA-mediated cartilage degradation influences TRPV4 signaling remains unknown. To determine if ATDC5 cells alter TRPV4-mediated calcium signaling and cell phenotype in response to softer substrates, we created PEGDA-RGDS hydrogels with Young’s moduli that simulated healthy ({\\textasciitilde}350 kPa), OA ({\\textasciitilde}175 kPa) and severe OA ({\\textasciitilde}35 kPa) tissue. We found that softer substrates reduced the influx of calcium through TRPV4 when challenging chondrocytes with hypotonic swelling (HTS). Chondrocyte apoptosis also increased on the OA and severe OA gels due to elevated basal [Ca2+]i, which is attenuated with pharmacological agonism of TRPV4. Pharmacological agonism of TRPV4 rescued the expression of aggrecan and TRPV4 in chondrocytes cultured on OA gels and enhanced the type II collagen (col2) expression in cells on the normal and OA gels. These data suggest that the biomechanical properties of degraded cartilage alter TRPV4-mediated mechanotransduction in chondrocytes. Given that TRPV4 reduced apoptosis and improved the chondrogenic capacity of cells, TRPV4 stimulation could provide a potential therapeutic target in patients with early to moderate OA.},\n\tlanguage = {en},\n\turldate = {2024-02-13},\n\tpublisher = {bioRxiv},\n\tauthor = {Trompeter, Nicholas and Farino, Cindy J. and Griffin, Mallory and Skinner, Ryan and Banda, Omar A. and Gleghorn, Jason P. and Slater, John H. and Duncan, Randall L.},\n\tmonth = sep,\n\tyear = {2021},\n}\n\n\n
@article{farino_reyes_influence_2021,\n\ttitle = {The {Influence} of {Ligand} {Density} and {Degradability} on {Hydrogel} {Induced} {Breast} {Cancer} {Dormancy} and {Reactivation}},\n\tvolume = {10},\n\tissn = {2192-2640, 2192-2659},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/adhm.202002227},\n\tdoi = {10.1002/adhm.202002227},\n\tlanguage = {en},\n\tnumber = {11},\n\turldate = {2023-01-10},\n\tjournal = {Advanced Healthcare Materials},\n\tauthor = {Farino Reyes, Cindy J. and Pradhan, Shantanu and Slater, John H.},\n\tmonth = jun,\n\tyear = {2021},\n\tpages = {2002227},\n}\n\n
@article{pradhan_biofabrication_2020,\n\ttitle = {Biofabrication {Strategies} and {Engineered} {In} {Vitro} {Systems} for {Vascular} {Mechanobiology}},\n\tvolume = {9},\n\tissn = {2192-2640, 2192-2659},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/adhm.201901255},\n\tdoi = {10.1002/adhm.201901255},\n\tabstract = {Abstract \n The vascular system is integral for maintaining organ‐specific functions and homeostasis. Dysregulation in vascular architecture and function can lead to various chronic or acute disorders. Investigation of the role of the vascular system in health and disease has been accelerated through the development of tissue‐engineered constructs and microphysiological on‐chip platforms. These in vitro systems permit studies of biochemical regulation of vascular networks and parenchymal tissue and provide mechanistic insights into the biophysical and hemodynamic forces acting in organ‐specific niches. Detailed understanding of these forces and the mechanotransductory pathways involved is necessary to develop preventative and therapeutic strategies targeting the vascular system. This review describes vascular structure and function, the role of hemodynamic forces in maintaining vascular homeostasis, and measurement approaches for cell and tissue level mechanical properties influencing vascular phenomena. State‐of‐the‐art techniques for fabricating in vitro microvascular systems, with varying degrees of biological and engineering complexity, are summarized. Finally, the role of vascular mechanobiology in organ‐specific niches and pathophysiological states, and efforts to recapitulate these events using in vitro microphysiological systems, are explored. It is hoped that this review will help readers appreciate the important, but understudied, role of vascular‐parenchymal mechanotransduction in health and disease toward developing mechanotherapeutics for treatment strategies.},\n\tlanguage = {en},\n\tnumber = {8},\n\turldate = {2024-02-13},\n\tjournal = {Advanced Healthcare Materials},\n\tauthor = {Pradhan, Shantanu and Banda, Omar A. and Farino, Cindy J. and Sperduto, John L. and Keller, Keely A. and Taitano, Ryan and Slater, John H.},\n\tmonth = apr,\n\tyear = {2020},\n\tpages = {1901255},\n}\n\n\n
@article{farino_influence_2020,\n\ttitle = {The {Influence} of {Matrix}-{Induced} {Dormancy} on {Metastatic} {Breast} {Cancer} {Chemoresistance}},\n\tvolume = {3},\n\turl = {https://doi.org/10.1021/acsabm.0c00549},\n\tdoi = {10.1021/acsabm.0c00549},\n\tabstract = {Metastasis remains the leading cause of cancer-associated death worldwide. Disseminated tumor cells can undergo dormancy upon infiltration of secondary organs, and chemotherapeutics fail to effectively eliminate dormant populations. Mechanistic understanding of dormancy-associated chemoresistance could lead to development of targeted therapeutic strategies. Toward this goal, we implemented three poly(ethylene glycol) (PEG)-based hydrogel formulations fabricated from proteolytically degradable PEG (PEG-PQ), integrin ligating PEG-RGDS, and the non-degradable cross-linker N-vinylpyrrolidone (NVP) to induce three distinct phenotypes in triple negative MDA-MB-231 breast cancer cells. With constant 5\\% w/v PEG-PQ, PEG-RGDS and NVP concentrations were tuned to induce (i) a growth state characterized by high proliferation, high metabolic activity, significant temporally increased cell density, and an invasive morphology; (ii) a balanced dormancy state characterized by a temporal balance (∼1:1 ratio) in new live and dead cell density and a non-invasive morphology; and (iii) a cellular dormancy state characterized by rounded, solitary quiescent cells with low viability, proliferation, and metabolic activity. The cellular responses to doxorubicin (DOX), paclitaxel (PAC), and 5-fluorouracil (5-FU) in the three phenotypic states were quantified. Under DOX treatment, cells in dormant states demonstrated increased chemoresistance with a 1.4- to 1.8-fold increase in half maximal effective concentration (EC50) and 1.3- to 1.8-fold increase in half maximal inhibitory concentration (IC50) compared to cells in the growth state. PAC and 5-FU treatment led to similar results. To mechanistically investigate the role of dormancy in conferring DOX resistance, cytoplasmic and nuclear accumulation of DOX was measured. The results indicated comparable DOX accumulation between all three phenotypic states; however, the intracellular to intranuclear distribution indicated a ∼1.5 fold increase in DOX nuclear accumulation in cells in the growth state compared to the two dormant states. These results further validate the utility of implementing engineered hydrogels as in vitro platforms of breast cancer dormancy for the development of anti-dormancy therapeutic strategies.},\n\tnumber = {9},\n\turldate = {2024-01-16},\n\tjournal = {ACS Applied Bio Materials},\n\tauthor = {Farino, Cindy J. and Pradhan, Shantanu and Slater, John H.},\n\tmonth = sep,\n\tyear = {2020},\n\tnote = {Publisher: American Chemical Society},\n\tpages = {5832--5844},\n}\n\n\n
@article{guo_accurate_2019,\n\ttitle = {Accurate flow in augmented networks ({AFAN}): an approach to generating three-dimensional biomimetic microfluidic networks with controlled flow},\n\tvolume = {11},\n\tshorttitle = {Accurate flow in augmented networks ({AFAN})},\n\turl = {https://pubs.rsc.org/en/content/articlelanding/2019/ay/c8ay01798k},\n\tdoi = {10.1039/C8AY01798K},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-02-13},\n\tjournal = {Analytical Methods},\n\tauthor = {Guo, Jiaming and A. Keller, Keely and Govyadinov, Pavel and Ruchhoeft, Paul and H. Slater, John and Mayerich, David},\n\tyear = {2019},\n\tpages = {8--16},\n}\n\n\n
@article{smith_brain_2019,\n\ttitle = {Brain {Capillary} {Networks} {Across} {Species}: {A} few {Simple} {Organizational} {Requirements} {Are} {Sufficient} to {Reproduce} {Both} {Structure} and {Function}},\n\tvolume = {10},\n\tissn = {1664-042X},\n\tshorttitle = {Brain {Capillary} {Networks} {Across} {Species}},\n\turl = {https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2019.00233},\n\tabstract = {Despite the key role of the capillaries in neurovascular function, a thorough characterization of cerebral capillary network properties is currently lacking. Here, we define a range of metrics (geometrical, topological, flow, mass transfer, and robustness) for quantification of structural differences between brain areas, organs, species, or patient populations and, in parallel, digitally generate synthetic networks that replicate the key organizational features of anatomical networks (isotropy, connectedness, space-filling nature, convexity of tissue domains, characteristic size). To reach these objectives, we first construct a database of the defined metrics for healthy capillary networks obtained from imaging of mouse and human brains. Results show that anatomical networks are topologically equivalent between the two species and that geometrical metrics only differ in scaling. Based on these results, we then devise a method which employs constrained Voronoi diagrams to generate 3D model synthetic cerebral capillary networks that are locally randomized but homogeneous at the network-scale. With appropriate choice of scaling, these networks have equivalent properties to the anatomical data, demonstrated by comparison of the defined metrics. The ability to synthetically replicate cerebral capillary networks opens a broad range of applications, ranging from systematic computational studies of structure-function relationships in healthy capillary networks to detailed analysis of pathological structural degeneration, or even to the development of templates for fabrication of 3D biomimetic vascular networks embedded in tissue-engineered constructs.},\n\turldate = {2024-02-13},\n\tjournal = {Frontiers in Physiology},\n\tauthor = {Smith, Amy F. and Doyeux, Vincent and Berg, Maxime and Peyrounette, Myriam and Haft-Javaherian, Mohammad and Larue, Anne-Edith and Slater, John H. and Lauwers, Frédéric and Blinder, Pablo and Tsai, Philbert and Kleinfeld, David and Schaffer, Chris B. and Nishimura, Nozomi and Davit, Yohan and Lorthois, Sylvie},\n\tyear = {2019},\n}\n\n\n
@article{banda_reference-free_2019,\n\ttitle = {Reference-{Free} {Traction} {Force} {Microscopy} {Platform} {Fabricated} via {Two}-{Photon} {Laser} {Scanning} {Lithography} {Enables} {Facile} {Measurement} of {Cell}-{Generated} {Forces}},\n\tvolume = {11},\n\tissn = {1944-8244, 1944-8252},\n\turl = {https://pubs.acs.org/doi/10.1021/acsami.9b04362},\n\tdoi = {10.1021/acsami.9b04362},\n\tlanguage = {en},\n\tnumber = {20},\n\turldate = {2024-02-13},\n\tjournal = {ACS Applied Materials \\& Interfaces},\n\tauthor = {Banda, Omar A. and Sabanayagam, Chandran R. and Slater, John H.},\n\tmonth = may,\n\tyear = {2019},\n\tpages = {18233--18241},\n}\n\n\n
@article{banda_fabrication_2019,\n\ttitle = {Fabrication and {Implementation} of a {Reference}-{Free} {Traction} {Force} {Microscopy} {Platform}},\n\tissn = {1940-087X},\n\turl = {https://www.jove.com/t/60383/fabrication-implementation-reference-free-traction-force-microscopy},\n\tdoi = {10.3791/60383},\n\tlanguage = {en},\n\tnumber = {152},\n\turldate = {2024-02-13},\n\tjournal = {Journal of Visualized Experiments},\n\tauthor = {Banda, Omar A. and Slater, John H.},\n\tmonth = oct,\n\tyear = {2019},\n\tpages = {60383},\n}\n\n\n
@article{pradhan_tunable_2019,\n\ttitle = {Tunable {Hydrogels} for {Controlling} {Phenotypic} {Cancer} {Cell} {States} to {Model} {Breast} {Cancer} {Dormancy} and {Reactivation}},\n\tvolume = {215},\n\tissn = {0142-9612},\n\turl = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6592634/},\n\tdoi = {10.1016/j.biomaterials.2019.04.022},\n\tabstract = {During metastasis, disseminated tumor cells (DTCs) from the primary tumor infiltrate secondary organs and reside there for varying lengths of time prior to forming new tumors. The time delay between infiltration and active proliferation, known as dormancy, mediates the length of the latency period. DTCs may undergo one of four fates post-infiltration: death, cellular dormancy, dormant micrometastasis, or invasive growth which, is in part, mediated by extracellular matrix (ECM) properties. Recapitulation of these cell states using engineered hydrogels could facilitate the systematic and controlled investigation of the mechanisms by which ECM properties influence DTC fate. Toward this goal, we implemented a set of sixteen hydrogels with systematic variations in chemical (ligand (RGDS) density and enzymatic degradability) and mechanical (elasticity, swelling, mesh size) properties to investigate their influence on the fate of encapsulated metastatic breast cancer cells, MDA-MB-231. Cell viability, apoptosis, proliferation, metabolic activity, and morphological measurements were acquired at five-day intervals over fifteen days in culture. Analysis of the phenotypic metrics indicated the presence of four different cell states that were classified as: (1) high growth, (2) moderate growth, (3) single cell, restricted survival, dormancy, or (4) balanced dormancy. Correlating hydrogel properties with the resultant cancer cell state indicated that ligand (RGDS) density and enzymatic degradability likely had the most influence on cell fate. Furthermore, we demonstrate the ability to reactivate cells from the single cell, dormant state to the high growth state through a dynamic increase in ligand (RGDS) density after forty days in culture. This tunable engineered hydrogel platform offers insight into matrix properties regulating tumor dormancy, and the dormancy-proliferation switch, and may provide future translational benefits toward development of anti-dormancy therapeutic strategies.},\n\turldate = {2024-01-11},\n\tjournal = {Biomaterials},\n\tauthor = {Pradhan, Shantanu and Slater, John H.},\n\tmonth = sep,\n\tyear = {2019},\n\tpmid = {31176804},\n\tpmcid = {PMC6592634},\n\tpages = {119177},\n}\n\n\n
@article{pradhan_datasets_2019,\n\ttitle = {Datasets describing hydrogel properties and cellular metrics for modeling of tumor dormancy},\n\tvolume = {25},\n\tissn = {2352-3409},\n\tdoi = {10.1016/j.dib.2019.104128},\n\tabstract = {Breast cancer dormancy is an underlying challenge toward targeting and controlling metastatic recurrence and disease progression. Development of engineered, well-defined in vitro models is necessary to systematically recapitulate tumor dormancy and investigate potential therapeutic strategies. Toward this end, a set of sixteen hydrogel formulations with varying degrees of adhesivity and crosslink density was developed for encapsulation, three-dimensional (3D) culture, and phenotypic assessment of MDA-MB-231 breast cancer cells. The hydrogel adhesivity was regulated by incorporation of RGDS peptide conjugated to acrylate poly(ethylene glycol) (PEG-RGDS) and the crosslink density by incorporation of N-vinyl pyrrolidinone (NVP). Here, we present data concerning the characterization of hydrogel properties (PEG-RGDS incorporation, hydrogel crosslink density, and hydrogel diffusivity as a function of NVP concentration) and phenotypic metrics (viability, early apoptosis, proliferation, metabolic activity, viable cell density, and morphological features) of encapsulated MDA-MB-231s over 15 days in culture. Interpretation of this data can be found in a research article titled "Tunable Hydrogels for Controlling Phenotypic Cancer Cell States to Model Breast Cancer Dormancy and Reactivation" (Pradhan et al., 2019) [1].},\n\tlanguage = {eng},\n\tjournal = {Data in Brief},\n\tauthor = {Pradhan, Shantanu and Slater, John H.},\n\tmonth = aug,\n\tyear = {2019},\n\tpmid = {31312698},\n\tpmcid = {PMC6609726},\n\tkeywords = {Cancer, Dormancy, Hydrogel, Metastasis, Relapse, Tissue engineering},\n\tpages = {104128},\n}\n\n\n
@article{pradhan_fabrication_2019,\n\ttitle = {Fabrication, characterization, and implementation of engineered hydrogels for controlling breast cancer cell phenotype and dormancy},\n\tvolume = {6},\n\tissn = {22150161},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S2215016119303140},\n\tdoi = {10.1016/j.mex.2019.11.011},\n\tabstract = {A better understanding of how microenvironmental factors regulate cancer dormancy is needed for development of new therapeutic strategies to control metastatic recurrence and disease progression. Modeling cancer dormancy using engineered, in vitro platforms is necessary for investigation under well-defined and wellcontrolled microenvironments. We present methods and protocols to fabricate, characterize, and implement engineered hydrogels with well-defined biochemical and physical properties for control over breast cancer cell phenotype in three-dimensional (3D) culture. Changes in hydrogel adhesivity, crosslink density, and degradability induce a range of phenotypic behaviors in breast cancer cells including: (1) high growth, (2) moderate growth, (3) single cell, restricted survival dormancy, and (4) balanced dormancy. We describe a method of classifying hydrogel formulations that support each of these phenotypic states. We also describe a method to phenotypically switch cancer cells from single cell dormancy to high growth by dynamically modulating ligand density, thereby recapitulating reactivation and metastatic recurrence.},\n\tlanguage = {en},\n\turldate = {2023-01-10},\n\tjournal = {MethodsX},\n\tauthor = {Pradhan, Shantanu and Slater, John H.},\n\tyear = {2019},\n\tpages = {2744--2766},\n}\n\n\n
@article{pradhan_engineered_2018,\n\ttitle = {Engineered {In} {Vitro} {Models} of {Tumor} {Dormancy} and {Reactivation}},\n\tvolume = {12},\n\tissn = {1754-1611},\n\turl = {https://jbioleng.biomedcentral.com/articles/10.1186/s13036-018-0120-9},\n\tdoi = {10.1186/s13036-018-0120-9},\n\tabstract = {Metastatic recurrence is a major hurdle to overcome for successful control of cancer-associated death. Residual tumor cells in the primary site, or disseminated tumor cells in secondary sites, can lie in a dormant state for long time periods, years to decades, before being reactivated into a proliferative growth state. The microenvironmental signals and biological mechanisms that mediate the fate of disseminated cancer cells with respect to cell death, single cell dormancy, tumor mass dormancy and metastatic growth, as well as the factors that induce reactivation, are discussed in this review. Emphasis is placed on engineered, in vitro, biomaterial-based approaches to model tumor dormancy and subsequent reactivation, with a focus on the roles of extracellular matrix, secondary cell types, biochemical signaling and drug treatment. A brief perspective of molecular targets and treatment approaches for dormant tumors is also presented. Advances in tissue-engineered platforms to induce, model, and monitor tumor dormancy and reactivation may provide much needed insight into the regulation of these processes and serve as drug discovery and testing platforms.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2023-01-10},\n\tjournal = {Journal of Biological Engineering},\n\tauthor = {Pradhan, Shantanu and Sperduto, John L. and Farino, Cindy J. and Slater, John H.},\n\tmonth = dec,\n\tyear = {2018},\n\tpages = {37},\n}\n\n\n
@article{heintz_image-guided_2017,\n\ttitle = {Image-guided, {Laser}-based {Fabrication} of {Vascular}-derived {Microfluidic} {Networks}},\n\tissn = {1940-087X},\n\turl = {https://www.jove.com/t/55101/image-guided-laser-based-fabrication-vascular-derived-microfluidic},\n\tdoi = {10.3791/55101},\n\tlanguage = {en},\n\tnumber = {119},\n\turldate = {2024-02-13},\n\tjournal = {Journal of Visualized Experiments},\n\tauthor = {Heintz, Keely A. and Mayerich, David and Slater, John H.},\n\tmonth = jan,\n\tyear = {2017},\n\tpages = {55101},\n}\n\n\n
@article{pradhan_fundamentals_2017,\n\ttitle = {Fundamentals of {Laser}‐{Based} {Hydrogel} {Degradation} and {Applications} in {Cell} and {Tissue} {Engineering}},\n\tvolume = {6},\n\tissn = {2192-2640, 2192-2659},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/adhm.201700681},\n\tdoi = {10.1002/adhm.201700681},\n\tabstract = {Abstract \n The cell and tissue engineering fields have profited immensely through the implementation of highly structured biomaterials. The development and implementation of advanced biofabrication techniques have established new avenues for generating biomimetic scaffolds for a multitude of cell and tissue engineering applications. Among these, laser‐based degradation of biomaterials is implemented to achieve user‐directed features and functionalities within biomimetic scaffolds. This review offers an overview of the physical mechanisms that govern laser–material interactions and specifically, laser–hydrogel interactions. The influences of both laser and material properties on efficient, high‐resolution hydrogel degradation are discussed and the current application space in cell and tissue engineering is reviewed. This review aims to acquaint readers with the capability and uses of laser‐based degradation of biomaterials, so that it may be easily and widely adopted.},\n\tlanguage = {en},\n\tnumber = {24},\n\turldate = {2024-02-13},\n\tjournal = {Advanced Healthcare Materials},\n\tauthor = {Pradhan, Shantanu and Keller, Keely A. and Sperduto, John L. and Slater, John H.},\n\tmonth = dec,\n\tyear = {2017},\n\tpages = {1700681},\n}\n\n\n
@incollection{slater_biomimetic_2016,\n\taddress = {Cham},\n\tseries = {Springer {Series} in {Biomaterials} {Science} and {Engineering}},\n\ttitle = {Biomimetic {Surfaces} for {Cell} {Engineering}},\n\tisbn = {9783319228617},\n\turl = {https://doi.org/10.1007/978-3-319-22861-7_18},\n\tabstract = {Cell behavior, in particular, migration, proliferation, differentiation, apoptosis, and activation, is mediated by a multitude of environmental factors: (i) extracellular matrix (ECM) properties including molecular composition, ligand density, ligand gradients, stiffness, topography, and degradability; (ii) soluble factors including type, concentration, and gradients; (iii) cell–cell interactions; and (iv) external forces such as shear stress, material strain, osmotic pressure, and temperature changes. The coordinated influence of these environmental cues regulate embryonic development, tissue function, homeostasis, and wound healing as well as other crucial events in vivo. From a fundamental biology perspective, it is of great interest to understand how these environmental factors regulate cell fate and ultimately cell and tissue function. From an engineering perspective, it is of interest to determine how to present these factors in a well-controlled manner to elicit a desired cell output for cell and tissue engineering applications. Both biophysical and biochemical factors mediate intracellular signaling cascades that influence gene expression and ultimately cell behavior, making it difficult to unravel the hierarchy of cell fate stimuli. Accordingly, much effort has focused on the fabrication of biomimetic surfaces that recapitulate a single or many aspects of the in vivo microenvironment including topography, elasticity, and ligand presentation, and by structured materials that allow for control over cell shape, spreading, and cytoskeletal tension. Controlled presentation of these properties to develop a desired microenvironment can be harnessed to guide cell fate decisions toward chosen paths and has provided a wealth of knowledge concerning which cues regulate apoptosis, proliferation, migration, lineage-specific stem cell differentiation, and immune cell activation to name a few. This chapter focuses on the implementation of biomimetic surfaces that recapitulate and control one or more aspects of the cellular microenvironment to induce a desired cell response. More specifically, biomimetic surfaces that mimic in vivo ECM composition, density, gradients, stiffness, or topography; those that allow for control over cell shape, spreading, or cytoskeletal tension; and those that mimic cell surfaces are discussed.},\n\tlanguage = {en},\n\turldate = {2024-02-13},\n\tbooktitle = {Carbon {Nanomaterials} for {Biomedical} {Applications}},\n\tpublisher = {Springer International Publishing},\n\tauthor = {Slater, John H. and Banda, Omar A. and Heintz, Keely A. and Nie, Hetty T.},\n\teditor = {Zhang, Mei and Naik, Rajesh R. and Dai, Liming},\n\tyear = {2016},\n\tdoi = {10.1007/978-3-319-22861-7_18},\n\tkeywords = {Adhesion Site, Leukocyte Adhesion Deficiency, Ligand Density, Major Histocompatibility Complex, Substrate Stiffness},\n\tpages = {543--569},\n}\n\n\n
@article{shukla_biomimetic_2016,\n\ttitle = {Biomimetic {Surface} {Patterning} {Promotes} {Mesenchymal} {Stem} {Cell} {Differentiation}},\n\tvolume = {8},\n\tissn = {1944-8244, 1944-8252},\n\turl = {https://pubs.acs.org/doi/10.1021/acsami.5b08978},\n\tdoi = {10.1021/acsami.5b08978},\n\tlanguage = {en},\n\tnumber = {34},\n\turldate = {2024-02-13},\n\tjournal = {ACS Applied Materials \\& Interfaces},\n\tauthor = {Shukla, Anita and Slater, John H. and Culver, James C. and Dickinson, Mary E. and West, Jennifer L.},\n\tmonth = aug,\n\tyear = {2016},\n\tpages = {21883--21892},\n}\n\n\n
@article{heintz_fabrication_2016,\n\ttitle = {Fabrication of {3D} {Biomimetic} {Microfluidic} {Networks} in {Hydrogels}},\n\tvolume = {5},\n\tissn = {2192-2640, 2192-2659},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/adhm.201600351},\n\tdoi = {10.1002/adhm.201600351},\n\tlanguage = {en},\n\tnumber = {17},\n\turldate = {2024-02-13},\n\tjournal = {Advanced Healthcare Materials},\n\tauthor = {Heintz, Keely A. and Bregenzer, Michael E. and Mantle, Jennifer L. and Lee, Kelvin H. and West, Jennifer L. and Slater, John H.},\n\tmonth = sep,\n\tyear = {2016},\n\tpages = {2153--2160},\n}\n\n\n
@article{slater_modulation_2015,\n\ttitle = {Modulation of {Endothelial} {Cell} {Migration} via {Manipulation} of {Adhesion} {Site} {Growth} {Using} {Nanopatterned} {Surfaces}},\n\tvolume = {7},\n\tissn = {1944-8244, 1944-8252},\n\turl = {https://pubs.acs.org/doi/10.1021/am508906f},\n\tdoi = {10.1021/am508906f},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2024-02-13},\n\tjournal = {ACS Applied Materials \\& Interfaces},\n\tauthor = {Slater, John H. and Boyce, Patrick J. and Jancaitis, Matthew P. and Gaubert, Harold E. and Chang, Alex L. and Markey, Mia K. and Frey, Wolfgang},\n\tmonth = feb,\n\tyear = {2015},\n\tpages = {4390--4400},\n}\n\n\n
@article{slater_recapitulation_2015,\n\ttitle = {Recapitulation and {Modulation} of the {Cellular} {Architecture} of a {User}-{Chosen} {Cell} of {Interest} {Using} {Cell}-{Derived}, {Biomimetic} {Patterning}},\n\tvolume = {9},\n\tissn = {1936-0851, 1936-086X},\n\turl = {https://pubs.acs.org/doi/10.1021/acsnano.5b01366},\n\tdoi = {10.1021/acsnano.5b01366},\n\tlanguage = {en},\n\tnumber = {6},\n\turldate = {2024-02-13},\n\tjournal = {ACS Nano},\n\tauthor = {Slater, John H. and Culver, James C. and Long, Byron L. and Hu, Chenyue W. and Hu, Jingzhe and Birk, Taylor F. and Qutub, Amina A. and Dickinson, Mary E. and West, Jennifer L.},\n\tmonth = jun,\n\tyear = {2015},\n\tpages = {6128--6138},\n}\n\n\n
@article{hu_progeny_2015,\n\ttitle = {Progeny {Clustering}: {A} {Method} to {Identify} {Biological} {Phenotypes}},\n\tvolume = {5},\n\tcopyright = {2015 The Author(s)},\n\tissn = {2045-2322},\n\tshorttitle = {Progeny {Clustering}},\n\turl = {https://www.nature.com/articles/srep12894},\n\tdoi = {10.1038/srep12894},\n\tabstract = {Estimating the optimal number of clusters is a major challenge in applying cluster analysis to any type of dataset, especially to biomedical datasets, which are high-dimensional and complex. Here, we introduce an improved method, Progeny Clustering, which is stability-based and exceptionally efficient in computing, to find the ideal number of clusters. The algorithm employs a novel Progeny Sampling method to reconstruct cluster identity, a co-occurrence probability matrix to assess the clustering stability and a set of reference datasets to overcome inherent biases in the algorithm and data space. Our method was shown successful and robust when applied to two synthetic datasets (datasets of two-dimensions and ten-dimensions containing eight dimensions of pure noise), two standard biological datasets (the Iris dataset and Rat CNS dataset) and two biological datasets (a cell phenotype dataset and an acute myeloid leukemia (AML) reverse phase protein array (RPPA) dataset). Progeny Clustering outperformed some popular clustering evaluation methods in the ten-dimensional synthetic dataset as well as in the cell phenotype dataset and it was the only method that successfully discovered clinically meaningful patient groupings in the AML RPPA dataset.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-02-13},\n\tjournal = {Scientific Reports},\n\tauthor = {Hu, Chenyue W. and Kornblau, Steven M. and Slater, John H. and Qutub, Amina A.},\n\tmonth = aug,\n\tyear = {2015},\n\tkeywords = {Classification and taxonomy, Computational biology and bioinformatics, Machine learning, Statistical methods},\n\tpages = {12894},\n}\n\n\n
@incollection{slater_chapter_2014,\n\tseries = {Micropatterning in {Cell} {Biology} {Part} {A}},\n\ttitle = {Chapter 11 - {Fabrication} of {Multifaceted}, {Micropatterned} {Surfaces} and {Image}-{Guided} {Patterning} {Using} {Laser} {Scanning} {Lithography}},\n\tvolume = {119},\n\turl = {https://www.sciencedirect.com/science/article/pii/B9780124167421000111},\n\tabstract = {This protocol describes the implementation of laser scanning lithography (LSL) for the fabrication of multifaceted, patterned surfaces and for image-guided patterning. This photothermal-based patterning technique allows for selective removal of desired regions of an alkanethiol self-assembled monolayer on a metal film through raster scanning a focused 532nm laser using a commercially available laser scanning confocal microscope. Unlike traditional photolithography methods, this technique does not require the use of a physical master and instead utilizes digital “virtual masks” that can be modified “on the fly” allowing for quick pattern modifications. The process to create multifaceted, micropatterned surfaces, surfaces that display pattern arrays of multiple biomolecules with each molecule confined to its own array, is described in detail. The generation of pattern configurations from user-chosen images, image-guided LSL is also described. This protocol outlines LSL in four basic sections. The first section details substrate preparation and includes cleaning of glass coverslips, metal deposition, and alkanethiol functionalization. The second section describes two ways to define pattern configurations, the first through manual input of pattern coordinates and dimensions using Zeiss AIM software and the second via image-guided pattern generation using a custom-written MATLAB script. The third section describes the details of the patterning procedure and postpatterning functionalization with an alkanethiol, protein, and both, and the fourth section covers cell seeding and culture. We end with a general discussion concerning the pitfalls of LSL and present potential improvements that can be made to the technique.},\n\turldate = {2024-02-13},\n\tbooktitle = {Methods in {Cell} {Biology}},\n\tpublisher = {Academic Press},\n\tauthor = {Slater, John H. and West, Jennifer L.},\n\teditor = {Piel, Matthieu and Théry, Manuel},\n\tmonth = jan,\n\tyear = {2014},\n\tdoi = {10.1016/B978-0-12-416742-1.00011-1},\n\tkeywords = {Alkanethiol, Lithography, Micropattern, Nanopattern, Photothermal},\n\tpages = {193--217},\n}\n\n\n
@article{culver_threedimensional_2012,\n\ttitle = {Three‐{Dimensional} {Biomimetic} {Patterning} in {Hydrogels} to {Guide} {Cellular} {Organization}},\n\tvolume = {24},\n\tissn = {0935-9648, 1521-4095},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/adma.201200395},\n\tdoi = {10.1002/adma.201200395},\n\tlanguage = {en},\n\tnumber = {17},\n\turldate = {2024-02-13},\n\tjournal = {Advanced Materials},\n\tauthor = {Culver, James C. and Hoffmann, Joseph C. and Poché, Ross A. and Slater, John H. and West, Jennifer L. and Dickinson, Mary E.},\n\tmonth = may,\n\tyear = {2012},\n\tpages = {2344--2348},\n}\n\n\n
@article{mcconnell_microcontact_2011,\n\ttitle = {Microcontact printing for co-patterning cells and viruses for spatially controlled substrate-mediated gene delivery},\n\tvolume = {7},\n\tissn = {1744-6848},\n\turl = {https://pubs.rsc.org/en/content/articlelanding/2011/sm/c0sm01209b},\n\tdoi = {10.1039/C0SM01209B},\n\tabstract = {Spatial organization of gene expression is a crucial element in the development of complex native tissues, and the capacity to achieve spatially controlled gene expression profiles in a tissue engineering construct is still a considerable challenge. To give tissue engineers the ability to design specific, spatially organized gene expression profiles in an engineered construct, we have investigated the use of microcontact printing to pattern recombinant adeno-associated virus (AAV) vectors on a two dimensional surface as a first proof-of-concept study. AAV is a highly safe, versatile, stable, and easy-to-use gene delivery vector, making it an ideal choice for this application. We tested the suitability of four chemical surfaces (–CH3, –COOH, –NH2, and –OH) to mediate localized substrate-mediated gene delivery. First, polydimethylsiloxane stamps were used to create microscale patterns of various self-assembled monolayers on gold-coated glass substrates. Next, AAV particles carrying genes of interest and human fibronectin (HFN) were immobilized on the patterned substrates, creating a spatially organized arrangement of gene delivery vectors. Immunostaining studies reveal that –CH3 and –NH2 surfaces result in the most successful adsorption of both AAV and HFN. Lastly, HeLa cells were used to analyze viral transduction and spatial localization of gene expression. We find that –CH3, –COOH, and –NH2 surfaces support complete uniform cell coverage with high gene expression. Notably, we observe a synergistic effect between HFN and AAV for substrate-mediated gene delivery. Our flexible platform should allow for the specific patterning of various gene and shRNA cassettes, resulting in spatially defined gene expression profiles that may enable the generation of highly functional tissue.},\n\tlanguage = {en},\n\tnumber = {10},\n\turldate = {2024-02-13},\n\tjournal = {Soft Matter},\n\tauthor = {McConnell, Kellie I. and Slater, John H. and Han, Arum and West, Jennifer L. and Suh, Junghae},\n\tmonth = may,\n\tyear = {2011},\n\tpages = {4993--5001},\n}\n\n\n
@article{slater_fabrication_2011,\n\ttitle = {Fabrication of {Multifaceted} {Micropatterned} {Surfaces} with {Laser} {Scanning} {Lithography}},\n\tvolume = {21},\n\tissn = {1616-301X, 1616-3028},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/adfm.201100297},\n\tdoi = {10.1002/adfm.201100297},\n\tabstract = {Abstract \n The implementation of engineered surfaces presenting micrometer‐sized patterns of cell adhesive ligands against a biologically inert background has led to numerous discoveries in fundamental cell biology. While existing surface patterning strategies allow patterning of a single ligand, it is still challenging to fabricate surfaces displaying multiple patterned ligands. To address this issue we implemented laser scanning lithography (LSL), a laser‐based thermal desorption technique, to fabricate multifaceted, micropatterned surfaces that display independent arrays of subcellular‐sized patterns of multiple adhesive ligands with each ligand confined to its own array. We demonstrate that LSL is a highly versatile “maskless” surface patterning strategy that provides the ability to create patterns with features ranging from 460 nm to 100 μm, topography ranging from ‐1 to 17 nm, and to fabricate both stepwise and smooth ligand surface density gradients. As validation for their use in cell studies, surfaces presenting orthogonally interwoven arrays of 1 μm × 8 μm elliptical patterns of Gly‐Arg‐Gly‐Asp‐terminated alkanethiol self‐assembled monolayers and human plasma fibronectin are produced. Human umbilical vein endothelial cells cultured on these multifaceted surfaces form adhesion sites to both ligands simultaneously and utilize both ligands for lamella formation during migration. The ability to create multifaceted, patterned surfaces with tight control over pattern size, spacing, and topography provides a platform to simultaneously investigate the complex interactions of extracellular matrix geometry, biochemistry, and topography on cell adhesion and downstream cell behavior.},\n\tlanguage = {en},\n\tnumber = {15},\n\turldate = {2024-02-13},\n\tjournal = {Advanced Functional Materials},\n\tauthor = {Slater, John H. and Miller, Jordan S. and Yu, Shann S. and West, Jennifer L.},\n\tmonth = aug,\n\tyear = {2011},\n\tpages = {2876--2888},\n}\n\n\n
@article{day_antibody-conjugated_2010,\n\ttitle = {Antibody-conjugated gold-gold sulfide nanoparticles as multifunctional agents for imaging and therapy of breast cancer},\n\tissn = {1178-2013},\n\turl = {http://www.dovepress.com/antibody-conjugated-gold-gold-sulfide-nanoparticles-as-multifunctional-peer-reviewed-article-IJN},\n\tdoi = {10.2147/IJN.S10881},\n\tlanguage = {en},\n\turldate = {2024-02-13},\n\tjournal = {International Journal of Nanomedicine},\n\tauthor = {{Day}},\n\tmonth = jun,\n\tyear = {2010},\n\tpages = {445},\n}\n\n\n
@article{slater_nanopatterning_2008,\n\ttitle = {Nanopatterning of fibronectin and the influence of integrin clustering on endothelial cell spreading and proliferation},\n\tvolume = {87A},\n\tissn = {1549-3296, 1552-4965},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/jbm.a.31725},\n\tdoi = {10.1002/jbm.a.31725},\n\tabstract = {Abstract \n Investigating stages of maturation of cellular adhesions to the extracellular matrix from the initial binding events to the formation of small focal complexes has been challenging because of the difficulty in fabricating the necessary nanopatterned substrates with controlled biochemical functionality. We present the fabrication and characterization of surfaces presenting fibronectin nanopatterns of controlled size and pitch that provide well‐defined cellular adhesion sites against a nonadhesive polyethylene glycol background. The nanopatterned surfaces allow us to control the number of fibronectin proteins within each adhesion site from 9 to 250, thereby limiting the number of integrins involved in each cell–substrate adhesion. We demonstrate the presence of fibronectin on the nanoislands, while no protein was observed on the passivated background. We show that the cell adheres to the nanopatterns with adhesions that are much smaller and more evenly distributed than on a glass control. The nanopattern influences cellular proliferation only at longer times, but influences spreading at both early and later times, indicating adhesion size and adhesion density play a role in controlling cell adhesion and signaling. However, the overall density of fibronectin on all patterns is far lower than on homogeneously coated control surfaces, showing that the local density of adhesion ligands, not the average density, is the important parameter for cell proliferation and spreading. © 2007 Wiley Periodicals, Inc. J Biomed Mater Res 87A: 176–195, 2008},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-02-13},\n\tjournal = {Journal of Biomedical Materials Research Part A},\n\tauthor = {Slater, John H. and Frey, Wolfgang},\n\tmonth = oct,\n\tyear = {2008},\n\tpages = {176--195},\n}\n\n\n