The authors would like to specifically acknowledge Carolyn Kim, Amelia Lao, Ryan Stoutamore, and Itay Solomon for their contributions to earlier iterations of the photogelation scheme. Cell lines GS122 and GS304 were generously provided by David Nathanson. All figures were created with BioRender.com. UCLA core facilities, the Molecular Screening Shared Resources, and the Nano and Pico Characterization Laboratory were instrumental to the work. Chen Chia-Chun was supported by the UCLA Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research Training Program. Grigor Varuzhanyan was supported by a Tumor Cell Biology Training Program NIH Grant (T32 CA 009056).

Patient-derived GBM cell lines (GS122 and GS304) were provided by Professor David Nathanson (our collaborator), who developed these lines under a protocol approved by the UCLA Institutional Review Board (IRB# 10-000655). Cells were provided de-identified so that the cell lines could not be linked back to the individual patients.
1. Preparation of hydrogel solution
<ol>
	<li>Prepare HEPES-buffered solution by dissolving HEPES powder at 20 mM in Hank&#39;s balanced salt solution (HBSS). Adjust pH to 7 following full solvation.</li>
	<li>In the HEPES-buffered solution, dissolve thiolated HA (700 kDa nominal molecular weight, see Table of Materials), prepared following the previous report31, so that 6%-8% of carboxylic acid residues on each glucuronic acid are modified with a thiol, at a concentration of 10 mg/mL in buffer solution. 
	NOTE: An amber vial is recommended to prevent thiol oxidation by ambient light.
	<ol>
		<li>Stir using a magnetic stir plate (&#60;1,000 rpm) at room temperature until fully dissolved, typically around 45 min.</li>
	</ol>
	</li>
	<li>While HA is dissolving, prepare separate solutions of (1) 100 mg/mL of 8-arm-PEG-Norbornene (20 kDa), (2) 100 mg/mL of 4-arm-PEG-Thiol (20 kDa), (3) 4 mM of cysteine or cysteine-containing peptide (e.g., GCGYGRGDSPG), and (4) 4 mg/mL of LAP in microcentrifuge tubes (see Table of Materials).
	<ol>
		<li>Prepare each of these four solutions in the HEPES-buffered solution prepared in step 1.1. Vortex the solutions to ensure full dissolution of each reagent prior to performing step 4. 
		NOTE: If testing multiple different peptides, each must contain a cysteine or other source of thiol moiety for this conjugation chemistry.</li>
		<li>Prepare solutions (4 mM available thiol) of all peptides to be tethered within a single hydrogel at this point. 
		NOTE: Peptide sequences and ECM proteins from which they were derived and used in this study are listed in Table 1. N-acetyl cysteine (see Table of Materials), to which cells do not bind, can be substituted for a bioactive, thiol-containing peptide to titrate the concentration of an adhesive peptide or act as a negative control31.</li>
	</ol>
	</li>
	<li>Mix the individual solutions of HA, PEG-Norbornene, PEG-thiol, and cysteine/thiol-containing peptides (see Table of Materials) to achieve the final concentrations for the final hydrogel matrices listed in Table 2. Stir (&#60;1,000 rpm) on a magnetic stir plate for at least 30 min to mix fully. 
	&#8203;NOTE: HA solutions are highly viscous and best handled using a positive displacement pipette (see Table of Materials). If a positive displacement pipette is unavailable, viscous solutions can also be dispensed with a standard micropipette by slowly pipetting using wide-orifice tips.</li>
</ol>
2. Illumination and photocrosslinking of hydrogels via an LED array
CAUTION: Wear UV protective eyewear and cover the illumination field with UV-absorbing material.
NOTE: The LED array described in this protocol consists of six sets of eight LEDs placed in series, as illustrated by the provided circuit diagram (Figure 1A). Each set of LEDs can be independently powered, which allows for up to six different irradiances per run. Supplementary File 1 contains screenshots corresponding to the following directions for further guidance.
<ol>
	<li>Download the Illumination Device.zip file from the Supplementary Coding Files. This directory contains the following files: Arduino.zip (Supplementary Coding File 1), Drivers.zip (Supplementary Coding File 2), GUI.zip (Supplementary Coding File 3), and Holder.zip (Supplementary Coding File 4). 
	NOTE: 3D Print the top and bottom portions for holding the circuit board in place (see Supplementary Coding Files for details).</li>
	<li>Download and install the microcontroller software (see Table of Materials).</li>
	<li>Download and install the GUI software (see Table of Materials). Refer to Supplementary File 1 for software operating instructions.</li>
	<li>Open Processing and install the controlIP5 library via clicking on Sketch &#62; Import Library &#62; Add Library. Then, search for controlIP5 in libraries and click on Install. Perform this for the very first time.</li>
	<li>Power the illumination device (see Table of Materials) using the 36 Volt power supply and connect it to a PC using a micro-USB cable. 
	NOTE: Some devices will not install drivers automatically for various Arduino nano boards. One set of drivers is provided in the device zip file.</li>
	<li>Open the Arduino.ino file, located in the Adruino.zip folder, using Arduino IDE.</li>
	<li>Compile the Arduino.ino file by clicking on the Checkmark button. Upload the compiled code by clicking on the Arrow button.</li>
	<li>Open the GUI.pde file, located in the GUI.zip folder, using Processing.</li>
	<li>Click on Run in the processing program to launch the graphical user interface for controlling the illumination device.</li>
	<li>In the graphical user interface window, click on Intensity for the column containing hydrogel precursor solution to be crosslinked and input the desired intensity. Click on the Time box and input desired time. For the solution provided in Table 2, this will be 15 s. 
	NOTE: End-users need to calibrate digital intensity values to irradiance using a radiometer. Examples of typical intensities are provided in Figure 2A.</li>
	<li>Align the samples with the illumination device (Figure 2B) with every other LED in a single column of the silicone molds (see Table of Materials) or 384-well plate. Click on Finish to begin illumination. Repeat this process as necessary for illumination of multiple slides or other wells of a 384-well plate. 
	NOTE: The holder is designed such that the 384-well plate sits flush with one corner of the inner chamber during illumination.
	<ol>
		<li>Following illumination, when placed in one corner, move the well plate to the next corner and repeat. To illuminate wells on the other half of the plate, lift the plate out of the holder and rotate 180&#176;.</li>
	</ol>
	</li>
	<li>Generate hydrogels with varying mechanics for mechanical characterization following the steps below.
	<ol>
		<li>Clean the glass slides and silicone molds using tape to remove debris. Adhere the silicone molds to the glass slide, press down to ensure a good seal, and displace any air bubbles.</li>
		<li>Pipette 80 &#181;L of hydrogel precursor solution, as prepared in step 1.4, into each silicone mold on the glass slide.</li>
		<li>Place the glass slide onto the illumination device aligned with every other LED in a single column. Expose the hydrogel precursors to UV light for 15 s, as described in step 2, to photocrosslink.</li>
		<li>Once illumination has stopped, retrieve the slides, and loosen the gels from the molds by tracing the inner circumference of the mold with a fine tip (10 &#181;L pipette tip, 30 G needle, etc.). Remove silicone molds with tweezers/forceps.</li>
		<li>Move crosslinked hydrogels into individual wells of a 12-well plate by wetting a spatula and gently pushing them off the glass slide. Fill each well with 2 mL of DPBS (see Table of Materials) prior to adding the hydrogel. Swell the gels in DPBS solution for at least 12 h (typically overnight) at room temperature (for the next day&#39;s mechanical characterization).</li>
	</ol>
	</li>
</ol>
3. Atomic Force Microscopy (AFM) measurements
<ol>
	<li>Turn on the atomic force microscope (AFM) according to the manufacturer&#39;s instructions (see Table of Materials). This protocol provides brief instructions for using the instrument and the related software.</li>
	<li>Install the AFM probe (see Table of Materials). 
	NOTE: For the present study, a triangular silicon nitride cantilever with a nominal spring constant of 0.01 N/m was modified with a spherical 2.5 &#181;m silicon dioxide particle.</li>
	<li>Following installation, align the laser to the apex of the triangular probe, and then adjust mirror and laser deflection to maximize signal sum (typically between 1.5-2.2 Volts).</li>
	<li>Immerse the probe in DPBS and wait for up to 15 min to obtain thermal equilibrium. Click on the Calibration button and select Contact-Dependent calibration. Click on the Collect Thermal Tuning button, and following data collection, select the peak around 3 kHz for calibration. 
	NOTE: Slight adjustment of the mirror and laser deflectors may be necessary following immersion into a liquid due to refractive index changes.</li>
	<li>Approach the surface of a Petri dish (plastic) by setting the Approach Parameters to Constant Velocity, a target height of 7.5 &#181;m, and an approach speed of 15 &#181;m/s. Enable Baseline Measurement Per Run for Approach so that the approach runs continuously and does not stop early due to drift in the deflector.</li>
	<li>Upon approach, set acquisition parameters for force mapping to 4 nN turnarounds, 2 &#181;m indentation distance, 1 &#181;m/s velocity, and 0 s contact time. Press the Start button to begin collecting a force curve on the plastic surface (e.g., a well plate).</li>
	<li>Return to the calibration window and select the portion of the force curve corresponding to contact and indentation of the plastic. Accept the calculated sensitivity and stiffness values for the probe to complete calibration.</li>
	<li>Following calibration, raise the AFM probe and place the hydrogel sample for interrogation. Approach hydrogel following the settings provided in step 5. 
	NOTE: During the approach procedure toward the hydrogel surface, the unit may mistakenly trigger the approached state. To verify the actual approach, obtain a force curve as in step 4.6. Repeat the approach procedure if the resulting curve does not show contact and resulting indentation.</li>
	<li>When the surface approach is successful, switch to the Force Mapping mode and set acquisition parameters to a map of 8 x 8 size with 40 &#181;m length per axis. Obtain force maps in various regions to assess the uniformity of stiffness measurements.
	<ol>
		<li>Interpret force curves using the software program JPK SPM Data Processing through a Hertz/Sneddon model fit (Equations 1 and 2, see Table 3 for the definition of all the variables) with the spherical geometry selected32,33,34. 
		<img alt="Equation 1" src="/files/ftp_upload/63791/63791eq01.jpg" style="margin: auto;" />&#160; &#160;Equation 132 
		<img alt="Equation 2" src="/files/ftp_upload/63791/63791eq02.jpg" style="margin: auto;" />&#160; &#160;Equation 232</li>
	</ol>
	</li>
</ol>
4. Setting up and drug treatment of 3D, matrix-embedded cultures
<ol>
	<li>Prepare desired cells as a single cell solution. 
	NOTE: Different cell types may require different passaging methods. A typical protocol for passaging a suspension culture of GBM spheroids from a T-75 flask is reported in reference31.</li>
	<li>Collect GBM spheroids (roughly 150 &#181;m in diameter) from a T-75 flask suspension culture into a 15 mL conical tube. Rinse the culture flask with 5 mL of DPBS to remove any residual cells and media and add this volume to the conical tube.</li>
	<li>Centrifuge the conical tube containing cells at 200 x g for 5 min at room temperature. Following centrifugation, remove the supernatant with a 5 mL serological pipette, taking care not to disturb the cell pellet, and resuspend in 5 mL of DPBS.</li>
	<li>Centrifuge at 200 x g for 5 min at room temperature to wash cells. Aspirate the supernatant with a 5 mL serological pipette, taking care not to disturb the cell pellet, and then resuspend cells in 2 mL of cell dissociation reagent (see Table of Materials).</li>
	<li>Incubate at room temperature for 10-15 min. Add 3 mL of complete medium (see Table of Materials) and gently pipette 3-5 times to break down the spheroids to a single cell suspension31.</li>
	<li>Centrifuge the single-cell suspension at 400 x g (single-cell suspensions may be spun faster for pellet formation) for 5 min to pellet cells at room temperature. Aspirate the supernatant with a 5 mL serological pipette, taking care not to disturb the cell pellet. Resuspend cells in 1 mL of complete medium. 
	NOTE: If the cells remain in clumps, rather than as single cells in suspension, following passaging, cells can be passed through a 40 &#181;m cell strainer to achieve a single cell suspension.</li>
	<li>Remove a portion of the cells for counting using a hemocytometer. Dilute this portion two-fold with trypan blue, which permeates cells with compromised viability. Count only the live, colorless cells. Typically, a T-75 seeded at 800,000 cells per flask yields 2-3 million cells after a week in culture.</li>
	<li>Determine the number of cells necessary for encapsulation. Transfer a volume of media containing the total number of cells needed into a sterile 1.7 mL microcentrifuge tube. Spin down at 400 x g for 5 min at room temperature. 
	NOTE: For example, a minimum of 2.5 million cells resuspended in 1 mL of gel volume is needed to encapsulate cells at 2.5 million cells/mL. A gel volume of 1 mL allows users to dispense 100 gel drops, where each gel drop is of 10 &#181;L volume. Preparing an extra ~20% volume of cells suspended in hydrogel solution is recommended to account for loss during pipette transfer. Thus, one would prepare 3 million cells and 1.2 mL of hydrogel precursor solution in this example. A minimum density of 500 thousand cells/mL is recommended.</li>
	<li>Aspirate the supernatant with a micropipette, taking care not to disturb the cell pellet. Resuspend the cell pellet in the hydrogel precursor solution, as prepared in step 1.4, mixing well by pipetting up and down with a 1,000 &#181;L micropipette 4-5 times.</li>
	<li>Load the cells into a repeat pipettor (see Table of Materials) set to dispense 10 &#181;L. To avoid bubbles and uneven dispensing, prime the repeat pipettor by dispensing an additional 1-2 times into a waste container.</li>
	<li>In each well of a 384-well plate, dispense 10 &#181;L of cells suspended in hydrogel solution from the repeat pipettor. Using the LED array, illuminate each well containing cells (step 2) for 15 s with intensities (example results in Figure 2A utilized intensities of 1.14, 1.55, 2.15, 2.74 mW/cm2) to achieve the desired mechanical properties. 
	NOTE: It is suggested to start with five replicates per experimental condition and scale up or down depending on the desired throughput and variance of the endpoint assay.</li>
	<li>Add 40 &#181;L of complete media to each well containing the cells. Add 50 &#181;L of DPBS to non-experimental, dry wells surrounding the gels to minimize losses due to evaporation.</li>
	<li>For GBM cells, add 40 &#181;L of the media-containing drug (e.g., TMZ, see Table of Materials) to achieve the final desired concentration (10 &#181;M-100 &#181;M in dimethylsulfoxide (DMSO) or vehicle (DMSO), accordingly, starting 3 days after encapsulation.</li>
</ol>
5. CCK8 proliferation assay
<ol>
	<li>Add 10 &#181;L of CCK8 reagent (see Table of Materials) to each well containing the cells. 
	NOTE: If performing this assay for the first time, include negative control wells such as media only or cell-free hydrogel in media.</li>
	<li>Incubate for 1-4 h according to the manufacturer&#39;s instructions. 
	NOTE: This time may vary as a function of cell type and density, and thus incubation times need to be tested for each application so that absorbance values fall within a linear range, a requirement for applying Beer&#39;s Law35.</li>
	<li>Read absorbances at 450 nm for all wells following incubation.</li>
	<li>Calculate the average absorbance at 450 nm obtained in step 3 for the vehicle condition for each group. Divide each drug-treated well by the average of the vehicle control per group.</li>
	<li>Calculate confidence intervals by generating bootstrap distributions (N = 10,000) through the percentile method36. 
	NOTE: Generally, one may utilize 95% confidence intervals and interpret conditions whose confidence intervals do not cross over 1 to be significant and warrant further investigation. Setting confidence intervals to 95% is congruent with setting a significance cutoff of p = 0.05. For the data shown in the results, there is utility in distinguishing conditions that either promote or inhibit matrix-mediated drug resistance, requiring a two-side analysis.</li>
</ol>

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K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Integrating+the+glioblastoma+microenvironment+into+engineered+experimental+models.">Integrating the glioblastoma microenvironment into engineered experimental models.</a> Future Science OA. 3 (3), (2017).</li><li>Trombetta-Lima, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Extracellular+matrix+proteome+remodeling+in+human+glioblastoma+and+medulloblastoma.">Extracellular matrix proteome remodeling in human glioblastoma and medulloblastoma.</a> Journal of Proteome Research. 20 (10), 4693-4707 (2021).</li><li>Schregel, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterization+of+glioblastoma+in+an+orthotopic+mouse+model+with+magnetic+resonance+elastography.">Characterization of glioblastoma in an orthotopic mouse model with magnetic resonance elastography.</a> NMR in Biomedicine. 31 (10), 3840 (2018).</li><li>Xiao, W., Ehsanipour, A., Sohrabi, A., Seidlits, S. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hyaluronic-acid+based+hydrogels+for+3-dimensional+culture+of+patient-derived+glioblastoma+cells.">Hyaluronic-acid based hydrogels for 3-dimensional culture of patient-derived glioblastoma cells.</a> Journal of Visualized Experiments: JoVE. (138), e58176 (2018).</li><li>Guz, N., Dokukin, M., Kalaparthi, V., Sokolov, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=If+cell+mechanics+can+be+described+by+elastic+modulus:+Study+of+different+models+and+probes+used+in+indentation+experiments.">If cell mechanics can be described by elastic modulus: Study of different models and probes used in indentation experiments.</a> Biophysical Journal. 107 (3), 564-575 (2014).</li><li>Sneddon, I. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+relation+between+load+and+penetration+in+the+axisymmetric+boussinesq+problem+for+a+punch+of+arbitrary+profile.">The relation between load and penetration in the axisymmetric boussinesq problem for a punch of arbitrary profile.</a> International Journal of Engineering Science. 3 (1), 47-57 (1965).</li><li>Soofi, S. S., Last, J. A., Liliensiek, S. J., Nealey, P. F., Murphy, C. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+elastic+modulus+of+MatrigelTM+as+determined+by+atomic+force+microscopy.">The elastic modulus of MatrigelTM as determined by atomic force microscopy.</a> Journal of Structural Biology. 167 (3), 216-219 (2009).</li><li>Mayerh&#246;fer, T. G., Popp, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Beer's+law+-+Why+absorbance+depends+(almost)+linearly+on+concentration.">Beer's law - Why absorbance depends (almost) linearly on concentration.</a> Chemphyschem: A European Journal of Chemical Physics and Physical Chemistry. 20 (4), 511-515 (2019).</li><li>Puth, M. T., Neuh&#228;user, M., Ruxton, G. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=On+the+variety+of+methods+for+calculating+confidence+intervals+by+bootstrapping.">On the variety of methods for calculating confidence intervals by bootstrapping.</a> Journal of Animal Ecology. 84 (4), 892-897 (2015).</li><li>Lavrentieva, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gradient+hydrogels.">Gradient hydrogels.</a> Advances in Biochemical Engineering/Biotechnology. 178, 227-251 (2020).</li><li>Zhu, D., Trinh, P., Li, J., Grant, G. A., Yang, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gradient+hydrogels+for+screening+stiffness+effects+on+patient-derived+glioblastoma+xenograft+cellfates+in+3D.">Gradient hydrogels for screening stiffness effects on patient-derived glioblastoma xenograft cellfates in 3D.</a> Journal of Biomedical Materials Research. Part A. 109 (6), 1027-1035 (2021).</li><li>da Hora, C. C., Schweiger, M. W., Wurdinger, T., Tannous, B. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Patient-derived+glioma+models:+From+patients+to+dish+to+animals.">Patient-derived glioma models: From patients to dish to animals.</a> Cells. 8 (10), 1177 (2019).</li><li>Li, W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterization+and+transplantation+of+enteric+neural+crest+cells+from+human+induced+pluripotent+stem+cells.">Characterization and transplantation of enteric neural crest cells from human induced pluripotent stem cells.</a> Molecular Psychiatry. 23 (3), 499-508 (2018).</li><li>Scaringi, C., Minniti, G., Caporello, P., Enrici, R. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Integrin+inhibitor+cilengitide+for+the+treatment+of+glioblastoma:+A+brief+overview+of+current+clinical+results.">Integrin inhibitor cilengitide for the treatment of glioblastoma: A brief overview of current clinical results.</a> Anticancer Research. 32 (10), 4213-4224 (2012).</li></ol>

The authors have nothing to disclose.

The current work presents methods to generate 3D, miniaturized cultures within HA-based while simultaneously altering matrix stiffness and peptides available for integrin engagement. This technique enables the systematic study of how matrix parameters affect cellular phenotypes (e.g., the viability of cancer cells exposed to chemotherapy) with increased throughput. Previous approaches, including that presented herein, have tuned hydrogel stiffness by varying the percent total polymer in the final formulation, where stiff...

The expected cost of developing a new drug has steadily risen over the past decade, with over $1 billion in current estimates1. Part of this expense is the high failure rate of drugs entering clinical trials. Approximately 12% of drug candidates ultimately earn approval from the United States (US) Food &#38; Drug Administration (FDA) in 2019. Many drugs fail in Phase I due to unanticipated toxicity2, while others that pass safety trials may fail due to a lack of efficacy3. This attrition due to non-efficacy can partly be explained by the fact that cancer models used during drug development are notoriously non-predictive of clinical efficacy4.
Functional disparities between in vitro and in vivo models may be attributed to removing cancer cells from their native microenvironment, including non-tumor cells and the physical ECM5,6. Commonly, research groups use commercially available culture matrices, such as Matrigel (a proteinaceous basement membrane matrix derived from mouse sarcomas) to provide cultured tumor cells with a 3D matrix microenvironment. Compared to 2D culture, 3D culture in membrane matrix has improved the clinical relevance of in vitro results7,8. However, culture biomaterials from decellularized tissues, including the membrane matrix, typically exhibit batch-to-batch variability that may compromise reproducibility9. Furthermore, matrices derived from tumors with different tissue origins from those studied may not provide the appropriate physiological cues10. Finally, cancers with high degrees of intratumoral heterogeneity have microenvironmental features that vary on a submicron-size scale and which the membrane matrix cannot be tuned to recapitulate11.
Glioblastoma (GBM), a uniformly lethal brain tumor with a median survival time of approximately 15 months, is a cancer for which treatment development has been particularly difficult12,13. The current standard of care for GBM consists of primary tumor resection, followed by radiotherapy, and then chemotherapy using temozolomide (TMZ)14. Yet, more than half of clinical GBM tumors exhibit treatment resistance through various mechanisms15,16,17. Predicting the efficacy of a treatment regimen for an individual patient is extremely difficult. Standard preclinical models used to predict individual outcomes consist of patient-derived tumor cells xenografted orthotopically into immunocompromised mice. While patient-derived xenografts can recapitulate many aspects of clinical GBM tumors and are valuable for preclinical models18, they are inherently expensive, low throughput, time-consuming, and involve ethical concerns19. Cultures of patient-derived cells, on 2D plastic surfaces or as spheroids, mostly avoid these issues. While patient-derived cells preserve&#160;genetic aberrations, their cultures in 2D or as suspended spheroids have been largely poor representations of patient-derived xenografts in rodents and original patient tumors20. Previously, we, and others, have shown that GBM cells cultured in a 3D ECM that mimics the mechanical and biochemical properties of brain tissue can preserve drug resistance phenotypes10,21,22,23.
Interactions between hyaluronic acid (HA), a polysaccharide abundant in the brain ECM and overexpressed in GBM tumors, and its CD44 receptor modulate the acquisition of drug resistance in vitro21,24,25,26,27.&#160;For example, the inclusion of HA within soft, 3D cultures increased the ability of patient-derived GBM cells to acquire therapeutic resistance. This mechano-responsivity was dependent on HA binding to CD44 receptors on GBM cells21. Additionally, integrin binding to RGD-bearing peptides, incorporated into 3D culture matrices, amplified CD44-mediated chemoresistance in a stiffness-dependent manner21. Beyond HA, the expression of several ECM proteins, many containing RGD regions, vary between normal brain and GBM tumors28. For example, one study reported that 28 distinct ECM proteins were upregulated in GBM tumors29. Within this complex tumor matrix microenvironment, cancer cells integrate mechanical and biochemical cues to yield a particular resistance phenotype, which depends on relatively small differences (e.g., less than an order of magnitude) in Young&#39;s modulus or density of integrin-binding peptides28,29,30.
The present protocol characterizes how tumor cells interpret unique combinations of matrix cues and identify complex, patient-specific matrix microenvironments that promote treatment resistance (Figure 1A). A photochemical method for generating miniaturized, precisely tuned matrices for 3D culture provides a large, orthogonal variable space. A custom-built array of LEDs, run by a microcontroller, was incorporated to photocrosslink hydrogels within a 384-well plate format to increase automation and reproducibility. Exposure intensity was varied across well to alter micro-mechanical properties of resulting hydrogels, as assessed using atomic force microscopy (AFM). While this manuscript does not focus on constructing the illumination array itself, a circuit diagram (Figure 1B) and parts list (Table of Materials) are provided as aids for device reproduction.
This report demonstrates the rapid generation of an array of GBM cells cultured in unique, 3D microenvironments in which Young&#39;s modulus (four levels across a single order of magnitude) and integrin-binding peptide content (derived from four different ECM proteins) were varied orthogonally. The approach was then used to investigate the relative contributions of hydrogel mechanics and ECM-specific integrin engagement on the viability and proliferation of patient-derived GBM cells as they acquire resistance to temozolomide (TMZ) chemotherapy.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>1.1 kOhm resistors, 6 W</td>
			<td>Digikey</td>
			<td>35601k1ft</td>
			<td></td>
		</tr>
		<tr>
			<td>1.7 mL microcentrifuge tube</td>
			<td>Genesse Scientific</td>
			<td>21-108</td>
			<td></td>
		</tr>
		<tr>
			<td>15 mL conical tube</td>
			<td>Fisher Scientific</td>
			<td>14-959-70C</td>
			<td></td>
		</tr>
		<tr>
			<td>365 nm LED</td>
			<td>Digikey</td>
			<td>ltpl-c034uvh365</td>
			<td></td>
		</tr>
		<tr>
			<td>384 well plate</td>
			<td>Bio Greiner One</td>
			<td>781090</td>
			<td></td>
		</tr>
		<tr>
			<td>40 &#181;m cell strainer</td>
			<td>MTC bio</td>
			<td>C4040</td>
			<td></td>
		</tr>
		<tr>
			<td>4-Armed thiol terminated polyethlene glycol (20 kDa)</td>
			<td>Laysan Bio</td>
			<td>4arm-PEG-SH-20K-1g</td>
			<td></td>
		</tr>
		<tr>
			<td>6 NPN BJTs</td>
			<td>Digikey</td>
			<td>2n5550ta</td>
			<td></td>
		</tr>
		<tr>
			<td>80 Ohm resistors, 0.125 W</td>
			<td>Digikey</td>
			<td>erjj-6enf80r6v</td>
			<td></td>
		</tr>
		<tr>
			<td>8-Armed norbornene terminated polyethylene glycol (20 kDa)</td>
			<td>Jenkem Technology</td>
			<td>A7025-1</td>
			<td></td>
		</tr>
		<tr>
			<td>Accutase</td>
			<td>Innovative Cell Technologies</td>
			<td>AT104500</td>
			<td>&#160;cell dissociation&#160; reagent</td>
		</tr>
		<tr>
			<td>AFM Probes</td>
			<td>Novascan</td>
			<td></td>
			<td>0.01 N/m Nominal spring constant, 2.5 &#181;m SiO2 particle</td>
		</tr>
		<tr>
			<td>Arduino IDE</td>
			<td>Arduino</td>
			<td>1.8.19</td>
			<td></td>
		</tr>
		<tr>
			<td>Arduino Nano</td>
			<td>Makerfire</td>
			<td>Mini Nano V3.0 ATmega328P Microcontroller Board</td>
			<td></td>
		</tr>
		<tr>
			<td>bFGF</td>
			<td>Peprotech</td>
			<td>100-18B</td>
			<td>20 ng/mL</td>
		</tr>
		<tr>
			<td>CCK8</td>
			<td>Abcam</td>
			<td>ab228554</td>
			<td></td>
		</tr>
		<tr>
			<td>Centrifuge</td>
			<td>Thermoscientific</td>
			<td>sorvall legend xtr</td>
			<td></td>
		</tr>
		<tr>
			<td>CP100ST</td>
			<td>Gilson</td>
			<td>F148415</td>
			<td>Pipette tips for positive displacement pipette</td>
		</tr>
		<tr>
			<td>Cubis Semi-Micro Balance</td>
			<td>Sartorius</td>
			<td>MSA225S100DI</td>
			<td></td>
		</tr>
		<tr>
			<td>DMEM - F12 (50-50)</td>
			<td>Life Technologies</td>
			<td>11330057</td>
			<td>1x</td>
		</tr>
		<tr>
			<td>DMSO</td>
			<td>Fisher Scientific</td>
			<td>BP231-100</td>
			<td></td>
		</tr>
		<tr>
			<td>DPBS Ca (-) Mg (-)</td>
			<td>Genesse Scientific</td>
			<td>25-508</td>
			<td></td>
		</tr>
		<tr>
			<td>EGF</td>
			<td>Peprotech</td>
			<td>AF100-15</td>
			<td>50 ng/mL</td>
		</tr>
		<tr>
			<td>Ethanol, Anhydrous</td>
			<td>Fisher Scientific</td>
			<td>A405P</td>
			<td>Add DI water to dilute to 70%</td>
		</tr>
		<tr>
			<td>Fisherbrand Class B Amber Glass threaded vials</td>
			<td>Fisher Scientific</td>
			<td>03-339-23C</td>
			<td></td>
		</tr>
		<tr>
			<td>Fisherbrand Weighing Paper</td>
			<td>Fisher Scientific</td>
			<td>09-898-12B</td>
			<td></td>
		</tr>
		<tr>
			<td>G21 Supplement</td>
			<td>Gemini Bio</td>
			<td>400-160</td>
			<td>50x</td>
		</tr>
		<tr>
			<td>Hanks Balanced Salt Solution</td>
			<td>Thermo Fisher Scientific</td>
			<td>14175095</td>
			<td></td>
		</tr>
		<tr>
			<td>HCl, ACS, 12M</td>
			<td>Sigma Aldrich</td>
			<td>S25838A</td>
			<td>Add DI water to dilute to 1 M</td>
		</tr>
		<tr>
			<td>Heparin sodium salt from porcine intestinal mucosa</td>
			<td>Sigma Aldrich</td>
			<td>H3149-100Ku</td>
			<td>25 &#181;g/mL</td>
		</tr>
		<tr>
			<td>HEPES</td>
			<td>Sigma Aldrich</td>
			<td>H7006-100G</td>
			<td></td>
		</tr>
		<tr>
			<td>Hot Air Gun</td>
			<td>Wagner</td>
			<td>HT1000</td>
			<td></td>
		</tr>
		<tr>
			<td>Integrin-binding sialoprotein (IBSP) peptide</td>
			<td>Genscript</td>
			<td>Custom Order</td>
			<td>GCGYGGGGNGEPRGDTYRAY</td>
		</tr>
		<tr>
			<td>Lithium phenyl-2,4,6 trimethylbenzoylphosphinate (LAP) , &#62;95%</td>
			<td>Sigma Aldrich</td>
			<td>900889-1G</td>
			<td></td>
		</tr>
		<tr>
			<td>Magnetic stir plate</td>
			<td>Thermo Scientific</td>
			<td>SP194715</td>
			<td></td>
		</tr>
		<tr>
			<td>Microcentrifuge</td>
			<td>Thermo Scientific</td>
			<td>Sorvall legend micro 21R</td>
			<td></td>
		</tr>
		<tr>
			<td>Microman E single Channel Pipettor</td>
			<td>Gilson</td>
			<td>FD10004</td>
			<td>Positive displacement pipette</td>
		</tr>
		<tr>
			<td>Micropipette Tips</td>
			<td>Various Manufacturs</td>
			<td></td>
			<td>Various sizes</td>
		</tr>
		<tr>
			<td>mLine micropipette</td>
			<td>Sartorious</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>N-acetyl Cysteine</td>
			<td>Sigma Aldrich</td>
			<td>A7250-10G</td>
			<td></td>
		</tr>
		<tr>
			<td>Nanowizard 4</td>
			<td>Bruker</td>
			<td></td>
			<td>AFM microscope</td>
		</tr>
		<tr>
			<td>NaOH</td>
			<td>Fisher Scientific</td>
			<td>ss255-1</td>
			<td>Add DI water to dilute to 1 M</td>
		</tr>
		<tr>
			<td>Normoicin</td>
			<td>Invivogen</td>
			<td>ant-nr-1</td>
			<td>500x</td>
		</tr>
		<tr>
			<td>Osteopontin Peptide</td>
			<td>Genscript</td>
			<td>Custom Order</td>
			<td>GCGYGTVDVPDGRGDSLAYG</td>
		</tr>
		<tr>
			<td>Pipet Aid</td>
			<td>Drummond</td>
			<td>4000102</td>
			<td></td>
		</tr>
		<tr>
			<td>Plain Microscope Slides</td>
			<td>Globe Scientific</td>
			<td>1301</td>
			<td></td>
		</tr>
		<tr>
			<td>Press-To-Seal silicone Isolator, 12-4.5mm diam x 2mm deep</td>
			<td>Grace Bio Labs</td>
			<td>664201-A</td>
			<td>Cut so that 8 individual molds are made from a single sheet</td>
		</tr>
		<tr>
			<td>Processing</td>
			<td>Processing</td>
			<td>3.5.4</td>
			<td></td>
		</tr>
		<tr>
			<td>Repeater M4</td>
			<td>Eppendorf</td>
			<td>4982000322</td>
			<td></td>
		</tr>
		<tr>
			<td>Repeater Pipette Tips</td>
			<td>Sartorious</td>
			<td>30089430</td>
			<td>1 mL sizes</td>
		</tr>
		<tr>
			<td>RGD Peptide</td>
			<td>Genscript</td>
			<td></td>
			<td>GCGYGRGDSPG</td>
		</tr>
		<tr>
			<td>Scoth Tape</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Serological Pipettes</td>
			<td>Genesse Scientific</td>
			<td>12-102,12-104</td>
			<td>5,10 mL Pipettes</td>
		</tr>
		<tr>
			<td>Solder Paste</td>
			<td>Digikey</td>
			<td>315-NC191LT15T5-ND</td>
			<td></td>
		</tr>
		<tr>
			<td>Solder Wire</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Straight dissecting forceps</td>
			<td>VWR Scientific</td>
			<td>82027-408</td>
			<td></td>
		</tr>
		<tr>
			<td>Synergy H1 Plate Reader</td>
			<td>Biotek</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>T-75 Cell Culture Treated Flask</td>
			<td>Genesee Scientific</td>
			<td>25-209</td>
			<td></td>
		</tr>
		<tr>
			<td>Temozolomide</td>
			<td>Sigma Aldrich</td>
			<td>T2577</td>
			<td>Typically used from 10 &#181;M to 100 &#181;M</td>
		</tr>
		<tr>
			<td>Tenascin-C Peptide</td>
			<td>Genscript</td>
			<td></td>
			<td>GCGYGRSTDLPGLKAATHYTITIR 
			GV</td>
		</tr>
		<tr>
			<td>Thiolated Hyaluronic Acid (700 kDa), 6-8% modified</td>
			<td>Lifecore Biomedical</td>
			<td>HA700K5</td>
			<td></td>
		</tr>
		<tr>
			<td>VWR Spinbar, Flea Micro</td>
			<td>VWR</td>
			<td>58948-375</td>
			<td></td>
		</tr>
	</tbody>
</table>

hydrogel arrays enable increased throughput for screening effects of matrix components and therapeutics in 3d tumor models

Cell-matrix interactions mediate complex physiological processes through biochemical, mechanical, and geometrical cues, influencing pathological changes and therapeutic responses. Accounting for matrix effects earlier in the drug development pipeline is expected to increase the likelihood of clinical success of novel therapeutics. Biomaterial-based strategies recapitulating specific tissue microenvironments in 3D cell culture exist but integrating these with the 2D culture methods primarily used for drug screening has been challenging. Thus, the protocol presented here details the development of methods for 3D culture within miniaturized biomaterial matrices in a multi-well plate format to facilitate integration with existing drug screening pipelines and conventional assays for cell viability. Since the matrix features critical for preserving clinically relevant phenotypes in cultured cells are expected to be highly tissue- and disease-specific, combinatorial screening of matrix parameters will be necessary to identify appropriate conditions for specific applications. The methods described here use a miniaturized culture format to assess cancer cell responses to orthogonal variation of matrix mechanics and ligand presentation. Specifically, this study demonstrates the use of this platform to investigate the effects of matrix parameters on the responses of patient-derived glioblastoma (GBM) cells to chemotherapy.

AFM measurements confirmed precise control of hydrogel mechanics as a function of UV irradiance (mW/cm2) during photo-crosslinking using a custom-built, Arduino-controlled LED array (Figure 2A). The hydrogel formulation used in this protocol can be found in Table 2. The spacing of the LEDs on the provided template matches the spacing for every other well of a 384-well plate, allowing for the formation of gels inside the plate (Figure 2B</stron...

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Hydrogel Arrays Enable Increased Throughput for Screening Effects of Matrix Components and Therapeutics in 3D Tumor Models

The present protocol describes an experimental platform to assess the effects of mechanical and biochemical cues on chemotherapeutic responses of patient-derived glioblastoma cells in 3D matrix-mimetic cultures using a custom-made UV illumination device facilitating high-throughput photocrosslinking of hydrogels with tunable mechanical features.

Cell-matrix interactions mediate complex physiological processes through biochemical, mechanical, and geometrical cues, influencing pathological changes ...

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Research

JoVE Journal

Bioengineering

2.4K Views.  University of California Los Angeles. The present protocol describes an experimental platform to assess the effects of mechanical and biochemical cues on chemotherapeutic responses of patient-derived glioblastoma cells in 3D matrix-mimetic cultures using a custom-made UV illumination device facilitating high-throughput photocrosslinking of hydrogels with tunable mechanical features.

Video: Hydrogel Arrays Enable Increased Throughput for Screening Effects of Matrix Components and Therapeutics in 3D Tumor Models

Longitudinal Measurement of Extracellular Matrix Rigidity in 3D Tumor Models Using Particle-tracking Microrheology

The mechanical microenvironment has been shown to act as a crucial regulator of tumor growth behavior and signaling, which is itself remodeled and modified as part of a set of complex, two-way mechanosensitive interactions. While the development of biologically-relevant 3D tumor models have facilitated mechanistic studies on the impact of matrix rheology on tumor growth, the inverse problem of mapping changes in the mechanical environment induced by tumors remains challenging. Here, we describe the implementation of particle-tracking microrheology (PTM) in conjunction with 3D models of pancreatic cancer as part of a robust and viable approach for longitudinally monitoring physical changes in the tumor microenvironment, in situ. The methodology described here integrates a system of preparing in vitro 3D models embedded in a model extracellular matrix (ECM) scaffold of Type I collagen with fluorescently labeled probes uniformly distributed for position- and time-dependent microrheology measurements throughout the specimen. In vitro tumors are plated and probed in parallel conditions using multiwell imaging plates. Drawing on established methods, videos of tracer probe movements are transformed via the Generalized Stokes Einstein Relation (GSER) to report the complex frequency-dependent viscoelastic shear modulus, G*(&#969;). Because this approach is imaging-based, mechanical characterization is also mapped onto large transmitted-light spatial fields to simultaneously report qualitative changes in 3D tumor size and phenotype. Representative results showing contrasting mechanical response in sub-regions associated with localized invasion-induced matrix degradation as well as system calibration, validation data are presented. Undesirable outcomes from common experimental errors and troubleshooting of these issues are also presented. The 96-well 3D culture plating format implemented in this protocol is conducive to correlation of microrheology measurements with therapeutic screening assays or molecular imaging to gain new insights into impact of treatments or biochemical stimuli on the mechanical microenvironment.

Particle-tracking microrheology can be used to non-destructively quantify and spatially map changes in extracellular matrix mechanical properties in 3D tumor models.

The mechanical microenvironment has been shown to act as a crucial regulator of tumor growth behavior and signaling, which is itself remodeled and ...

Porous Silicon Microparticles for Delivery of siRNA Therapeutics

Small interfering RNA (siRNA) can be used to suppress gene expression, thereby providing a new avenue for the treatment of various diseases. However, the successful implementation of siRNA therapy requires the use of delivery platforms that can overcome the major challenges of siRNA delivery, such as enzymatic degradation, low intracellular uptake and lysosomal entrapment. Here, a protocol for the preparation and use of a biocompatible and effective siRNA delivery system is presented. This platform consists of polyethylenimine (PEI) and arginine (Arg)-grafted porous silicon microparticles, which can be loaded with siRNA by performing a simple mixing step. The silicon particles are gradually degraded over time, thereby triggering the formation of Arg-PEI/siRNA nanoparticles. This delivery vehicle provides a means for protecting and internalizing siRNA, without causing cytotoxicity. The major steps of polycation functionalization, particle characterization, and siRNA loading are outlined in detail. In addition, the procedures for determining particle uptake, cytotoxicity, and transfection efficacy are also described.

Delivery remains the main challenge for the therapeutic implementation of small interfering RNA (siRNA). This protocol involves the use of a multifunctional and biocompatible siRNA delivery platform, consisting of arginine and polyethylenimine grafted porous silicon microparticles.

Small interfering RNA (siRNA) can be used to suppress gene expression, thereby providing a new avenue for the treatment of various diseases. However, the ...

3D Microtissues for Injectable Regenerative Therapy and High-throughput Drug Screening

To upgrade traditional 2D cell culture to 3D cell culture, we have integrated microfabrication with cryogelation technology to produce macroporous microscale cryogels (microcryogels), which can be loaded with a variety of cell types to form 3D microtissues. Herein, we present the protocol to fabricate versatile 3D microtissues and their applications in regenerative therapy and drug screening. Size and shape-controllable microcryogels can be fabricated on an array chip, which can be harvested off-chip as individual cell-loaded carriers for injectable regenerative therapy or be further assembled on-chip into 3D microtissue arrays for high-throughput drug screening. Due to the high elastic nature of these microscale cryogels, the 3D microtissues exhibit great injectability for minimally invasive cell therapy by protecting cells from mechanical shear force during injection. This ensures enhanced cell survival and therapeutic effect in the mouse limb ischemia model. Meanwhile, assembly of 3D microtissue arrays in a standard 384-multi-well format facilitates the use of common laboratory facilities and equipment, enabling high-throughput drug screening on this versatile 3D cell culture platform.

This protocol describes the fabrication of elastic 3D macroporous microcryogels by integrating microfabrication with cryogelation technology. Upon loading with cells, 3D microtissues are generated, which can be readily injected in vivo to facilitate regenerative therapy or assembled into arrays for in vitro high-throughput drug screening.

To upgrade traditional 2D cell culture to 3D cell culture, we have integrated microfabrication with cryogelation technology to produce macroporous ...

Improved 3D Hydrogel Cultures of Primary Glial Cells for In Vitro Modelling of Neuroinflammation

In the central nervous system, numerous acute injuries and neurodegenerative disorders, as well as implanted devices or biomaterials engineered to enhance function result in the same outcome: excess inflammation leads to gliosis, cytotoxicity, and/or formation of a glial scar that collectively exacerbate injury or prevent healthy recovery. With the intent of creating a system to model glial scar formation and study inflammatory processes, we have generated a 3D cell scaffold capable of housing primary cultured glial cells: microglia that regulate the foreign body response and initiate the inflammatory event, astrocytes that respond to form a fibrous scar, and oligodendrocytes that are typically vulnerable to inflammatory injury. The present work provides a detailed step-by-step method for the fabrication, culture, and microscopic characterization of a hyaluronic acid-based 3D hydrogel scaffold with encapsulated rat brain-derived glial cells. Further, protocols for characterization of cell encapsulation and the hydrogel scaffold by confocal immunofluorescence and scanning electron microscopy are demonstrated, as well as the capacity to modify the scaffold with bioactive substrates, with incorporation of a commercial basal lamina mixture to improved cell integration.

Improved 3D Hydrogel Cultures of Primary Glial Cells for In Vitro Modelling of Neuroinflammation

Herein, we present a protocol for the 3D culture of rat brain-derived glia cells, including astrocytes, microglia, and oligodendrocytes. We demonstrate primary cell culture, methacrylated hyaluronic acid (HAMA) hydrogel synthesis, HAMAphoto-polymerization and cell encapsulation, and sample processing for confocal and scanning electron microscopic imaging.

In the central nervous system, numerous acute injuries and neurodegenerative disorders, as well as implanted devices or biomaterials engineered to enhance ...

Fabricating a Kidney Cortex Extracellular Matrix-Derived Hydrogel

Extracellular matrix (ECM) provides important biophysical and biochemical cues to maintain tissue homeostasis. Current synthetic hydrogels offer robust mechanical support for in vitro cell culture but lack the necessary protein and ligand composition to elicit physiological behavior from cells. This manuscript describes a fabrication method for a kidney cortex ECM-derived hydrogel with proper mechanical robustness and supportive biochemical composition. The hydrogel is fabricated by mechanically homogenizing and solubilizing decellularized human kidney cortex ECM. The matrix preserves native kidney cortex ECM protein ratios while also enabling gelation to physiological mechanical stiffnesses. The hydrogel serves as a substrate upon which kidney cortex-derived cells can be maintained under physiological conditions. Furthermore, the hydrogel composition can be manipulated to model a diseased environment which enables the future study of kidney diseases.

Here we present a protocol to fabricate a kidney cortex extracellular matrix-derived hydrogel to retain the native kidney extracellular matrix (ECM) structural and biochemical composition. The fabrication process and its applications are described. Finally, a perspective on using this hydrogel to support kidney-specific cellular and tissue regeneration and bioengineering is discussed.

Extracellular matrix (ECM) provides important biophysical and biochemical cues to maintain tissue homeostasis. Current synthetic hydrogels offer robust ...

Pancreatic Tissue-Derived Extracellular Matrix Bioink for Printing 3D Cell-Laden Pancreatic Tissue Constructs

The transplantation of pancreatic islets is a promising treatment for patients who suffer from type 1 diabetes accompanied by hypoglycemia and secondary complications. However, islet transplantation still has several limitations such as the low viability of transplanted islets due to poor islet engraftment and hostile environments. In addition, the insulin-producing cells differentiated from human pluripotent stem cells have limited ability to secrete sufficient hormones that can regulate the blood glucose level; therefore, improving the maturation by culturing cells with proper microenvironmental cues is strongly required. In this article, we elucidate protocols for preparing a pancreatic tissue-derived decellularized extracellular matrix (pdECM) bioink to provide a beneficial microenvironment that can increase glucose sensitivity of pancreatic islets, followed by describing the processes for generating 3D pancreatic tissue constructs using a microextrusion-based bioprinting technique.

Decellularized extracellular matrix (dECM) can provide suitable microenvironmental cues to recapitulate the inherent functions of target tissues in an engineered construct. This article elucidates the protocols for the decellularization of pancreatic tissue, evaluation of pancreatic tissue-derived dECM bioink, and generation of 3D pancreatic tissue constructs using a bioprinting technique.

The transplantation of pancreatic islets is a promising treatment for patients who suffer from type 1 diabetes accompanied by hypoglycemia and secondary ...

A Human 3D Extracellular Matrix-Adipocyte Culture Model for Studying Matrix-Cell Metabolic Crosstalk

The extracellular matrix (ECM) plays a central role in regulating tissue homeostasis, engaging in crosstalk with cells and regulating multiple aspects of cellular function. The ECM plays a particularly important role in adipose tissue function in obesity, and alterations in adipose tissue ECM deposition and composition are associated with metabolic disease in mice and humans. Tractable in vitro models that permit dissection of the roles of the ECM and cells in contributing to global tissue phenotype are sparse. We describe a novel 3D in vitro model of human ECM-adipocyte culture that permits study of the specific roles of the ECM and adipocytes in regulating adipose tissue metabolic phenotype. Human adipose tissue is decellularized to isolate ECM, which is subsequently repopulated with preadipocytes that are then differentiated within the ECM into mature adipocytes. This method creates ECM-adipocyte constructs that are metabolically active and retain characteristics of the tissues and patients from which they are derived. We have used this system to demonstrate disease-specific ECM-adipocyte crosstalk in human adipose tissue. This culture model provides a tool for dissecting the roles of the ECM and adipocytes in contributing to global adipose tissue metabolic phenotype and permits study of the role of the ECM in regulating adipose tissue homeostasis.

We describe a 3D human extracellular matrix-adipocyte in vitro culture system that permits dissection of the roles of the matrix and adipocytes in contributing to adipose tissue metabolic phenotype.

The extracellular matrix (ECM) plays a central role in regulating tissue homeostasis, engaging in crosstalk with cells and regulating multiple aspects of ...

An Open Source Technology Platform to Manufacture Hydrogel-Based 3D Culture Models in an Automated and Standardized Fashion

Current mixing steps of viscous materials rely on repetitive and time-consuming tasks which are performed mainly manually in a low throughput mode. These issues represent drawbacks in workflows that can ultimately result in irreproducibility of research findings. Manual-based workflows are further limiting the advancement and widespread adoption of viscous materials, such as hydrogels used for biomedical applications. These challenges can be overcome by using automated workflows with standardized mixing processes to increase reproducibility. In this study, we present step-by-step instructions to use an open source protocol designer, to operate an open source workstation, and to identify reproducible mixtures. Specifically, the open source protocol designer guides the user through the experimental parameter selection and generates a ready-to-use protocol code to operate the workstation. This workstation is optimized for pipetting of viscous materials to enable automated and highly reliable handling by the integration of temperature docks for thermoresponsive materials, positive displacement pipettes for viscous materials, and an optional tip touch dock to remove excess material from the pipette tip. The validation and verification of mixtures are performed by a fast and inexpensive absorbance measurement of Orange G. This protocol presents results to obtain 80% (v/v) glycerol mixtures, a dilution series for gelatin methacryloyl (GelMA), and double network hydrogels of 5% (w/v) GelMA and 2% (w/v) alginate. A troubleshooting guide is included to support users with protocol adoption. The described workflow can be broadly applied to a number of viscous materials to generate user-defined concentrations in an automated fashion.

This protocol serves as a comprehensive tutorial for standardized and reproducible mixing of viscous materials with a novel open source automation technology. Detailed instructions are provided on the operation of a newly developed open source workstation, the usage of an open source protocol designer, and the validation and verification to identify reproducible mixtures.

Current mixing steps of viscous materials rely on repetitive and time-consuming tasks which are performed mainly manually in a low throughput mode. These ...

Photodegradable Hydrogel Interfaces for Bacteria Screening, Selection, and Isolation

Biologists have long attempted to understand the relationship between phenotype and genotype. To better understand this connection, it is crucial to develop practical technologies that couple microscopic cell screening with cell isolation at high purity for downstream genetic analysis. Here, the use of photodegradable poly(ethylene glycol) hydrogels for screening and isolation of bacteria with unique growth phenotypes from heterogeneous cell populations is described. The method relies on encapsulating or entrapping cells with the hydrogel, followed by culture, microscopic screening, then use of a high-resolution light patterning tool for spatiotemporal control of hydrogel degradation and release of selected cells into a solution for retrieval. Applying different light patterns allows for control over the morphology of the extracted cell, and patterns such as rings or crosses can be used to retrieve cells with minimal direct UV light exposure to mitigate DNA damage to the isolates. Moreover, the light patterning tool delivers an adjustable light dose to achieve various degradation and cell release rates. It allows for degradation at high resolution, enabling cell retrieval with micron-scale spatial precision. Here, the use of this material to screen and retrieve bacteria from both bulk hydrogels and microfabricated lab-on-a-chip devices is demonstrated. The method is inexpensive, simple, and can be used for common and emerging applications in microbiology, including isolation of bacterial strains with rare growth profiles from mutant libraries and isolation of bacterial consortia with emergent phenotypes for genomic characterizations.

The use of photodegradable hydrogels to isolate bacterial cells by utilizing a high-resolution light pattering tool is reported. Essential experimental procedures, results, and advantages of the process are reviewed. The method enables rapid and inexpensive isolation of targeted bacteria showing rare or unique functions from heterogeneous communities or populations.

Biologists have long attempted to understand the relationship between phenotype and genotype. To better understand this connection, it is crucial to ...

Gelatin Methacryloyl Granular Hydrogel Scaffolds: High-throughput Microgel Fabrication, Lyophilization, Chemical Assembly, and 3D Bioprinting

The emergence of granular hydrogel scaffolds (GHS), fabricated via assembling hydrogel microparticles (HMPs), has enabled microporous scaffold formation in situ. Unlike conventional bulk hydrogels, interconnected microscale pores in GHS facilitate degradation-independent cell infiltration as well as oxygen, nutrient, and cellular byproduct transfer. Methacryloyl-modified gelatin (GelMA), a (photo)chemically crosslinkable, protein-based biopolymer containing cell adhesive and biodegradable moieties, has widely been used as a cell-responsive/instructive biomaterial. Converting bulk GelMA to GHS&#160;may open a plethora of opportunities for tissue engineering and regeneration. In this article, we demonstrate the procedures of high-throughput GelMA microgel fabrication, conversion to resuspendable dry microgels (micro-aerogels), GHS formation via the chemical assembly of microgels, and granular bioink fabrication for extrusion bioprinting. We show how a sequential physicochemical treatment via cooling and photocrosslinking enables the formation of mechanically robust GHS.&#160;When light is inaccessible (e.g., during deep tissue injection), individually crosslinked GelMA HMPs may be bioorthogonally assembled via enzymatic crosslinking using transglutaminases. Finally, three-dimensional (3D) bioprinting of microporous GHS&#160;at low HMP packing density is demonstrated via the interfacial self-assembly of heterogeneously charged nanoparticles.

This article describes protocols for high-throughput gelatin methacryloyl microgel fabrication using microfluidic devices, converting microgels to resuspendable powder (micro-aerogels), the chemical assembly of microgels to form granular hydrogel scaffolds, and developing granular hydrogel bioinks with preserved microporosity for 3D bioprinting.

The emergence of granular hydrogel scaffolds (GHS), fabricated via assembling hydrogel microparticles (HMPs), has enabled microporous scaffold formation ...