This research was funded by the State of Florida&#39;s Bankhead-Coley Team Science Grant (2BT03), the National Institutes of Health/National Cancer Institute (1R21CA164322-01) and Moffitt Cancer Center&#8217;s Team Science Grant. This work has been supported in part by the Translational Research&#160;Core Facility at the H. Lee Moffitt Cancer Center &#38; Research Institute, an NCI designated Comprehensive Cancer Center (P30-CA076292). Access to primary cells was made possible through the Total Cancer Care Protocol at the Moffitt Cancer Center.

The use of human cells derived from biopsies as described below was approved by Moffitt&#8217;s Institutional Review Board and conducted under the clinical trial MCC# 14745 conducted at the H. Lee Moffitt Cancer Center and Research Institute.
1. Sorting of MM Cells from Bone Marrow Aspirates
<ol>
	<li>Collect bone marrow aspirates (20 ml) from patients in sodium heparin syringe.</li>
	<li>Isolate mononuclear cells by centrifuging diluted marrow (1:1 with sterile PBS) over a sterile aqueous medium centrifugation gradient at 400 x g for 30 min at ambient temperature.</li>
	<li>Collect the interface, which contains the mononuclear cells. Wash cells with cold PBS and count using a hemocytometer or automated cell counter, using trypan blue for determination of viability.</li>
	<li>Prepare a thin-layer cell preparation slide10 and stain with Wright-Giemsa stain to assess plasma cell percentage11.</li>
	<li>Calculate the amount of CD138 beads to be used based the number of cells and plasma cell percentage. If starting sample is less than 20% plasma cells, then re-suspend cells using 90 &#181;l of separation buffer and 10 &#181;l of CD138 beads per 5 x 106 cells. If starting sample is more than 20% plasma cells, resuspended using 80 &#181;l of separation buffer and 20 &#181;l of CD138 beads per 1 x 107 cells.</li>
	<li>Incubate cells with beads at 4 &#176;C for 15 min.</li>
	<li>Pass cells through a 35 &#181;m strainer added to pre-wetted separation (LS) columns placed in the magnetic field separator (see list of materials).</li>
	<li>Remove column from magnet. Collect CD138-selected cells by washing the column 3 times with 1 ml of separation buffer.</li>
	<li>Assess CD138 enrichment with another stained thin-layer cell preparation slide10.</li>
	<li>Filter plasma obtained from bone marrow biopsy from each patient with a 0.22 &#181;m syringe filter. Use fresh plasma from the same patient as the CD138+ cells.</li>
	<li>Prepare media for experiment by supplementing RPMI-1640 with 10% heat Inactivated fetal bovine serum, 10% patient plasma and 1% penicillin&#8211;streptomycin.</li>
	<li>Collect the flow-through of the selection (CD138-) and follow the classical adhesion method12 to select for bone marrow mesenchymal cells (BMSCs). Since this process requires weeks before BMSCs are ready to be used, it is necessary to have BMSCs ready from previous patients or healthy donors.</li>
</ol>
2. Seeding Cells in Plates (Using a Manual Multi-channel Pipettor)
<ol>
	<li>Use a multi-well plate (384 or 1,536) with black walls and a transparent flat bottom, preferentially one optimized for optical applications and cell culture.</li>
	<li>Co-culture BMSCs with MM cells in either collagen type I or basement membrane matrix, however, HUVECs require basement membrane matrix.</li>
	<li>Keep the final densities of each cell type in the following range: 3 x 105 cells/ml for MM cell lines, 2 x 105 cells/ml for HUVECs or BMSCs, and 2 x 106 cells/ml for patient-derived MM cells. 
	Note: These densities are the result of experimental optimization to allow for the highest possible image quality and longest possible imaging time while maintaining biological relevance in the assays. MM cell lines are seeded at lower densities than primary MM cells due to their faster replication rate and larger size.</li>
	<li>Co-culture of primary MM cells with BMSCs:
	<ol>
		<li>Prepare 100 &#181;l aliquots of pre-mixed media consisting of 20 &#181;l of 10x MEM, 20 &#181;l of deionized H2O, 10 &#181;l of 7.5% sodium bicarbonate solution, and 50 &#181;l of 1x RPMI 1,640 and store at 4 &#176;C.</li>
		<li>At the time of seeding the plates with MM cells, mix aliquots of pre-mixed media with 150 &#181;l of 3.1 mg/ml Bovine collagen type I to a final volume of 250 &#181;l.</li>
		<li>Re-suspend 50 &#181;l of cells in RPMI 1,640 at six times the final desired density.</li>
		<li>Mix to cell suspension with collagen mix to create a final volume of 300 &#181;l using a P200 pipette.</li>
		<li>Using a manual or repeater pipette, deposit a 8 &#181;l drop of final cell/matrix mix in the center of each well in 384-well plates, or 2 &#181;l in each well of 1,536 well plates (See step 2.6 for an example of spatial arrangement of wells).</li>
		<li>Centrifuge plate for 2 min at 500 x g to concentrate all cells to the same focal plane during imaging.</li>
		<li>Leave plate in an incubator (5% CO2, 37 &#176;C) for 1 hr, for gel polymerization.</li>
		<li>Add 80 &#181;l of supplemented growth media (RPMI-1640, 10% FBS HI, 10% patient-derived plasma, 1% P/S) to each well in 384-well plates, or 8 &#181;l in 1,536-well plates.</li>
		<li>Leave plate O/N in incubator (5% CO2, 37 &#176;C) for adhesion of stroma to the bottom of the plate.</li>
	</ol>
	</li>
	<li>Co-culture of primary MM cells with HUVECs:
	<ol>
		<li>Transfer basement membrane matrix from -80 &#176;C to a bucket with ice to thaw.</li>
		<li>Count and re-suspend primary cells and HUVECs in RPMI-1640 media at 4 times the final density, each in a separate tube.</li>
		<li>Mix patient cells and HUVECs volumes at a 1:1 proportion.</li>
		<li>Once basement membrane matrix is thawed, but still not polymerized, mix 1:1 with cell mixture from previous step.</li>
		<li>Seed droplets with adequate volume of cell-matrix mix in the center of each well (8 &#181;l for 384-well plates and 2 &#181;l for 1,536-well plates, see step 2.6 for an example of spatial arrangement of wells).</li>
		<li>Centrifuge plate at 500 x g for 10 min.</li>
		<li>Place plate in incubator (5% CO2, 37 oC) for 1 hr for matrix polymerization.</li>
		<li>Add growth media (RPMI-1640 supplemented with 10% FBS, 10% patient plasma and 1% P/S) to each well (80 &#181;l for 384-well plates, 8 &#181;l for 1,536-well plates).</li>
		<li>Leave plate O/N in incubator (5% CO2, 37 &#176;C) for adhesion of HUVECs to the bottom of the plate.</li>
	</ol>
	</li>
	<li>Seed a 384-well plate. Figure 3 depicts a typical spatial distribution of seeding.
	<ol>
		<li>Starting on well B2, seed as many columns as drugs to be tested. In the example of Figure 3, use seven drugs.</li>
		<li>Repeat seeding as many times as concentrations to be used. In the example in Figure 3, use five concentrations.</li>
		<li>Seed four more wells for control conditions.</li>
		<li>Repeat steps 2.6.1 and 2.6.2 for the second replicate.</li>
		<li>Repeat steps 2.6.1 to 2.6.4 for every patient sample to be tested in the plate.</li>
		<li>Seed a MM cell line in two lines of wells, each with as many wells as drugs to be tested (in duplicate). Each of these wells will be treated with the highest concentration of each drug to ensure that the stock used had adequate potency (see Figure 3 for example).</li>
		<li>Seed two wells with a MM cell line to serve as control of the experimental conditions, such as proper functioning of the bench top incubator, growth media, etc.</li>
	</ol>
	</li>
</ol>
3. Seeding Cells in Plates (Using a Robotic Pipettor)
Note: This series of steps seeds a 384-well plate using a robotic pipettor. The design of the plate is depicted in Supplemental Figure 1, where primary MM cells are tested against a panel of 31 different drugs at five different concentrations in two replicates, plus negative control. A cell line is also seeded as positive control for assessment of drug efficacy and tested against all 31 drugs at the highest concentration, in two replicates. The files provided are for a particular brand and model (see Materials table) but the algorithm can be adapted to any robotic pipettors.
<ol>
	<li>Co-culture of primary MM cells with BMSCs:
	<ol>
		<li>Prepare a 15 ml tube consisting of 240 &#181;l of 10x MEM, 240 &#181;l of deionized H2O, 120 &#181;l of 7.5% sodium bicarbonate solution, 600 &#181;l of 1x RPMI 1,640 and 1.8 ml of 3.1 mg/ml Bovine collagen type I. Label tube as &#8220;pre-mix for CD138+&#8221;. Place on ice until use.</li>
		<li>Prepare a 1.5 ml tube consisting of 50 &#181;l of 10x MEM, 50 &#181;l of deionized H2O, 25 &#181;l of 7.5% sodium bicarbonate solution, 125 &#181;l of 1x RPMI 1,640 and 375 &#181;l of 3.1 mg/ml Bovine collagen type I. Label tube as &#8220;pre-mix for Cell Line&#8221;. Place on ice until use.</li>
		<li>Re-suspend 300 &#181;l of CD138+ cells in RPMI 1,640 at six times the final desired density. Re-suspend 300 &#181;l of BMSC cells in RPMI 1640 at six times the final desired density. Mix both volumes together in a 1.5 ml tube and label &#8220;CD138+&#8221;. Place in incubator until use.</li>
		<li>Re-suspend 60 &#181;l of cell line in RPMI 1640 at six times the final desired density. Re-suspend 60 &#181;l of BMSC cells in RPMI 1640 at six times the final desired density. Mix both volumes together in a 1.5 ml tube and label &#8220;Cell Line&#8221;. Place in incubator until use.</li>
		<li>Using the software provided with the robotic pipettor, load the first script file, &#8220;cell_seedingPt47.PGM&#8221;. Place a 200 &#181;l pipette tip box, a microtiter plate, and a sterile 384 well plate in the stations A, B and E, respectively, of the robot.</li>
		<li>Mix the contents of tubes &#8220;pre-mix for CD138+&#8221; and &#8220;CD138+&#8221;. Transfer 1.5 ml of its contents to the well #1 of the microtiter plate. Place the tube with remaining volume on ice. Start the program. The robot will seed the first 176 wells (11 left-most columns) of the 384-well plate and then pause. Transfer the remaining of the tube on ice to well #2 of microtiter plate. Resume the program. The robot will seed the remaining 144 wells of the 384-well plate and pause.</li>
		<li>Mix the contents of tubes &#8220;pre-mix for Cell Line&#8221; and &#8220;Cell Line&#8221; and transfer contents to well #3 of microtiter plate. Resume program. The robot will seed the remaining 64 wells of the 384-well plate.</li>
		<li>Place 384-well plate in centrifuge for 10 min at 500 x g and 4 &#176;C. Transfer plate to incubator (5% CO2, 37 &#176;C) for 1 hr&#160;for collagen polymerization.</li>
		<li>Load the second script file, &#8220;media_layer.PGM&#8221;. Place 120 &#181;l pipette tip box, a reagent reservoir with 31 ml of RPMI-1640 supplemented with 10% FBS, 10% patient plasma and 1% P/S, and the 384-well plate with cells into stations A, B and E, respectively. Run the program. The robot will transfer 81 &#181;l of media to each well. Once finished, transfer 384-well plate to incubator and allow stroma to adhere to substrate O/N.</li>
	</ol>
	</li>
</ol>
4. Drug Preparation and Drugging of Plates (Using a Manual Multi-channel Pipettor)
<ol>
	<li>Prepare a template similar to Figure 3 in order to facilitate the process of adding drug to wells and reduce chance of confusion.</li>
	<li>Prepare, in a 96-well plate, a serial dilution of each of the drugs to be tested in the plate, for instance, for five concentrations using a 3-fold dilution:
	<ol>
		<li>Add 120 &#181;l of drug at 10x the desired concentration in the highest concentration well. For example, use 500 &#181;M melphalan if the highest concentration the cells will be exposed in the plate will be 50 &#181;M.</li>
		<li>Add 80 &#181;l of growth media (RPMI supplemented with 10%FBS, 10% patient-derived plasma and 1% penicillin/streptomycin (P/S)) to the four subsequent wells.</li>
		<li>Transfer 40 &#181;l from the first well to the second and mix, to a total volume of 120 &#181;l at 1/3 of the first well&#8217;s drug concentration, or 167 &#181;M.</li>
		<li>Repeat step 4.2.3 to the remaining wells (e.g., transfer 40 &#181;l from second to third, mix, then transfer 40 &#181;l from third to fourth, etc.).</li>
	</ol>
	</li>
	<li>Transfer 8 &#181;l from each drug containing well to the corresponding well in the cell plate. Each drug containing well should have enough volume for 10 wells in the cell plate. In the example of Figure 3, each drug concentration is added to 6 different wells, except for the highest concentration, which is added to 8 wells.</li>
	<li>Add 8 &#181;l of growth media (RPMI supplemented with 10%FBS, 10% patient-derived plasma and 1% P/S) to the control wells.</li>
	<li>Place cells in microscope as soon as ready and turn on the bench top incubation.</li>
</ol>
5. Drug Preparation and Drugging of Plates (Using a Robotic Pipettor)
<ol>
	<li>Download script files for robotic pipettor from http://www.i-genics.com/Jove2014Silva/Precision XS files.zip</li>
	<li>Load the script &#8220;media_layer_DRUGPLATE.PGM&#8221; in the robotic pipettor user interface. Place a 120 &#181;l pipette tip box, reservoir with 21 ml of RPMI-1,640 supplemented with 10% FBS, 10% patient plasma and 1% P/S and an empty 384-well plate in stations A, B and E, respectively. Run the program, the robotic pipettor will add 30 &#181;l of media to all wells in the 384-well plate.</li>
	<li>Following the template from Supplemental Figure 2 add 200 &#181;l of drug at 20x maximum concentration to each well of a microtiter plate. This setup accommodates up to 31 drugs. To the control well (CTRL), add RPMI-1640 supplemented with 10% FBS, 10% patient plasma and 1% P/S.</li>
	<li>Place a 120 &#181;l pipette tip box, microtiter plate with drugs at 20X concentration, and 384-well with media (from step 5.1) in stations A, B and C, respectively. Load the program &#8220;drug_plate.PGM&#8221;. The robotic pipettor will create a serial dilution of 1:3, following the spatial distribution in Supplemental Figure 1.</li>
	<li>Place a 120 &#181;l pipette tip box, the 384-well plate with drug dilution (from step 5.3) and the 384-well plate with cells (from step 3.1.9) into stations A, B and C, respectively. Load and run program &#8220;drug_add.PGM&#8221;. The robotic pipettor will transfer 8 &#181;l of drug from each well in the drug plate to its counterpart in the cell plate. Once finished, transfer cell plate to the incubator of the digital microscope as soon as possible.</li>
</ol>
6. Imaging of Cells in Plate
Note: The procedure below applies to the Evos Auto FL microscope, but can be readily adapted to other motorized stage microscopes with bench top incubation or incubator-embedded microscopes.
<ol>
	<li>Clean the interior of the bench top incubator with an ethanol-wet wipe and carefully remove the lid of the plate while placing the lid of the incubator.</li>
	<li>Follow the software steps to add the beacons. This is the term used to refer to landmarks for regions of interest, to be imaged successively during the experiment (see software user guide for details).</li>
	<li>Use a 5X or 10X magnification objective. Make sure that the focus is similar to Figure 2: MM cells appear as bright disks surrounded by a dark ring and BMSCs or HUVECs are barely visible. Some primary MM cells are very small and thus a fine-tuning might be required to find the optimum focus.</li>
	<li>Adjust the acquisition interval between 10-30 min and for duration of at least 96 hr. While longer intervals between acquisitions are acceptable, intervals of 45 min or more may significantly reduce the precision of measurement of viability.</li>
	<li>Configure the software so that the images of each well are stored in separate files named Beacon-1, Beacon-2, etc. If the robotic pipettor was used, set the beacons in the order depicted in Supplemental Figure 3.</li>
	<li>Make sure that there is enough water in the incubator humidifier and gas, so that cells will be in optimum conditions.</li>
	<li>Upon completion of the experiment, copy the folders containing the images to the computer that will run the analysis.</li>
</ol>
7. Quantification of Drug Sensitivity
Note: The following instructions guide the use of the image analysis using a computer cluster, since the analysis of a multi-well plate in a personal computer is extremely time consuming.
<ol>
	<li>Download ImageJ software from NIH&#8217;s website: http://imagej.nih.gov/ij/</li>
	<li>Download script and plugins at http://www.i-genics.com/Jove2014Silva/</li>
	<li>Follow instructions in http://www.i-genics.com/Jove2014Silva/UserGuide.pdf to run digital image analysis software. The result should be a spreadsheet named Results.csv containing the viability measurements at regular intervals for each well in the plate for the duration of the experiment (i.e.,&#160;96 hr).</li>
	<li>If using a manual multi-channel pipettor, perform the following steps.
	<ol>
		<li>Download the file http://www.i-genics.com/Jove2014Silva/ExperimentalDesign.txt and modify it to match the layout of the plate defined in step 3.1 (e.g., Figure 3).</li>
		<li>Download the software http://www.i-genics.com/Jove2014Silva/Evos384.jar and run it using the files created in steps 5.3 and 5.4 as the input parameter. The result will be a folder name Report containing multiple spreadsheets, each grouping the results for a particular drug.</li>
		<li>Copy and paste contents in spreadsheet template http://www.i-genics.com/Jove2014Silva/GraphPadAnalysisPT.pzfx 
		Note: The result should be graphs such as the one depicted in Figure 4, representing the chemosensitivity of the sample to different drugs as a function of drug concentration and exposure time.</li>
	</ol>
	</li>
	<li>If using a robotic pipettor, perform the following steps.
	<ol>
		<li>Download template files from Download script files for robotic pipettor from http://www.i-genics.com/Jove2014Silva/Robotic Template Files.zip and extract files in a directory.</li>
		<li>Modify the file DrugList.csv according to the list of drugs and highest drug concentration in the plate with cells. Follow the layout of Supplemental Figure 2.</li>
		<li>Run the program BuildExperimentalDesign.java passing as parameter the folder containing the files extracted in step 7.5.1 and the files Results.csv from step 7.3. The outcome should be two folders name MM1_S and PtSample. The first contains a description of the wells (drugs and concentrations) for the cell line positive control. The second contains the same information, but regarding the part of the plate seeded with patient cells.</li>
		<li>Copy the file Results.csv into each of the directories created in the step 7.5.3. Download the software http://www.i-genics.com/Jove2014Silva/Evos384.jar and run it using the files created in steps 7.5.3 for both folders. The result will be a folder name Report in each of the folders created in 7.5.3. The Report folder contains multiple spreadsheets, each grouping the results for a particular drug.</li>
		<li>Run the program BuildGraphPadFile.java and pass as parameter the folder containing the files extracted in step 7.5.1 and the files Results.csv from step 7.3. The result will be a graphpad file containing the dose response curves for each of the 31 drugs, and normalized by the control. Each chart will contain 5 drug concentrations for the primary MM cells and one concentration for the positive cell line control.</li>
	</ol>
	</li>
</ol>

<ol>
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G., Jacobson, J., Barlogie, B., Crowley, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Magnitude+of+response+with+myeloma+frontline+therapy+does+not+predict+outcome:+importance+of+time+to+progression+in+southwest+oncology+group+chemotherapy+trials.">Magnitude of response with myeloma frontline therapy does not predict outcome: importance of time to progression in southwest oncology group chemotherapy trials.</a> J Clin Oncol. 22, 1857-1863 (2004).</li><li>Harousseau, J. L., Attal, M., Avet-Loiseau, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+role+of+complete+response+in+multiple+myeloma.">The role of complete response in multiple myeloma.</a> Blood. 114, 3139-3146 (2009).</li><li>Khin, Z. 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The authors have no conflict of interest to disclose.

In summary, this is a powerful and high throughput method to quantify chemosensitivity of primary MM cells and ex vivo pharmacodynamics of drugs in a reconstruction of the bone marrow. The critical steps within this protocol are the proper seeding of the wells and adequate focusing (see Figure 2 for expected results): ensure that MM and stromal cells are uniformly distributed, that stromal cells are adherent to the bottom of the well, that all MM cells are in the same focal plane, and that MM ce...

The goal of this method is to characterize the drug sensitivity of multiple myeloma (MM) primary cells to a panel of agents ex vivo, as close as possible to physiological conditions, and with sufficient precision that these results can be used to identify chemoresistant sub-populations within the tumor burden and, ultimately, to parameterize computational models designed to estimate clinical response.
Computational models are powerful tools to analyze complex systems, such as cancer-host-therapy interactions. However, models are only as good as the data used to parameterize them. Unfortunately, most data available in literature cannot be used in its current form to parameterize such models, as they often are obtained in mutually exclusive experimental conditions. Thus, new experiments are often required with the goal of obtaining the set of experimental parameters needed. Most viability assays, however, are destructive and thus limited to a small number of time points, often only one. This greatly handicaps the usage of chemosensitivity assays to parameterize computational models, since such experiments fail to provide information on the temporal dynamics of the system. This is especially true with primary cancer cells, which are often limited to a few millions per sample, and have a short lifespan after biopsy, thus limiting the number of experimental conditions available. In addition, most viability assays require the separation of the cancer from the non-cancer (stroma) cells at the time of quantification, which adds extra work to the protocol, further perturbs the cells, and limits the number of experiments that can be performed.
40 years ago, Salmon and collaborators1 proposed their famous in vitro colony formation assay for assessment of chemosensitivity of tumor cells. Unfortunately this assay found mixed success due to the small number of multiple myeloma (MM) patient samples that were capable of forming colonies under control conditions: It was estimated that only a small subgroup of 0.001% to 0.1% of MM cells were capable of replication, being termed as multiple myeloma stem cells2. This significantly limited the success rate of the assay and the number of drugs that could be tested at one time, even in more recent models3. This issue is much more important now when MM agents (standard or experimental) are more numerous than four decades ago.
A major limitation of these early assays is their dichotomized output: either a patient is &#8220;sensitive&#8221; or &#8220;resistant&#8221; to a particular drug. No information is provided regarding the degree of sensitivity and heterogeneity of the tumor population. Thus, patients with small sub-populations of fast-growing resistant cells would be classified as &#8220;sensitive&#8221; to therapy, but would relapse shortly, and thus not benefit from treatment. Given the importance of duration of response in overall survival (OS) of cancer patients4,5, it is clear how these assays were not able to properly estimate OS consistently.
In order to circumvent these limitations, and to be able to generate patient-specific computational models that would estimate personalized clinical response to a panel of drugs, we have developed a method for non-destructively testing drug sensitivity of multiple myeloma (MM) cell lines and primary MM cells in an ex vivo reconstruction of the bone marrow microenvironment, including extracellular matrix and stroma6. This assay, however, had the limitation of relying on a particular commercial microfluidic slide, whose dimensions and cost restricted the number of experiments or drugs that could be performed at once in a given piece of equipment.
The here described system extends this original assay into a high-throughput organotypic dose-response platform, for in vitro screening of drugs, based on a digital image analysis algorithm to non-destructively quantify cell viability. Each well in 384 or 1,536-well plates is a 3D reconstruction of the bone marrow microenvironment, including primary MM cells, extracellular matrix, and patient-derived stroma and growth factors. Live microscopy and digital image analysis are used to detect cell death events in different drug concentrations, which are used to generate dose-response surfaces. From the in vitro data, a mathematical model identifies the size and chemosensitivity of sub-populations within the patient&#8217;s tumor burden, and can be used to simulate how the tumor would respond to the drug(s) in physiological conditions in a clinical regimen6 (Figure 1).
The main innovations of this platform are: (a) small number of cancer cells required (1,000-10,000 per drug concentration); (b) assessment of drug efficacy in physiological conditions (extracellular matrix, stroma, patient-derived growth factors); (c) No toxicity from viability markers7 since only bright field imaging is used, thus no need to transfect cells with fluorescence8 or bioluminescence9; (d) continuous imaging provides drug effect as a function of concentration and exposure time (pharmacodynamics); and (e) the integration between in vitro and computational evolutionary models, to estimate clinical outcome6 (Silva et al., in preparation).
The key factor that allows the digital image analysis algorithm to discern cancer from stromal cells is their different affinity to the bottom of the well: MM cells do not adhere, and remain in suspension in the matrix, while stromal cells adhere to the bottom of the well and then stretch.
This separation occurs even though MM and stroma are seeded at the same time, and occurs during the O/N process of incubation. The spinning down in the centrifuge following seeding of the plate further accelerates this process. As a consequence, MM cells appear in the image as round bright disks surrounded by a dark ring, while the stroma maintains a low profile and a darker shade (Figure 2). Thus, the assay in its current form is best suited for non-adherent cancer cells, although adjustments in the algorithm could be done to separate cancer and stroma based on other morphologic features, such as size and shape. In this protocol we describe two types of extracellular matrix (collagen and basement membrane matrix) as well as two types of co-cultures, with (bone marrow derived mesenchymal stem cells) BMSC and HUVECS, representing the interstitial and perivascular niches of the bone marrow, respectively.
Using a 384-well plate, 5 concentrations per drug and two replicates, we were able to test up to 31 different drugs with the sample of a single patient. In 1,536-well plates this number is 127. Figure 3 depicts the layout currently used for manual cell seeding, while Supplemental Figure 1 represents the optimum distribution using a robotic pipettor. In the design from Figure 3, each 384-well plate can carry 3 patient samples with 7 different drugs, or one patient sample tested with 21 drugs. Each drug is represented by 5 concentrations, and each condition is seeded in duplicates. 4 control wells (no drug added) are seeded for each set of 7 drugs (e.g., wells 36-39, 126-129 and 200-203). To ensure the potency of the drugs used, a human myeloma cell line (e.g., H929 or MM1.S) is also seeded, and drugged in duplicates at the highest concentration of each of the drugs used (wells 76-89). The positive cell line control ensures that the drugs used have adequate potency, since their dose response curves are comparable across experiments. Two wells are seeded with a myeloma cell line as control for the environmental conditions, in other words, to detect possible problems in the bench top incubator during imaging (wells 75 and 90). The enumeration of the wells follows a zigzag pattern in order to reduce the distance covered by the motorized stage of the microscope, which reduces acquisition time and reduces wear of the equipment.

<table border="0" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td>EVOS FL AUTO</td>
			<td>AMG</td>
			<td>AMAFD1000 + AMC1000</td>
			<td>Digital microscope equipped with motorized stage and bench top incubator.</td>
		</tr>
		<tr>
			<td>384-well plate CellBind</td>
			<td>CORNING</td>
			<td>CLS3683 SIGMA</td>
			<td>Corning CellBIND 384 well plates 
			384 well plate, polystyrene, CellBIND surface, sterile, clear flat bottom, black, w/lid</td>
		</tr>
		<tr>
			<td>1,536-well plate CellBind</td>
			<td>CORNING</td>
			<td>CLS3832 ALDRICH</td>
			<td>Corning 1536 well plates, low base, surface treatment CellBIND, sterile</td>
		</tr>
		<tr>
			<td>Ficoll-Paque Plus&#160;</td>
			<td>GE Healthcare</td>
			<td>GE17-1440-02 SIGMA</td>
			<td>For in vitro isolation of lymphocytes from human peripheral blood.</td>
		</tr>
		<tr>
			<td>CD138 magnetic beads</td>
			<td>Miltenyi&#160;</td>
			<td>130-051-301</td>
			<td>Antibody conjugated magnetic beads for selection of CD138+ cells.</td>
		</tr>
		<tr>
			<td>LS columns</td>
			<td>Miltenyi&#160;</td>
			<td>&#160;130-042-401</td>
			<td>Column for separation of cells.</td>
		</tr>
		<tr>
			<td>MidiMACS Separator</td>
			<td>Miltenyi&#160;</td>
			<td>130-042-302</td>
			<td>Magnet for separation column.</td>
		</tr>
		<tr>
			<td>Matrigel</td>
			<td>Sigma-Aldrich</td>
			<td>E6909 SIGMA</td>
			<td>ECM Gel from Engelbreth-Holm-Swarm murine sarcoma</td>
		</tr>
		<tr>
			<td>Getrex</td>
			<td>Life Technologies</td>
			<td>A1413201</td>
			<td>LDEV-Free Reduced Growth Factor Basement Membrane Matrix</td>
		</tr>
		<tr>
			<td>HUVEC</td>
			<td>Life Technologies</td>
			<td>C-003-25P-B</td>
			<td>Human Umbilical Vein Endothelial Cells (HUVEC )</td>
		</tr>
		<tr>
			<td>RPMI-1640 media</td>
			<td>GIBCO</td>
			<td>11875-093</td>
			<td>RPMI 1640 Medium + L-Glutamine + Phenol Red</td>
		</tr>
		<tr>
			<td>FBS Heat inactivated</td>
			<td>GIBCO</td>
			<td>10082-147</td>
			<td>Fetal Bovine Serum, certified, heat inactivated, US origin</td>
		</tr>
		<tr>
			<td>3.1mg/mL Bovine collagen type I</td>
			<td>Advanced Biomatrix</td>
			<td>5005-B</td>
			<td>Bovine Collagen Solution, Type I, 3 mg/ml, 100 ml</td>
		</tr>
		<tr>
			<td>Precision XS</td>
			<td>BIOTEK</td>
			<td>PRC3841</td>
			<td>Robotic pipettor system</td>
		</tr>
	</tbody>
</table>

an organotypic high throughput system for characterization of drug sensitivity of primary multiple myeloma cells

In this work we describe a novel approach that combines ex vivo drug sensitivity assays and digital image analysis to estimate chemosensitivity and heterogeneity of patient-derived multiple myeloma (MM) cells. This approach consists in seeding primary MM cells freshly extracted from bone marrow aspirates into microfluidic chambers implemented in multi-well plates, each consisting of a reconstruction of the bone marrow microenvironment, including extracellular matrix (collagen or basement membrane matrix) and stroma (patient-derived mesenchymal stem cells) or human-derived endothelial cells (HUVECs). The chambers are drugged with different agents and concentrations, and are imaged sequentially for 96 hr through bright field microscopy, in a motorized microscope equipped with a digital camera. Digital image analysis software detects live and dead cells from presence or absence of membrane motion, and generates curves of change in viability as a function of drug concentration and exposure time. We use a computational model to determine the parameters of chemosensitivity of the tumor population to each drug, as well as the number of sub-populations present as a measure of tumor heterogeneity. These patient-tailored models can then be used to simulate therapeutic regimens and estimate clinical response.

The flow of the experiment is briefly described in Figure 1. If all steps are completed successfully, the images obtained by the microscope should be equivalent to Figure 2: live MM cells should be clearly seen as bright disks and BMSCs or HUVECs should be barely visible and well distributed in the background. As seen in Figure 2A, MM cells range in size from one patient to the other, but in general they are smaller than cell lines. Since they practically do not replicat...

Watch this Scientific Journal Video about An Organotypic High Throughput System for Characterization of Drug Sensitivity of Primary Multiple Myeloma Cells at JoVE.com

An Organotypic High Throughput System for Characterization of Drug Sensitivity of Primary Multiple Myeloma Cells

We describe a high-throughput drug sensitivity assay for primary multiple myeloma cells. It consists of a reconstruction of the bone marrow microenvironment (including extracellular matrix and stroma) in multi-well plates, and a non-invasive method for longitudinal quantification of cell viability.

In this work we describe a novel approach that combines ex vivo drug sensitivity assays and digital image analysis to estimate chemosensitivity and ...

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Medicine

8.6K ビュー.  H. Lee Moffitt Cancer Center and Research Institute. We describe a high-throughput drug sensitivity assay for primary multiple myeloma cells. It consists of a reconstruction of the bone marrow microenvironment (including extracellular matrix and stroma) in multi-well plates, and a non-invasive method for longitudinal quantification of cell viability.

ビデオ: An Organotypic High Throughput System for Characterization of Drug Sensitivity of Primary Multiple Myeloma Cells

Coculture System with an Organotypic Brain Slice and 3D Spheroid of Carcinoma Cells

Patients with cerebral metastasis of carcinomas have a poor prognosis. However, the process at the metastatic site has barely been investigated, in particular the role of the resident (stromal) cells. Studies in primary carcinomas demonstrate the influence of the microenvironment on metastasis, even on prognosis1,2. Especially the tumor associated macrophages (TAM) support migration, invasion and proliferation3. Interestingly, the major target sites of metastasis possess tissue-specific macrophages, such as Kupffer cells in the liver or microglia in the CNS. Moreover, the metastatic sites also possess other tissue-specific cells, like astrocytes. Recently, astrocytes were demonstrated to foster proliferation and persistence of cancer cells4,5. Therefore, functions of these tissue-specific cell types seem to be very important in the process of brain metastasis6,7.
Despite these observations, however, up to now there is no suitable in vivo/in vitro model available to directly visualize glial reactions during cerebral metastasis formation, in particular by bright field microscopy. Recent in vivo live imaging of carcinoma cells demonstrated their cerebral colonization behavior8. However, this method is very laborious, costly and technically complex. In addition, these kinds of animal experiments are restricted to small series and come with a substantial stress for the animals (by implantation of the glass plate, injection of tumor cells, repetitive anaesthesia and long-term fixation). Furthermore, in vivo imaging is thus far limited to the visualization of the carcinoma cells, whereas interactions with resident cells have not yet been illustrated. Finally, investigations of human carcinoma cells within immunocompetent animals are impossible8.
For these reasons, we established a coculture system consisting of an organotypic mouse brain slice and epithelial cells embedded in matrigel (3D cell sphere). The 3D carcinoma cell spheres were placed directly next to the brain slice edge in order to investigate the invasion of the neighboring brain tissue. This enables us to visualize morphological changes and interactions between the glial cells and carcinoma cells by fluorescence and even by bright field microscopy. After the coculture experiment, the brain tissue or the 3D cell spheroids can be collected and used for further molecular analyses (e.g. qRT-PCR, IHC, or immunoblot) as well as for investigations by confocal microscopy. This method can be applied to monitor the events within a living brain tissue for days without deleterious effects to the brain slices. The model also allows selective suppression and replacement of resident cells by cells from a donor tissue to determine the distinct impact of a given genotype. Finally, the coculture model is a practicable alternative to in vivo approaches when testing targeted pharmacological manipulations.

The organotypic brain slice coculture with carcinoma cells enables visualizing morphological changes by fluorescence as well as bright field (video) microscopy during the process of carcinoma cell invasion of brain tissue. This model system also allows for cell exchange and replenishment approaches and offers a wide variety of manipulations and analyses.

Patients with cerebral metastasis of carcinomas have a poor prognosis. However, the process at the metastatic site has barely been investigated, in ...

High Throughput Characterization of Adult Stem Cells Engineered for Delivery of Therapeutic Factors for Neuroprotective Strategies

Mesenchymal stem cells (MSCs) derived from bone marrow are a powerful cellular resource and have been used in numerous studies as potential candidates to develop strategies for treating a variety of diseases. The purpose of this study was to develop and characterize MSCs as cellular vehicles engineered for delivery of therapeutic factors as part of a neuroprotective strategy for rescuing the damaged or diseased nervous system. In this study we used mouse MSCs that were genetically modified using lentiviral vectors, which encoded brain-derived neurotrophic factor (BDNF) or glial cell-derived neurotrophic factor (GDNF), together with green fluorescent protein (GFP). 
Before proceeding with in vivo transplant studies it was important to characterize the engineered cells to determine whether or not the genetic modification altered aspects of normal cell behavior. Different culture substrates were examined for their ability to support cell adhesion, proliferation, survival, and cell migration of the four subpopulations of engineered MSCs. High content screening (HCS) was conducted and image analysis performed. 
Substrates examined included: poly-L-lysine, fibronectin, collagen type I, laminin, entactin-collagen IV-laminin (ECL). Ki67 immunolabeling was used to investigate cell proliferation and Propidium Iodide staining was used to investigate cell viability. Time-lapse imaging was conducted using a transmitted light/environmental chamber system on the high content screening system.
Our results demonstrated that the different subpopulations of the genetically modified MSCs displayed similar behaviors that were in general comparable to that of the original, non-modified MSCs. The influence of different culture substrates on cell growth and cell migration was not dramatically different between groups comparing the different MSC subtypes, as well as culture substrates. 
This study provides an experimental strategy to rapidly characterize engineered stem cells and their behaviors before their application in long-term in vivo transplant studies for nervous system rescue and repair.

This study describes an experimental platform to rapidly characterize engineered stem cells and their behaviors before their application in long-term in vivo transplant studies for nervous system rescue and repair.

Mesenchymal stem cells (MSCs) derived from bone marrow are a powerful cellular resource and have been used in numerous studies as potential candidates to ...

A Brain Tumor/Organotypic Slice Co-culture System for Studying Tumor Microenvironment and Targeted Drug Therapies

Brain tumors are a major cause of cancer-related morbidity and mortality. Developing new therapeutics for these cancers is difficult, as many of these tumors are not easily grown in standard culture conditions. Neurosphere cultures under serum-free conditions and orthotopic xenografts have expanded the range of tumors that can be maintained. However, many types of brain tumors remain difficult to propagate or study. This is particularly true for pediatric brain tumors such as pilocytic astrocytomas and medulloblastomas. This protocol describes a system that allows primary human brain tumors to be grown in culture. This quantitative assay can be used to investigate the effect of microenvironment on tumor growth, and to test new drug therapies. This protocol describes a system where fluorescently labeled brain tumor cells are grown on an organotypic brain slice from a juvenile mouse. The response of tumor cells to drug treatments can be studied in this assay, by analyzing changes in the number of cells on the slice over time. In addition, this system can address the nature of the microenvironment that normally fosters growth of brain tumors. This brain tumor organotypic slice co-culture assay provides a propitious system for testing new drugs on human tumor cells within a brain microenvironment.

Many types of human brain tumors are localized to specific regions within the brain and are difficult to grow in culture. This protocol addresses the role of tumor microenvironment and investigates new drug treatments by analyzing fluorescent primary brain tumor cells growing in an organotypic mouse brain slice. &#160;

Brain tumors are a major cause of cancer-related morbidity and mortality. Developing new therapeutics for these cancers is difficult, as many of these ...

Forskolin-induced Swelling in Intestinal Organoids: An In Vitro Assay for Assessing Drug Response in Cystic Fibrosis Patients

Recently-developed cystic fibrosis transmembrane conductance regulator (CFTR)-modulating drugs correct surface expression and/or function of the mutant CFTR channel in subjects with cystic fibrosis (CF). Identification of subjects that may benefit from these drugs is challenging because of the extensive heterogeneity of CFTR mutations, as well as other unknown factors that contribute to individual drug efficacy. Here, we describe a simple and relatively rapid assay for measuring individual CFTR function and response to CFTR modulators in vitro. Three dimensional (3D) epithelial organoids are grown from rectal biopsies in standard organoid medium. Once established, the organoids can be bio-banked for future analysis. For the assay, 30-80 organoids are seeded in 96-well plates in basement membrane matrix and are then exposed to drugs. One day later, the organoids are stained with calcein green, and forskolin-induced swelling is monitored by confocal live cell microscopy at 37 &#176;C. Forskolin-induced swelling is fully CFTR-dependent and is sufficiently sensitive and precise to allow for discrimination between the drug responses of individuals with different and even identical CFTR mutations. In vitro swell responses correlate with the clinical response to therapy. This assay provides a cost-effective approach for the identification of drug-responsive individuals, independent of their CFTR mutations. It may also be instrumental in the development of future CFTR modulators.

Forskolin-induced Swelling in Intestinal Organoids: An In Vitro Assay for Assessing Drug Response in Cystic Fibrosis Patients

This protocol describes an assay for measuring CFTR function and CFTR modulator responses in cultured tissue from subjects with cystic fibrosis (CF). Biopsy-derived intestinal organoids swell in a cAMP-driven fashion, a response that is defective (or strongly reduced) in CF organoids and can be restored by exposure to CFTR modulators.

Recently-developed cystic fibrosis transmembrane conductance regulator (CFTR)-modulating drugs correct surface expression and/or function of the mutant ...

Optimized LC-MS/MS Method for the High-throughput Analysis of Clinical Samples of Ivacaftor, Its Major Metabolites, and Lumacaftor in Biological Fluids of Cystic Fibrosis Patients

Defects in the cystic fibrosis trans-membrane conductance regulator (CFTR) are the cause of cystic fibrosis (CF), a disease with life-threatening pulmonary manifestations. Ivacaftor (IVA) and ivacaftor-lumacaftor (LUMA) combination are two new breakthrough CF drugs that directly modulate the activity and trafficking of the defective CFTR-protein. However, there is still a dearth of understanding on pharmacokinetic/pharmacodynamic parameters and the pharmacology of ivacaftor and lumacaftor. The HPLC-MS technique for the simultaneous analysis of the concentrations of ivacaftor, hydroxymethyl-ivacaftor, ivacaftor-carboxylate, and lumacaftor in biological fluids in patients receiving standard ivacaftor or ivacaftor-lumacaftor combination therapy has previously been developed by our group and partially validated to FDA standards. However, to allow the high-throughput analysis of a larger number of patient samples, our group has optimized the reported method through the use of a smaller pore size reverse-phase chromatography column (2.6 &#181;m, C8 100 &#197;; 50 x 2.1 mm) and a gradient solvent system (0-1 min: 40% B; 1-2 min: 40-70% B; 2-2.7 min: held at 70% B; 2.7-2.8 min: 70-90% B; 2.8-4.0 min: 90% B washing; 4.0-4.1 min: 90-40% B; 4.1-6.0 min: held at 40% B) instead of an isocratic elution. The goal of this study was to reduce the HPLC-MS analysis time per sample dramatically from ~15 min to only 6 min per sample, which is essential for the analysis of a large amount of patient samples. This expedient method will be of considerable utility for studies into the exposure-response relationships of these breakthrough CF drugs.

Ivacaftor and ivacaftor-lumacaftor combination are two new CF drugs. However, there is still a dearth of understanding on their PK/PD and pharmacology. We present an optimized HPLC-MS technique for the simultaneous analysis of ivacaftor and its major metabolites, and lumacaftor.

Defects in the cystic fibrosis trans-membrane conductance regulator (CFTR) are the cause of cystic fibrosis (CF), a disease with life-threatening ...

Improved Method for the Establishment of an In Vitro Blood-Brain Barrier Model Based on Porcine Brain Endothelial Cells

The aim of this protocol presents an optimized procedure for the purification and cultivation of pBECs and to establish in vitro blood-brain barrier (BBB) models based on pBECs in mono-culture (MC), MC with astrocyte-conditioned medium (ACM), and non-contact co-culture (NCC) with astrocytes of porcine or rat origin. pBECs were isolated and cultured from fragments of capillaries from the brain cortices of domestic pigs 5-6 months old. These fragments were purified by careful removal of meninges, isolation and homogenization of grey matter, filtration, enzymatic digestion, and centrifugation. To further eliminate contaminating cells, the capillary fragments were cultured with puromycin-containing medium. When 60-95% confluent, pBECs growing from the capillary fragments were passaged to permeable membrane filter inserts and established in the models. To increase barrier tightness and BBB characteristic phenotype of pBECs, the cells were treated with the following differentiation factors: membrane permeant 8-CPT-cAMP (here abbreviated cAMP), hydrocortisone, and a phosphodiesterase inhibitor, RO-20-1724 (RO). The procedure was carried out over a period of 9-11 days, and when establishing the NCC model, the astrocytes were cultured 2-8 weeks in advance. Adherence to the described procedures in the protocol has allowed the establishment of endothelial layers with highly restricted paracellular permeability, with the NCC model showing an average transendothelial electrical resistance (TEER) of 1249 &#177; 80 &#937; cm2, and paracellular permeability (Papp) for Lucifer Yellow of 0.90 10-6 &#177; 0.13 10-6 cm sec-1 (mean &#177; SEM, n=55). Further evaluation of this pBEC phenotype showed good expression of the tight junctional proteins claudin 5, ZO-1, occludin and adherens junction protein p120 catenin. The model presented can be used for a range of studies of the BBB in health and disease and, with the highly restrictive paracellular permeability, this model is suitable for studies of transport and intracellular trafficking.

Improved Method for the Establishment of an In Vitro Blood-Brain Barrier Model Based on Porcine Brain Endothelial Cells

The aim of the protocol is to present an optimized procedure for the establishment of an in vitro blood-brain barrier (BBB) model based on primary porcine brain endothelial cells (pBECs). The model shows high reproducibility, high tightness, and is suitable for studies of transport and intracellular trafficking in drug discovery.

The aim of this protocol presents an optimized procedure for the purification and cultivation of pBECs and to establish in vitro blood-brain barrier (BBB) ...

Isolation of Primary Human Decidual Cells from the Fetal Membranes of Term Placentae

The decidua, also known as the pregnant endometrium, is a critically important reproductive tissue. Decidual cells, comprised mainly of decidualized stromal cells and immune cells, are responsible for the secretion of hormonal and inflammatory factors which are critical for successful blastocyst implantation, placental development and play a role in the initiation of labor at term and preterm. Many pregnancy complications can arise from perturbations of a fine balance of different cell populations comprising decidua. Alterations in the proportion of specific decidual cell types may disrupt these crucial processes and increase the risk of developing serious complications of pregnancy, such as embryo implantation failure, intrauterine growth restriction, preeclampsia and preterm labor. The protocol outlined here demonstrates a cost and time effective method for the isolation of primary human decidual cells collected from the fetal membranes of term placentae. By combining enzymatic digestion and gentle mechanical disruption of the decidual tissue, a high yield of decidual cells was obtained with virtually no chorion contamination. Importantly, isolated decidual cells were characterized (stromal cells (55-60%), leukocytes (35%), epithelial (1%) or trophoblast (0.01%) cells) and maintained high viability (80%) which was confirmed by multicolor imaging flow cytometry assay. This protocol is specific to the decidua parietalis and can be adapted to first and second trimester placentae. Once isolated, decidual cells can be used for a multitude of experimental applications aiming to understand the role of different decidual cell sub-populations in pregnancy complications.

This protocol demonstrates a method for the isolation of primary human decidual cells collected from the fetal membranes of term placentae which can be used for a variety of applications (i.e. immunocytochemistry, flow cytometry, etc.) aiming to study the role of different cell populations in pregnancy complications.

The decidua, also known as the pregnant endometrium, is a critically important reproductive tissue. Decidual cells, comprised mainly of decidualized ...

High-Throughput Analysis of Optical Mapping Data Using ElectroMap

Optical mapping is an established technique for high spatio-temporal resolution study of cardiac electrophysiology in multi-cellular preparations. Here we present, in a step-by-step guide, the use of ElectroMap for analysis, quantification, and mapping of high-resolution voltage and calcium datasets acquired by optical mapping. ElectroMap analysis options cover a wide variety of key electrophysiological parameters, and the graphical user interface allows straightforward modification of pre-processing and parameter definitions, making ElectroMap applicable to a wide range of experimental models. We show how built-in pacing frequency detection and signal segmentation allows high-throughput analysis of entire experimental recordings, acute responses, and single beat-to-beat variability. Additionally, ElectroMap incorporates automated multi-beat averaging to improve signal quality of noisy datasets, and here we demonstrate how this feature can help elucidate electrophysiological changes that might otherwise go undetected when using single beat analysis. Custom modules are included within the software for detailed investigation of conduction, single file analysis, and alternans, as demonstrated here. This software platform can be used to enable and accelerate the processing, analysis, and mapping of complex cardiac electrophysiology.

This protocol describes the setup and use of ElectroMap, a MATLAB-based open-source software platform for analysis of cardiac optical mapping data. ElectroMap provides a versatile high-throughput tool for analysis of optical mapping voltage and calcium datasets across a wide range of cardiac experimental models.

Optical mapping is an established technique for high spatio-temporal resolution study of cardiac electrophysiology in multi-cellular preparations. Here we ...

A High-Throughput Electrochemiluminescence 7-Plex Assay Simultaneously Screening for Type 1 Diabetes and Multiple Autoimmune Diseases

Islet autoantibodies (IAbs) are widely used in type 1 diabetes (T1D) diagnosis and prediction. Four major IAbs to insulin (IAA), glutamate decarboxylase-65 (GADA), insulinoma antigen-2 (IA-2A), and zinc transporter-8 (ZnT8A) are equally important in disease prediction. Presently, up to 40% of patients diagnosed with T1D go on to develop other autoimmune disorders. Unfortunately, current screening methods using a single autoantibody for measurement are laborious and inefficient for large scale screening studies. We recently developed a simple multiplexed electrochemiluminescence (ECL) assay to address these current issues. The assay combines all 7 autoantibody tests into one well. Each well includes three IAbs (IAA, GADA, and IA-2A), autoantibodies to thyroid peroxidase (TPOA) and thyroid globulin (ThGA) to detect autoimmune thyroid disease, autoantibodies to tissue transglutaminase (TGA) for celiac disease, and autoantibodies to interferon alpha (IFN&#945;A) for autoimmune polyglandular syndrome-1 (APS-1); all of which screen for T1D and other relevant autoimmune diseases, simultaneously. The multiplex ECL assay is based on the single ECL assay platform, but instead uses the multiplex plate combining multiple autoantibody assays, up to 10, into a single well. The main difference from the single ECL assay is that each antibody-antigen complex formed in the fluid-phase is restrained onto a specific spot on each well through a linker system on the multiplex plate. The 7-Plex ECL assay, in the present study, is validated against standard radio-binding assays (RBA) and single ECL assays, using a large cohort of newly diagnosed T1D patients and age-matched healthy controls, resulting in excellent assay sensitivity and specificity.

We model a simple multiplexed ECL assay that combines 7 autoantibody assays together. The assay is capable of screening for T1D and multiple other autoimmune diseases, simultaneously, including celiac disease, autoimmune thyroid disease, and autoimmune polyglandular syndrome 1.

Islet autoantibodies (IAbs) are widely used in type 1 diabetes (T1D) diagnosis and prediction. Four major IAbs to insulin (IAA), glutamate ...

Characterization of a Novel Human Organotypic Retinal Culture Technique

Previous human organotypic retinal culture (HORC) models have utilized detached retinas; however, without the structural support conferred by retinal pigment epithelium-choroid (RPE-choroid) and sclera, the integrity of the fragile retina can easily be compromised. The aim of this study was to develop a novel HORC model that contains the retina, RPE-choroid and sclera to maintain retinal integrity when culturing retinal explants.
After cutting circumferentially along the limbus to remove iris and lens, four deep incisions were made to flatten the eyecup. In contrast to previous HORC protocols, a trephine was used to cut through not only the retina but also the RPE-choroid and sclera. The resultant triple-layered explants were cultured for 72 h. Hematoxylin and Eosin staining (H&#38;E) was used to assess anatomical structures and retinal explants were further characterized by immunohistochemistry (IHC) for apoptosis, M&#252;ller cell integrity and retinal inflammation. To confirm the possibility of disease induction, explants were exposed to high glucose (HG) and pro-inflammatory cytokines (Cyt), to mimic diabetic retinopathy (DR). The Luminex magnetic bead assay was used to measure DR-related cytokines released into the culture medium.
H&#38;E staining revealed distinct retinal lamellae and compact nuclei in retinal explants with the underlying RPE-choroid and sclera, while retinas without the underlying structures exhibited reduced thickness and severe nuclei loss. IHC results indicated absence of apoptosis and retinal inflammation as well as preserved M&#252;ller cell integrity. The Luminex&#160;assays showed significantly increased secretion of DR-associated pro-inflammatory cytokines in retinal explants exposed to HG + Cyt relative to baseline levels at 24 h.
We successfully developed and characterized a novel HORC protocol in which retinal integrity was preserved without apoptosis or retinal inflammation. Moreover, the induced secretion of DR-associated pro-inflammatory biomarkers when exposing retinal explants to HG + Cyt suggests that this model could be used for clinically translatable retinal disease studies.

This study aims to develop a novel human organotypic retinal culture (HORC) model that prevents compromising retinal integrity during explant handling. This is achieved by culturing the retina with the overlying vitreous and the underlying retinal pigment&#160;epithelium-choroid (RPE-choroid) and sclera.

Previous human organotypic retinal culture (HORC) models have utilized detached retinas; however, without the structural support conferred by retinal ...