Name: an organotypic high throughput system for characterization of drug sensitivity of primary multiple myeloma cells
Uploaded: 2015-07-15T15:00:00
Description: Watch this Scientific Journal Video about An Organotypic High Throughput System for Characterization of Drug Sensitivity of Primary Multiple Myeloma Cells at JoVE.com

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 m...

<ol>
	<li>Salmon, S. E., 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=Quantitation+of+differential+sensitivity+of+human-tumor+stem+cells+to+anticancer+drugs.">Quantitation of differential sensitivity of human-tumor stem cells to anticancer drugs.</a> N Engl J Med. 298, 1321-1327 (1978).</li><li>Suggitt, M., Bibby, M. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=50+years+of+preclinical+anticancer+drug+screening:+empirical+to+target-driven+approaches.">50 years of preclinical anticancer drug screening: empirical to target-driven approaches.</a> Clin Cancer Res. 11, 971-981 (2005).</li><li>Kirshner, J., 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=A+unique+three-dimensional+model+for+evaluating+the+impact+of+therapy+on+multiple+myeloma.">A unique three-dimensional model for evaluating the impact of therapy on multiple myeloma.</a> Blood. 112, 2935-2945 (2008).</li><li>Durie, B. 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. P., 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=A+preclinical+assay+for+chemosensitivity+in+multiple+myeloma.">A preclinical assay for chemosensitivity in multiple myeloma.</a> Cancer Res. 74, 56-67 (2014).</li><li>Misund, 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=A+method+for+measurement+of+drug+sensitivity+of+myeloma+cells+co-cultured+with+bone+marrow+stromal+cells.">A method for measurement of drug sensitivity of myeloma cells co-cultured with bone marrow stromal cells.</a> J Biomol Screen. 18, 637-646 (2013).</li><li>Ramasamy, 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=Fluorescence-based+experimental+model+to+evaluate+the+concomitant+effect+of+drugs+on+the+tumour+microenvironment+and+cancer+cells.">Fluorescence-based experimental model to evaluate the concomitant effect of drugs on the tumour microenvironment and cancer cells.</a> Br J Haematol. 157, 564-579 (2012).</li><li>McMillin, D. 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=Tumor+cell-specific+bioluminescence+platform+to+identify+stroma-induced+changes+to+anticancer+drug+activity.">Tumor cell-specific bioluminescence platform to identify stroma-induced changes to anticancer drug activity.</a> Nat Med. 16, 483-489 (2010).</li><li>Koh, C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Preparation+of+cells+for+microscopy+using+cytospin.">Preparation of cells for microscopy using cytospin.</a> Methods Enzymol. 533, 235-240 (2013).</li><li>Al-Quran, S. Z., Yang, L., Magill, J. M., Braylan, R. C., Douglas-Nikitin, V. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Assessment+of+bone+marrow+plasma+cell+infiltrates+in+multiple+myeloma:+the+added+value+of+CD138+immunohistochemistry.">Assessment of bone marrow plasma cell infiltrates in multiple myeloma: the added value of CD138 immunohistochemistry.</a> Hum Pathol. 38, 1779-1787 (2007).</li><li>Najar, 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=Mesenchymal+stromal+cells+promote+or+suppress+the+proliferation+of+T+lymphocytes+from+cord+blood+and+peripheral+blood:+the+importance+of+low+cell+ratio+and+role+of+interleukin-6.">Mesenchymal stromal cells promote or suppress the proliferation of T lymphocytes from cord blood and peripheral blood: the importance of low cell ratio and role of interleukin-6.</a> Cytotherapy. 11, 570-583 (2009).</li><li>Scott, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phase+i+trialist.">Phase i trialist.</a> Lancet Oncol. 13, 236 (2012).</li></ol>

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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