Grant support: Fondation de Projet de L&#39;Universit&#233; de Nantes, les Bagouz&#39; &#224; Manon, La Ligue contre le Cancer comit&#233; de Loire-Atlantique, comit&#233; du Morbihan, and comit&#233; de Vend&#233;e, une rose pour S.A.R.A.H, L&#39;Etoile de Martin and la Soci&#233;t&#233; Fran&#231;aise de Lutte contre les Cancers et les leuc&#233;mies de L&#39;Enfant et de L&#39;adolescent (SFCE).&#160;M.B. and J.F. are supported by La Ligue Contre Le Cancer. The authors thank the UTE-facility of the Structure F&#233;d&#233;rative de Recherche Fran&#231;ois Bonamy. The authors also thank Dr. S. Suzin (Inserm, Paris) for providing the IMR5 cells and Ms. H. Est&#233;phan for her technical assistance.

Animal housing and experimental procedure were approved by the French Government (agreements #C44-278 and #APAFIS 03479.01). Animal care and procedures were conducted under directive EU 2010/63/EU and French Law #2013-118 on the protection of animals used for scientific purposes.
1. Evaluation of the Drug Interaction Between mAb 8B6 and Topotecan In Vitro
<ol>
	<li>96-well sample preparation 
	CAUTION: Consult the institution&#39;s Health and Safety committee and follow local regulation rules related to laboratory safety. Review the Material and Safety Data Sheet information before working with any media, cell lines, or reagents. Use proper sterile technique and work in a laminar flow hood. All solutions/equipment that are used to manipulate cells must be sterile. 
	NOTE: The following protocol was designed for use with adherent cells. Modifications are required to apply the method to nonadherent cells growing in suspension; this protocol uses quadruplicate for each experimental condition.
	<ol>
		<li>Grow IMR5 cells in a T75 flask.</li>
		<li>On the first day (day 0), observe the cell culture under a microscope to check the cell confluency. Aspirate the cell medium from the flask, wash it with 5 mL of phosphate-buffered saline (PBS), and add 3 mL of 0.05% ethylenediaminetetraacetic acid (EDTA)/PBS solution. Return the flask to the incubator for 3 min (37 &#176;C, 5% CO2).</li>
		<li>Examine the cell culture under a microscope for cell detachment. 
		NOTE: If necessary, return the flask to the incubator for an additional 3 to 5 min, depending on tumor cell type.</li>
		<li>Add 10 mL of complete cell medium to the flask and transfer the cell suspension to a sterile 15 mL conical tube. Centrifuge the cells for 5 min at 300 x g. Count the cells using a hemocytometer.</li>
		<li>Remove and discard the supernatant. Resuspend the cell pellet in complete growth medium. Adjust the medium volume to obtain a final concentration of 1 x 105 cells/mL.</li>
		<li>Seed 84 wells of a 96-well culture plate with 104 cells each, which is 100 &#181;L of cell suspension. Follow the experimental layout shown in Figure 2.</li>
		<li>Incubate the cells for 18 h in the cell incubator (37 &#176;C, 5% CO2).</li>
	</ol>
	</li>
	<li>Drug solution preparation 
	NOTE: For drug/mAb sensitization studies, modify the timing, the length, and the concentration treatment to suit the particular drug/mAb in question. Note that the initial concentration is 3x the final concentration.
	<ol>
		<li>The next morning (day 1), prepare the following drug solutions using complete growth medium.
		<ol>
			<li>mAb solution preparation
			<ol>
				<li>Dilute mAb in 500 &#181;L of complete growth medium to obtain an antibody working solution with an mAb concentration of 240 &#181;g/mL.</li>
				<li>Perform five two-fold serial dilutions as indicated in Figure 2.</li>
			</ol>
			</li>
			<li>Topotecan solution preparation
			<ol>
				<li>Dilute, as above, the drug in 500 &#181;L of complete growth medium to obtain a drug working solution with a final concentration of 120 nM.</li>
				<li>Perform five two-fold serial dilutions as indicated in Figure 2.</li>
			</ol>
			</li>
			<li>Antibody and drug solution preparation
			<ol>
				<li>Dilute the drug and mAb solutions in 500 &#181;L of complete growth medium to obtain a solution at 120 nM drug and 240 &#181;g/mL mAb (working solution).</li>
				<li>Perform five two-fold serial dilutions as indicated in Figure 2.</li>
			</ol>
			</li>
		</ol>
		</li>
		<li>To arrive at the final concentration, transfer 50 &#181;L of each drug solution into the corresponding wells, as indicated in the experimental layout ( Figure 2). 
		NOTE: Transfer 50 &#181;L of complete growth medium into the untreated cell wells, as indicated in Figure 2.</li>
		<li>Incubate the cells for 72 h in the incubator (37 &#176;C, 5% CO2).</li>
	</ol>
	</li>
	<li>MTT assay
	<ol>
		<li>Add 10 &#181;L of MTT reagent solution into each well.</li>
		<li>Incubate at 37 &#176;C for 4 h.</li>
		<li>Add 100 &#181;L of lysis solution (10% SDS in 0.01 M HCl) into each well, using a multichannel pipette, and mix thoroughly by pipetting.</li>
		<li>Incubate at 37 &#176;C for 4 h in a humidified chamber (95% humidity).</li>
		<li>Read the absorbance at 570 nm (A570) and 620 nm (A620) using a spectrophotometer. 
		NOTE: Mix each sample again by pipetting before reading the absorbance; absorbance at 620 nm allows the correction of nonspecific background values.</li>
		<li>Calculate the corrected absorbance: corrected absorbance = A570- A620.</li>
		<li>Calculate the cell viability as follows: cell viability = 100 x (sample mean corrected absorbance / control mean corrected absorbance).</li>
		<li>Calculate the fraction-affected values (Fa) using the following equation: 1 - (sample mean corrected absorbance / control mean corrected absorbance).</li>
	</ol>
	</li>
	<li>Drug interaction analytical simulation software for single and drug combination studies
	<ol>
		<li>Run the simulation software to open the start window.</li>
		<li>Click on the New Experiment button to open the Main window.</li>
		<li>Type the name of the experiment in the Name window. 
		NOTE: A date can be added in the Date window.</li>
		<li>Click on the New Single Drug button.</li>
		<li>Type the name in the Full Name window.</li>
		<li>Type the abbreviation in the Abbrev window.</li>
		<li>Type the drug concentration unit in the Units window.</li>
		<li>Enter Data Point 1 Dose and Fa value, press Enter.</li>
		<li>Repeat this step until all Data Points are entered.</li>
		<li>Click on the Finished button.</li>
		<li>Follow the same steps to enter mAb Data Points. 
		NOTE: Use the same concentration unit as is used by Drug.</li>
		<li>Click on the New Drug Combo button.</li>
		<li>Select Drug and mAb.</li>
		<li>Select Constant Ratio and click on OK.</li>
		<li>Type the name in the Full Name window.</li>
		<li>Type the abbreviation in the Abbrev window.</li>
		<li>Type the drug/mAb ratio in the Ratio of window.</li>
		<li>Enter Data Point 1 Dose and press Enter. 
		NOTE: The program will automatically calculate the doses of mAb and Combo.</li>
		<li>Enter the Data Point 1 Fa value and press Enter.</li>
		<li>Repeat this step until all Data Points are entered.</li>
		<li>Click on the Finished button and, then, click on the Generate Report button.</li>
		<li>Select drug and mAb and, then, click OK.</li>
		<li>Select Combo and, then, click OK.</li>
		<li>Select Header, CI table, and Summary table. Then, click OK.</li>
		<li>Type the file name of the analysis file and click SAVE to generate the report. 
		NOTE: After clicking OK, the report will automatically open in the computer&#39;s default web browser.</li>
		<li>To print the report, choose Print from the web browser&#39;s file menu. The report contains a Summary Table Section that includes title, date, file name, description note, parameters (m, Dm, and r), ED50 for either agent used in monotherapy or in combination, and the CI table for each combination at ED50, ED75, ED90, and ED95. 
		NOTE: A CI value of &#60;1 indicates synergism, a CI value of =1 indicates additivity, and a CI value of &#62;1 indicates antagonism.</li>
	</ol>
	</li>
</ol>
2. Generation of Human Neuroblastoma Xenografts in Nonobese Diabetic NOD Scid Gamma Mice (NSG Mice)
NOTE: Exclude any contamination of the cell culture. Since the basement membrane matrix forms a gel above 5 &#176;C, all cultureware or media coming in contact with the basement membrane matrix reagent should be prechilled/ice-cold. Keep the basement membrane matrix on ice during the entire process.
<ol>
	<li>Preparation of the IMR5 cell suspension
	<ol>
		<li>Thaw the basement membrane matrix reagent&#160;overnight by submerging the vial in ice in a 4 &#176;C refrigerator before use.</li>
		<li>On day 0, harvest the cultured IMR5 cells as detailed above.</li>
		<li>Transfer the cells to a 15 mL conical tube and centrifuge at 300 x g for 5 min.</li>
		<li>Discard the supernatant. Wash the cells 2x with 15 mL of ice-cold PBS, and prepare a cell suspension of 5 x 107 cells/mL in ice-cold PBS. 
		NOTE: If necessary, transfer the cell suspension to a 1.5 mL microcentrifuge tube.</li>
		<li>Swirl the basement membrane matrix vial. 
		NOTE: The basement membrane matrix reagent should be thawed and dispersed.</li>
		<li>Add one volume of basement membrane matrix reagent and mix it by pipetting to obtain a cell suspension of 2.5 x 107 cells /mL.</li>
		<li>Keep the cell suspension on ice.</li>
	</ol>
	</li>
	<li>Preparation of the mice 
	NOTE: The mice should be six to seven weeks old.
	<ol>
		<li>Maintain mice under a specific pathogen-free condition.</li>
		<li>Allow a three- to five-day acclimatization period after the mice have arrived.</li>
		<li>On the day of inoculation, shave the flank where the injection will be done (see step 2.3.6).</li>
	</ol>
	</li>
	<li>Preparation of the tumor cell injection 
	NOTE: Keep the ice-cold basement membrane matrix cell suspension aseptic throughout the procedure.
	<ol>
		<li>Mix the cells and carefully draw the cell suspension into a 1 mL syringe mounted with a 21 G needle.</li>
		<li>Check to be sure that there are no air bubbles in the syringe.</li>
		<li>Disinfect the inoculation area of the mouse with an antiseptic solution.</li>
		<li>Gently squeeze the mouse&#39;s skin on the flank between fingers, at the injection site.</li>
		<li>Insert the needle exactly into the skin fold. Do not place the needle deep into the tissue to ensure a subcutaneous injection.</li>
		<li>Inject 100 &#181;L of IMR5 cell suspension (i.e., 2.5 x 106 cells) subcutaneously into the lower right flank of the mice.</li>
		<li>Rotate the syringe to prevent leakage and withdraw the needle.</li>
	</ol>
	</li>
	<li>Monitoring of body weight changes and tumor growth
	<ol>
		<li>Measure the length (A) and the width (B) of the tumor with a caliper.</li>
		<li>Calculate the tumor volume using the formula (A x B2) x 0.5.</li>
		<li>Start therapy when the tumors have reached an average volume of ~50 - 60 mm3.</li>
	</ol>
	</li>
</ol>
3. Drug and Antibody Administration in Mice
<ol>
	<li>Intravenous administration of mAb 8B6
	<ol>
		<li>Carefully fill a 1 mL syringe mounted with a 25 G needle with mAb solution.</li>
		<li>Place the mouse under a heat lamp for 10 min to dilate the tail vein.</li>
		<li>Restrain the mouse in a rodent restrainer.</li>
		<li>Disinfect the inoculation area of the mouse with an antiseptic solution.</li>
		<li>Insert the needle parallel to the tail vein, penetrating 2 - 4 mm into the lumen while keeping the bevel of the needle face upward (Figure 3A).</li>
		<li>Inject 100 &#181;L of antibody solution intravenously (i.v.).</li>
		<li>When the injection is finished, gently pressure the injection site to prevent bleeding.</li>
	</ol>
	</li>
	<li>Intraperitoneal administration of topotecan
	<ol>
		<li>Draw the drug solution in a 1 mL syringe mounted with a 25 G needle.</li>
		<li>Hold the mouse in a supine position, with its posterior end slightly elevated.</li>
		<li>Disinfect the inoculation area of the mouse with an antiseptic solution.</li>
		<li>Locate the mouse&#39;s abdomen midline and mentally divide the abdomen into quadrants. Locate the injection site in the right or left lower quadrant (Figure 3B).</li>
		<li>Insert the needle into the abdomen (5 mm deep) at ~10&#176; angle, in the right or left lower quadrant.</li>
		<li>Inject 100 &#181;L of drug solution intraperitoneally (i.p.).</li>
		<li>Disinfect the inoculation site.</li>
	</ol>
	</li>
</ol>

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B., Jacob, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+simple+practice+guide+for+dose+conversion+between+animals+and+human.">A simple practice guide for dose conversion between animals and human.</a> Journal of Basic Clinical Pharmacy. 7 (2), 27-31 (2016).</li><li>Dayde, D., 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+burden+influences+exposure+and+response+to+rituximab:+pharmacokinetic-pharmacodynamic+modeling+using+a+syngeneic+bioluminescent+murine+model+expressing+human+CD20.">Tumor burden influences exposure and response to rituximab: pharmacokinetic-pharmacodynamic modeling using a syngeneic bioluminescent murine model expressing human CD20.</a> Blood. 113 (16), 3765-3772 (2009).</li><li>Racki, W. 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=NOD-scid+IL2rgamma(null)+mouse+model+of+human+skin+transplantation+and+allograft+rejection.">NOD-scid IL2rgamma(null) mouse model of human skin transplantation and allograft rejection.</a> Transplantation. 89 (5), 527-536 (2010).</li><li>Sherif, A., Winerdal, M., Winqvist, O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Immune+Responses+to+Neoadjuvant+Chemotherapy+in+Muscle+Invasive+Bladder+Cancer.">Immune Responses to Neoadjuvant Chemotherapy in Muscle Invasive Bladder Cancer.</a> Bladder Cancer. 4 (1), 1-7 (2018).</li></ol>

S.Fa., J.F., and S.B. are designated as inventors of pending patents covering the clinical application of anti-O-acetyl-GD2 therapeutic antibodies.

To predict the effect of drug interactions, three methods can be used: the isobologram methodology17, the nonlinear mixture model18, and the combination index1. Combination index analysis is the most commonly used because its application is simplified by the availability of a user-friendly computer program. For this purpose, we first characterized the dose-effect response of each agent used alone or in combination, by performing an MTT assay<sup clas...

The conventional approach in the treatment of a large number of different types of cancer was based on monotherapy. Even if it is still used in many cases, this method met several obstacles leading to opting for combined therapies2. Particularly, cancer cells are more susceptible to develop resistance when treated with a single drug by inducing alternative survival mechanisms3, resulting in therapeutic failure in patients4. Moreover, in monotherapy, drugs are usually administrated at a high dose. This situation often results in the occurrence of strong dose-dependent side effects that can be intolerable and force physicians to stop the treatment2. For these reasons, the association of anticancer molecules is now preferred to monotherapy.
Ideal drug combinations would be those that act in synergy against tumor cells, without increased toxicity against normal cells. Synergism refers to the interaction of two or more drugs that produces a therapeutic effect greater than the sum of each individual drug acting separately. Such interactions may result in enhanced clinical therapeutic efficacy2. It limits treatment resistance, increases efficacy, and can also reduce toxicity2. In fact, the dosage of each drug can be reduced to lower their side effects by targeting different pathways. In addition, one of the molecules can also serve as a sensitizing agent against cancer cells. The effect of the second drug may be enhanced on sensitized cells and fewer dosages can be used5.
Combined therapy can include two or more chemotherapeutic drugs and/or biologics, such as monoclonal antibodies6. These mAbs specifically target cells expressing a cell surface antigen of interest and are able to kill tumor cells through immunological pathways including antibody-dependent cell-mediated cytotoxicity (ADCC), with the involvement of immune effector cells7, and complement-dependent cytotoxicity (CDC)6. They can also act via a non-immunological mechanism mediated by apoptosis8,9,10,11. In this case, the induction of the process of programmed cell death may sensitize cancer cells, weaken their function, and make the associated chemotherapeutic drug more effective at a lower dosage. As such, proapoptotic mAb are good candidates for designing combination regimens with antineoplastic drugs.
Different mathematical models have been described to assess drug synergism; one of them is based on the combination index method1. This method is based on the median-effect principle developed by Chou1. The median-effect equation correlates the drug dose and drug effect as follows.
<img alt="Equation 1" src="/files/ftp_upload/58291/58291eq1.jpg" />
Here, D is the drug dose; Dm is the median-effect dose; Fa is the fraction affected by the dose; m is an exponent that signifies the shape of the dose-effect plot1. The median-effect dose is used to calculate the dose Dx of a drug that inhibits or kills &#34;x&#34; percent of cells. The CI value is then calculated to assess the additive effect of the drug combination, as follows1.
<img alt="Equation 2" src="/files/ftp_upload/58291/58291eq2.jpg" style="font-size: 14px;" />
A CI value of 1 indicates an additive effect and a CI value of &#60;1 indicates a synergistic effect, while a CI value of &#62;1 indicates antagonism1. The application of this method is further facilitated by the availability of a computer program, CompuSyn, that determines synergism and antagonism at all doses or effect levels simulated automatically12.
Our group has developed the mAb 8B6 specific for O-acetyl-GD2 ganglioside (OAcGD2) neuroblastoma antigen13 and further demonstrated that this mAb is able to induce cell death with attributes of apoptosis11. To test whether mAb 8B6 can sensitize neuroblastoma cells to the antineoplastic agent topotecan, we adapted the above-mentioned method developed by Chou1. First, we determine the effective dose 50 (ED50) values of mAb 8B6 and topotecan. Next, the neuroblastoma cells with equipotent ratios of the two compounds based on ED50 values are exposed to determine the CI values using the above-mentioned simulation software. This method allows us to demonstrate synergism between mAb 8B6 and topotecan in vitro. Next, we describe a protocol to further assess the potency and the safety of this combination regimen in vivo. This protocol can be easily applied to select potent and safe anticancer mAb and chemotherapeutic agent combinations in preclinical studies. A schematic representation of this study is provided in Figure 1.

<table><tbody><tr><td>Cell Proliferation kit (MTT)</td><td>Roche</td><td>11-465-007-001</td><td></td></tr><tr><td>CompuSyn software</td><td>ComboSyn</td><td></td><td>Combosyn can be downloaded for free at http://www.combosyn.com</td></tr><tr><td>Electric shaver</td><td>Bioseb</td><td>BIO-1556</td><td></td></tr><tr><td>Fetal calf serum</td><td>Eurobio</td><td>CVFSVFF00-01</td><td>10% heat-inactivated fetal calf serum in RPMI 1640</td></tr><tr><td>Firefox&amp;nbsp;</td><td>Mozilla Corporation</td><td></td><td>Firefox can be downloaded for free at http://www.mozilla.org/en-US/firefox/</td></tr><tr><td>Heat lamp</td><td>Verre&amp;amp;Quartz</td><td>4003/1R</td><td></td></tr><tr><td>Human neuroblastoma IMR-5 cell line</td><td>Accegen Biotechnology</td><td>ABC-TC0450</td><td>IMR-5 is a clone of the human neuroblastoma cell line IMR32 5459762. IMR-5 cells were generously provided by Dr. Santos Susin (U.872, Paris, France)</td></tr><tr><td>L-glutamine</td><td>Gibco</td><td>25030-024</td><td>2 mM in RPMI 1640</td></tr><tr><td>Lysis solution&amp;nbsp;</td><td>Roche&amp;nbsp;</td><td>11-465-007-001</td><td></td></tr><tr><td>mAb 8B6</td><td>University of Nantes</td><td>N/A</td><td></td></tr><tr><td>Matrigel</td><td>Corning</td><td>354248</td><td></td></tr><tr><td>Multiskan FC</td><td>Thermofischer Scientific&amp;nbsp;</td><td>N08625</td><td></td></tr><tr><td>Needle 21G 1 &amp;frac12;&amp;nbsp;</td><td>BD Microlance</td><td>304432</td><td></td></tr><tr><td>Needle 25G 1</td><td>Terumo</td><td>NN-2525R</td><td></td></tr><tr><td>NSG mice</td><td>Charles River Laboratories</td><td>5557</td><td></td></tr><tr><td>Nunc MicroWell 96-well microplates</td><td>Thermofisher</td><td>167008</td><td></td></tr><tr><td>PBS</td><td>VWR</td><td>L182-10</td><td></td></tr><tr><td>PBS, 0,05% EDTA</td><td>Sigma-Aldrich</td><td>E9884</td><td></td></tr><tr><td>PC that runs windows 7</td><td>Microsoft</td><td></td><td>Windows 7 can be purchased at http://www.microsoft.com/en-gb/software-download/windows7</td></tr><tr><td>Penicillin-Streptomycin</td><td>Gibco</td><td>15140-122</td><td>100 units/mL penicillin and 100 mg/mL streptomycin in RPMI 1640</td></tr><tr><td>Reagent reservoir</td><td>Thermofischer Scientific</td><td>8094</td><td></td></tr><tr><td>Rodent restrainer</td><td>Bioseb</td><td>TV-150-SM</td><td></td></tr><tr><td>RPMI 1640</td><td>Gibco</td><td>31870-025</td><td></td></tr><tr><td>Syringe 1 mL</td><td>Henke Sass Wolf</td><td>5010.200V0</td><td></td></tr><tr><td>Topotecan</td><td>Sigma-Aldrich</td><td>T2705</td><td></td></tr></tbody></table>

potentiation of anticancer antibody efficacy by antineoplastic drugs: detection of antibody-drug synergism using the combination index equation

Potentiation of hostile monoclonal antibodies (mAb) by chemotherapeutic agents constitutes a valuable strategy for designing effective and safer therapy against cancer. Here we provide a protocol to identify a rational combination at the preclinical step. First, we describe a cell-based assay to assess the synergism between anticancer mAb and cytotoxic drugs, that uses the combination index equation of Chou and Talalay1. This includes the measurement of tumor cell drug- and antibody-sensitivity using an MTT assay, followed by an automated computer analysis to calculate the combination index (CI) values. CI values of &lt;1 indicate synergism between tested mAbs and cytotoxic agents1. To corroborate the in vitro findings in vivo, we further describe a method to assess the combination regimen efficacy in a xenograft tumor model. In this model, the combined regimen significantly delays tumor growth, which results in a significant extended survival in comparison to single-agent controls. Importantly, the in vivo experimentation reveals that the combination regimen is well tolerated. This protocol allows the effective evaluation of anticancer drug combinations in preclinical models and the identification of rational combination to evaluate in clinical trials.

The representative results and figures are adapted with permission from earlier published work14.
Anti-OAcGD2 mAb 8B6 Synergistically Enhances the Inhibitory Effects of Topotecan on Neuroblastoma Cell Line Growth:
To establish the drug and the antibody concentrations to be used for assessing synergism between topotecan and mAb 8...

Watch this Scientific Journal Video about Potentiation of Anticancer Antibody Efficacy by Antineoplastic Drugs: Detection of Antibody-drug Synergism Using the Combination Index Equation at JoVE.com

Potentiation of Anticancer Antibody Efficacy by Antineoplastic Drugs: Detection of Antibody-drug Synergism Using the Combination Index Equation

This protocol describes how to assess synergism between an anticancer antibody and antineoplastic drugs in preclinical models by using the combination index equation of Chou and Talalay.

Potentiation of hostile monoclonal antibodies (mAb) by chemotherapeutic agents constitutes a valuable strategy for designing effective and safer therapy ...

potentiation-anticancer-antibody-efficacy-antineoplastic-drugs

Research

JoVE Journal

Cancer Research

12.1K Views.  Centre de Recherche en Cancérologie et Immunologie Nantes Angers (CRCINA), Institut national de la santé et de la recherche médicale (INSERM), Université d'Angers, Université de Nantes, Nantes, France. Immunotherapie in combinatie met chemotherapie is een innovatieve aanpak om efficiënte therapie bij kanker te ontwikkelen. De belangrijkste doelstellingen zijn het bereiken van synergetische, therapeutische effecten, dosis- en toxiciteitsreductie, en het minimaliseren of vertragen van de inductie van resistentie tegen geneesmiddelen. Echter, om praktische en ethische redenen, is het niet mogelijk om synergisme bij patiënten te bepalen. Voordat de combinatie in klinische proeven rechtstreeks...

Video: Potentiation of Anticancer Antibody Efficacy by Antineoplastic Drugs: Detection of Antibody-drug Synergism Using the Combination Index Equation

Sample Extraction and Simultaneous Chromatographic Quantitation of Doxorubicin and Mitomycin C Following Drug Combination Delivery in Nanoparticles to Tumor-bearing Mice

Combination chemotherapy is frequently used in the clinic for cancer treatment; however, associated adverse effects to normal tissue may limit its therapeutic benefit. Nanoparticle-based drug combination has been shown to mitigate the problems encountered by free drug combination therapy. Our previous studies have shown that the combination of two anticancer drugs, doxorubicin (DOX) and mitomycin C (MMC), produced a synergistic effect against both murine and human breast cancer cells in vitro. DOX and MMC co-loaded polymer-lipid hybrid nanoparticles (DMPLN) bypassed various efflux transporter pumps that confer multidrug resistance and demonstrated enhanced efficacy in breast tumor models. Compared to conventional solution forms, such superior efficacy of DMPLN was attributed to the synchronized pharmacokinetics of DOX and MMC and increased intracellular drug bioavailability within tumor cells enabled by the nanocarrier PLN. 
To evaluate the pharmacokinetics and bio-distribution of co-administered DOX and MMC in both free solution and nanoparticle forms, a simple and efficient multi-drug analysis method using reverse-phase high performance liquid chromatography (HPLC) was developed. In contrast to previously reported methods that analyzed DOX or MMC individually in the plasma, this new HPLC method is able to simultaneously quantitate DOX, MMC and a major cardio-toxic DOX metabolite, doxorubicinol (DOXol), in various biological matrices (e.g., whole blood, breast tumor, and heart). A dual fluorescent and ultraviolet absorbent probe 4-methylumbelliferone (4-MU) was used as an internal standard (I.S.) for one-step detection of multiple drug analysis with different detection wavelengths. This method was successfully applied to determine the concentrations of DOX and MMC delivered by both nanoparticle and solution approaches in whole blood and various tissues in an orthotopic breast tumor murine model. The analytical method presented is a useful tool for pre-clinical analysis of nanoparticle-based delivery of drug combinations.

This protocol describes an efficient and convenient analytical process of sample extraction and simultaneous determination of multiple drugs, doxorubicin (DOX), mitomycin C (MMC) and a cardio-toxic DOX metabolite, doxorubicinol (DOXol), in the biological samples from a preclinical breast tumor model treated with nanoparticle formulations of synergistic drug combination.

Combination chemotherapy is frequently used in the clinic for cancer treatment; however, associated adverse effects to normal tissue may limit its ...

High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method

Although antimicrobial drugs have dramatically increased the lifespan and quality of life in the 20th century, antimicrobial resistance threatens our entire society's ability to treat systemic infections. In the United States alone, antibiotic-resistant infections kill approximately 23,000 people a year and cost around 20 billion USD in additional healthcare. One approach to combat antimicrobial resistance is combination therapy, which is particularly useful in the critical early stage of infection, before the infecting organism and its drug resistance profile have been identified. Many antimicrobial treatments use combination therapies. However, most of these combinations are additive, meaning that the combined efficacy is the same as the sum of the individual antibiotic efficacy. Some combination therapies are synergistic: the combined efficacy is much greater than additive. Synergistic combinations are particularly useful because they can inhibit the growth of antimicrobial drug resistant strains. However, these combinations are rare and difficult to identify. This is due to the sheer number of molecules needed to be tested in a pairwise manner: a library of 1,000 molecules has 1 million potential combinations. Thus, efforts have been made to predict molecules for synergy. This article describes our high-throughput method for predicting synergistic small molecule pairs known as the Overlap2 Method (O2M). O2M uses patterns from chemical-genetic datasets to identify mutants that are hypersensitive to each molecule in a synergistic pair but not to other molecules. The Brown lab exploits this growth difference by performing a high-throughput screen for molecules that inhibit the growth of mutant but not wild-type cells. The lab's work previously identified molecules that synergize with the antibiotic trimethoprim and the antifungal drug fluconazole using this strategy. Here, the authors present a method to screen for novel synergistic combinations, which can be altered for multiple microorganisms.

High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method

Synergistic drug combinations are difficult and time-consuming to identify empirically. Here, we describe a method for identifying and validating synergistic small molecules.

Although antimicrobial drugs have dramatically increased the lifespan and quality of life in the 20th century, antimicrobial resistance threatens our ...

Genetics

In Vivo Immunofluorescence Localization for Assessment of Therapeutic and Diagnostic Antibody Biodistribution in Cancer Research

Monoclonal antibodies (mAbs) are important tools in cancer detection, diagnosis, and treatment. They are used to unravel the role of proteins in tumorigenesis, can be directed to cancer biomarkers enabling tumor detection and characterization, and can be used for cancer therapy as mAbs or antibody-drug conjugates to activate immune effector cells, to inhibit signaling pathways, or directly kill cells carrying the specific antigen. Despite clinical advancements in the development and production of novel and highly specific mAbs, diagnostic and therapeutic applications can be impaired by the complexity and heterogeneity of the tumor microenvironment. Thus, for the development of efficient antibody-based therapies and diagnostics, it is crucial to assess the biodistribution and interaction of the antibody-based conjugate with the living tumor microenvironment. Here, we describe In Vivo Immunofluorescence Localization (IVIL) as a new approach to study interactions of antibody-based therapeutics and diagnostics in the in vivo physiological and pathological conditions. In this technique, a therapeutic or diagnostic antigen-specific antibody is intravenously injected in&#160;vivo and localized ex vivo with a secondary antibody in isolated tumors. IVIL, therefore, reflects the in vivo biodistribution of antibody-based drugs and targeting agents. Two IVIL applications are described assessing the biodistribution and accessibility of antibody-based contrast agents for molecular imaging of breast cancer. This protocol will allow future users to adapt the IVIL method for their own antibody-based research applications.

The in vivo immunofluorescence localization (IVIL) method can be used to examine in vivo biodistribution of antibodies and antibody conjugates for oncological purposes in living organisms using a combination of in vivo tumor targeting and ex vivo immunostaining methods.

Monoclonal antibodies (mAbs) are important tools in cancer detection, diagnosis, and treatment. They are used to unravel the role of proteins in ...

Analyzing Tumor and Tissue Distribution of Target Antigen Specific Therapeutic Antibody

Monoclonal antibodies are high affinity multifunctional drugs that work by variable independent mechanisms to eliminate cancer cells. Over the last few decades, the field of antibody-drug conjugates, bispecific antibodies, chimeric antigen receptors (CAR) and cancer immunotherapy has emerged as the most promising area of basic and therapeutic investigations. With numerous successful human trials targeting immune checkpoint receptors and CAR-T cells in leukemia and melanoma at a breakthrough pace, it is highly exciting times for oncologic therapeutics derived from variations of antibody engineering. Regrettably, a significantly large numbers of antibody and CAR based therapeutics have also proven disappointing in human trials of solid cancers because of the limited availability of immune effector cells in the tumor bed. Importantly, nonspecific distribution of therapeutic antibodies in tissues other than tumors also contribute to the lack of clinical efficacy, associated toxicity and clinical failure. As faithful translation of preclinical studies into human clinical trails are highly relied on mice tumor xenograft efficacy and safety studies, here we highlight a method to test the tumor and general tissue distribution of therapeutic antibodies. This is achieved by labeling the protein-A purified antibody with near Infrared fluorescent dye followed by live imaging of tumor bearing mice.

Here we present a protocol to study the in vivo localization of antibodies in mice tumor xenograft models.

Monoclonal antibodies are high affinity multifunctional drugs that work by variable independent mechanisms to eliminate cancer cells. Over the last few ...

High-Content Screening Assay for the Identification of Antibody-Dependent Cellular Cytotoxicity Modifying Compounds

Immunotherapy with antigen-specific antibodies or immune checkpoint inhibitors has revolutionized the therapy of breast cancer. Breast cancer cells expressing the epidermal growth factor receptor HER2 can be targeted by the anti-HER-2 antibody trastuzumab. Antibody-dependent cellular cytotoxicity (ADCC) is an important mechanism implicated in the antitumor action of HER-2. Trastuzumab bound to cancer cells can be recognized by the Fc receptors of ADCC effector cells (e.g., natural killer (NK) cells, macrophages, and granulocytes), triggering the cytotoxic activity of these immune cells leading to cancer cell death. We set out to develop an image-based assay for the quantification of ADCC to identify novel ADCC modulator compounds by high-content screening. In the assay, HER2 overexpressing JIMT-1 breast cancer cells are co-cultured with NK-92 cells in the presence of trastuzumab, and target cell death is quantified by automated microscopy and quantitative image analysis. Target cells are distinguished from effector cells based on their EGFP fluorescence. We show how compound libraries can be tested in the assay to identify ADCC modulator drugs. For this purpose, a compound library test plate was set up using randomly selected fine chemicals off the lab shelf. Three microtubule destabilizing compounds (colchicine, vincristine, podophyllotoxin) expected to interfere with NK cell migration and degranulation were also included in the test library. The test screen identified all three positive control compounds as hits proving the suitability of the method to identify ADCC-modifying drugs in a chemical library. With this assay, compound library screens can be performed to identify ADCC-enhancing compounds that could be used as adjuvant therapeutic agents for the treatment of patients receiving anticancer immunotherapies. In addition, the method can also be used to identify any undesirable ADCC-inhibiting side effects of therapeutic drugs taken by cancer patients for different indications.

This protocol presents an automated, image-based high-throughput technique to identify compounds modulating natural killer cell-mediated breast cancer cell killing in the presence of a therapeutic anti-HER-2 antibody.

Immunotherapy with antigen-specific antibodies or immune checkpoint inhibitors has revolutionized the therapy of breast cancer. Breast cancer cells ...

Quantifying Antibody-Dependent Cellular Cytotoxicity in a Tumor Spheroid Model: Application for Drug Discovery

Monoclonal antibody-based immunotherapy targeting tumor antigens is now a mainstay of cancer treatment. One of the clinically relevant mechanisms of action of the antibodies is antibody-dependent cellular cytotoxicity (ADCC), where the antibody binds to the cancer cells and engages the cellular component of the immune system, e.g., natural killer (NK) cells, to kill the tumor cells. The effectiveness of these therapies could be improved by identifying adjuvant compounds that increase the sensitivity of the cancer cells or the potency of the immune cells. In addition, undiscovered drug interactions in cancer patients co-medicated for previous conditions or cancer-associated symptoms may determine the success of the antibody therapy; therefore, such unwanted drug interactions need to be eliminated. With these goals in mind, we created a cancer ADCC model and describe here a simple protocol to find ADCC-modulating drugs. Since 3D models such as cancer cell spheroids are superior to 2D cultures in predicting in vivo responses of tumors to anticancer therapies, spheroid co-cultures of EGFP-expressing HER2+ JIMT-1 breast cancer cells and the NK92.CD16 cell lines were set up and induced with Trastuzumab, a monoclonal antibody clinically approved against HER2-positive breast cancer. JIMT-1 spheroids were allowed to form in cell-repellent U-bottom 96-well plates. On day 3, NK cells and Trastuzumab were added. The spheroids were then stained with Annexin V-Alexa 647 to measure apoptotic cell death, which was quantitated in the peripheral zone of the spheroids with an automated microscope. The applicability of our assay to identify ADCC-modulating molecules is demonstrated by showing that Sunitinib, a receptor tyrosine kinase inhibitor approved by the FDA against metastatic cancer, almost completely abolishes ADCC. The generation of the spheroids and image acquisition and analysis pipelines are compatible with high-throughput screening for ADCC-modulating compounds in cancer cell spheroids.

Here, we present a method to identify compounds that modulate the ADCC mechanism, an important cancer cell-killing mechanism of antitumor antibodies. The cytotoxic effect of NK cells is measured in breast cancer cell spheroids in the presence of Trastuzumab. Image analysis identifies live and dead killer and target cells in spheroids.

Monoclonal antibody-based immunotherapy targeting tumor antigens is now a mainstay of cancer treatment. One of the clinically relevant mechanisms of ...

Evaluating the Effectiveness of Cancer Drug Sensitization In Vitro and In Vivo

Due to the high level of heterogeneity and mutations inherent in human cancers, single agent therapies, or combination regimens which target the same pathway, are likely to fail. Emphasis must be placed upon the inhibition of pathways that are responsible for intrinsic and/or adaptive resistance to therapy. An active field of investigation is the development and testing of DNA repair inhibitors that promote the action of, and prevent resistance to, commonly used chemotherapy and radiotherapy. We used a novel protocol to evaluate the effectiveness of BRCA2 inhibition as a means to sensitize tumor cells to the DNA damaging drug cisplatin. Tumor cell metabolism (acidification and respiration) was monitored in real-time for a period of 72 hr to delineate treatment effectiveness on a minute by minute basis. In combination, we performed an assessment of metastatic frequency using a chicken embryo chorioallantoic membrane (CAM) model of extravasation and invasion. This protocol addresses some of the weaknesses of commonly used in vitro and in vivo methods to evaluate novel cancer therapy regimens. It can be used in addition to common methods such as cell proliferation assays, cell death assays, and in vivo murine xenograft studies, to more closely discriminate amongst candidate targets and agents, and select only the most promising candidates for further development.

Evaluating the Effectiveness of Cancer Drug Sensitization In Vitro and In Vivo

Here, real-time monitoring of tumor cell metabolism, combined with an in vivo chicken embryo chorio-allantoic membrane (CAM) model of metastasis, are used to evaluate novel anti-cancer targets/agents for their ability to sensitize tumor cells to DNA damaging chemotherapeutics.

Due to the high level of heterogeneity and mutations inherent in human cancers, single agent therapies, or combination regimens which target the same ...

Medicine

High Throughput, Real-time, Dual-readout Testing of Intracellular Antimicrobial Activity and Eukaryotic Cell Cytotoxicity

Traditional measures of intracellular antimicrobial activity and eukaryotic cell cytotoxicity rely on endpoint assays. Such endpoint assays require several additional experimental steps prior to readout, such as cell lysis, colony forming unit determination, or reagent addition. When performing thousands of assays, for example, during high-throughput screening, the downstream effort required for these types of assays is considerable. Therefore, to facilitate high-throughput antimicrobial discovery, we developed a real-time assay to simultaneously identify inhibitors of intracellular bacterial growth and assess eukaryotic cell cytotoxicity. Specifically, real-time intracellular bacterial growth detection was enabled by marking bacterial screening strains with either a bacterial lux operon (1st generation assay) or fluorescent protein reporters (2nd generation, orthogonal assay). A non-toxic, cell membrane-impermeant, nucleic acid-binding dye was also added during initial infection of macrophages. These dyes are excluded from viable cells. However, non-viable host cells lose membrane integrity permitting entry and fluorescent labeling of nuclear DNA (deoxyribonucleic acid). Notably, DNA binding is associated with a large increase in fluorescent quantum yield that provides a solution-based readout of host cell death. We have used this combined assay to perform a high-throughput screen in microplate format, and to assess intracellular growth and cytotoxicity by microscopy. Notably, antimicrobials may demonstrate synergy in which the combined effect of two or more antimicrobials when applied together is greater than when applied separately. Testing for in vitro synergy against intracellular pathogens is normally a prodigious task as combinatorial permutations of antibiotics at different concentrations must be assessed. However, we found that our real-time assay combined with automated, digital dispensing technology permitted facile synergy testing. Using these approaches, we were able to systematically survey action of a large number of antimicrobials alone and in combination against the intracellular pathogen, Legionella pneumophila.

A high throughput, real-time assay was developed to simultaneously identify (1) eukaryotic cell-penetrant antimicrobials targeting an intracellular bacterial pathogen, and (2) assess eukaryotic cell cytotoxicity. A variation on the same technology was thereafter combined with digital dispensing technology to enable facile, high-resolution, dose-response, and two- and three-dimensional synergy studies.

Traditional measures of intracellular antimicrobial activity and eukaryotic cell cytotoxicity rely on endpoint assays. Such endpoint assays require ...

Immunology and Infection

Antimicrobial Synergy Testing by the Inkjet Printer-assisted Automated Checkerboard Array and the Manual Time-kill Method

As rates of multidrug-resistant (MDR) pathogens continue to rise, outpacing the development of new antimicrobials, novel approaches to treatment of MDR bacteria are increasingly becoming a necessity. One such approach is combination therapy, in which two or more antibiotics are used together to treat an infection against which one or both of the drugs may be ineffective alone. When two drugs, in combination, exert a greater than additive effect, they are considered synergistic. In vitro investigation of synergistic activity is an important first step in evaluating the possible efficacy of drug combinations. Two main in vitro synergy testing methods have been developed: the checkerboard array and the time-kill study. In this paper, we present an automated checkerboard array method that makes use of inkjet printing technology to increase the efficiency and accuracy of this technique, as well as a standard manual time-kill synergy method. The automated checkerboard array can serve as a high-throughput screening assay, while the manual time-kill study provides additional, complementary data on synergistic activity and killing.
The checkerboard array is a modification of standard minimum inhibitory concentration (MIC) testing, in which bacteria are incubated with antibiotics at different concentration combinations and evaluated for growth inhibition after overnight incubation. Manual performance of the checkerboard array requires a laborious and error-prone series of calculations and dilutions. In the automated method presented here, the calculation and dispensing of required antibiotic stock solution volumes are automated through the use of inkjet printer technology. In the time-kill synergy assay, bacteria are incubated with the antibiotics of interest, both together and individually, and sampled at intervals over the course of 24 h for quantitative culture. The results can determine whether a combination is synergistic and whether it is bactericidal, and provide data on inhibition and killing of bacteria over time.

Antimicrobial synergy testing is used to evaluate the effect of two or more antibiotics used in combination and is typically performed by one of two methods: the checkerboard array or the time-kill assay. Here, we present an automated, inkjet printer-assisted checkerboard array synergy technique and a classic time-kill synergy study.

As rates of multidrug-resistant (MDR) pathogens continue to rise, outpacing the development of new antimicrobials, novel approaches to treatment of MDR ...

Thyroid Cancer Cells as Effectors in an ADCC Bioassay for Cancer Immunotherapy

Assessing Antibody-dependent, Cell-mediated Cytotoxicity in Cancer Cells using Antibody-Dependent Cell-Mediated Cytotoxicity Reporter Bioassay

The method for antibody-dependent, cell-mediated cytotoxicity (ADCC) represents an important tool to assess the efficacy of therapeutic antibodies in cancer immunotherapy. Evaluating ADCC activity in cancer cells is essential for the development and optimization of antibody-based treatments. Here, we propose a methodological approach of utilizing an ADCC bioassay kit for quantitative assessment of ADCC reaction using thyroid cancer cells as effector cells. The protocol involves the co-culture of effector cells with target cancer cells in different ratios in the presence of a therapeutic antibody. The ADCC bioassay kit used in this experiment includes the genetically engineered effector cells expressing a luciferase reporter gene under the control of Nuclear Factor of Activated T-cell (NFAT) response elements. Upon the binding of the surface antigen on the target cells with the antibodies and effector cells, the effector cells release luciferase, enabling quantification of cytotoxicity through measurement of luminescence signal. In contrast to conventional ADCC assays, this method proved the binding of target antigen with antibodies and effector cells, which can produce reliable results in a short period.

Author Spotlight: Optimizing Antibody-Based Cancer Treatments via Antibody-Dependent, Cell-Mediated Cytotoxicity Assay

Here, we present a protocol for an antibody-dependent, cell-mediated cytotoxicity (ADCC) assay using an ADCC bioassay kit. This method offers a valuable tool for elucidating the ADCC mechanism and evaluating the therapeutic potential of antibodies in cancer immunotherapy.

The method for antibody-dependent, cell-mediated cytotoxicity (ADCC) represents an important tool to assess the efficacy of therapeutic antibodies in ...

Potentiation of Anticancer Antibody Efficacy by Antineoplastic Drugs: Detection of Antibody-drug Synergism Using the Combination Index Equation

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