From ab660e869d098ef3ed950f6aa6067adec55a92bf Mon Sep 17 00:00:00 2001 From: ndwarshuis Date: Wed, 8 Sep 2021 15:48:52 -0400 Subject: [PATCH] ENH proofread most of aim 1 --- tex/thesis.tex | 497 ++++++++++++++++++++++++++----------------------- 1 file changed, 264 insertions(+), 233 deletions(-) diff --git a/tex/thesis.tex b/tex/thesis.tex index 4bcbebd..0fa4014 100644 --- a/tex/thesis.tex +++ b/tex/thesis.tex @@ -288,7 +288,10 @@ \DeclareSIUnit\IU{IU} \DeclareSIUnit\rpm{RPM} \DeclareSIUnit\carrier{carrier} +\DeclareSIUnit\gauge{gauge} \DeclareSIUnit\dms{DMS} +\DeclareSIUnit\stp{STP} +\DeclareSIUnit\snb{SNB} \DeclareSIUnit\cell{cells} \DeclareSIUnit\ab{mAb} \DeclareSIUnit\normal{N} @@ -370,6 +373,7 @@ \newcommand{\miltenyi}{Miltenyi Biotech} \newcommand{\bl}{Biolegend} \newcommand{\bd}{Becton Dickenson} +\newcommand{\pltread}{BioTek plate reader} % the obligatory misc category \newcommand{\inlinecode}{\texttt} @@ -1404,13 +1408,13 @@ novel considering the state-of-the-art technology for T cell manufacturing: \section{Introduction} -The first aim was to develop a microcarrier system that mimics several key -aspects of the \invivo{} lymph node microenvironment. We compared compare this -system to state-of-the-art T cell activation technologies for both expansion -potential and memory cell formation. The governing hypothesis was that -microcarriers functionalized with \acd{3} and \acd{28} \glspl{mab} will -provide superior expansion and memory phenotype compared to state-of-the-art -bead-based T cell expansion technology\footnote{adapted from \dmspaper{}}. +This aim was to develop a functionalized microcarrier system that mimics several +key aspects of the \invivo{} lymph node microenvironment. We compared compare +this system to state-of-the-art T cell activation technologies for both +expansion potential and memory cell formation. The governing hypothesis was that +microcarriers functionalized with \acd{3} and \acd{28} \glspl{mab} will provide +superior expansion and memory phenotype compared to state-of-the-art bead-based +T cell expansion technology\footnote{adapted from \dmspaper{}}. \section{Methods} @@ -1428,41 +1432,62 @@ bead-based T cell expansion technology\footnote{adapted from \dmspaper{}}. \end{figure*} \product{\gls{cus}}{\gehc}{DG-2001-OO} or \product{\gls{cug}}{\gehc}{DG-0001-OO} -were suspended at \SI{20}{\mg\per\ml} in 1X \gls{pbs} and autoclaved. All -subsequent steps were done aseptically, and all reactions were carried out at -\SI{20}{\mg\per\ml} carriers at room temperature and agitated using an orbital -shaker with a \SI{3}{\mm} orbit diameter. After autoclaving, the microcarriers -were washed using sterile \gls{pbs} three times in a 10:1 volume ratio. +were suspended at \SI{20}{\mg\per\ml} in 1X \gls{pbs} in a 15, 50, or 250 +\si{\ml} conical tube. The mass of the tube with the \gls{pbs} and microcarriers +were recorded to the nearest millimeter (subsequently referred to here as +``reaction mass''). The tube was centrifuged for \SI{30}{\second} at +\SI{4500}{\gforce} to ensure all microcarriers were at the bottom of the tube. +The tube was then autoclaved using a \SI{15}{\minute} cycle at +\SI{121}{\degreeCelsius} and \SI{100}{\kPa\of{\gauge}}. + +All subsequent steps were done aseptically, and all reactions were carried out +at \SI{20}{\mg\of{\carrier}\per\ml} at room temperature and agitated using an +orbital shaker with a \SI{3}{\mm} orbit diameter. After autoclaving, the +microcarriers were washed using sterile \gls{pbs} three times in a 10:1 volume +ratio. The volume after these washes was corrected by massing the tube and its +contents and adding or removing \gls{pbs} until the ``reaction mass'' was +reached. + \product{\Gls{snb}}{\thermo}{21217} was dissolved at approximately \SI{10}{\uM} in sterile ultrapure water, and the true concentration was then determined using -the \gls{haba} assay (see below). \SI{5}{\ul\of{\ab}\per\mL} \gls{pbs} was added -to carrier suspension and allowed to react for \SI{60}{\minute} at -\SI{700}{\rpm} of agitation. After the reaction, the amount of biotin remaining -in solution was quantified using the \gls{haba} assay (see below). The carriers -were then washed three times, which entailed adding sterile \gls{pbs} in a 10:1 -volumetric ratio, agitating at \SI{900}{\rpm} for \SI{10}{\minute}, adding up to -a 15:1 volumetric ratio (relative to reaction volume) of sterile \gls{pbs}, -centrifuging at \SI{1000}{\gforce} for \SI{1}{\minute}, and removing all liquid -back down to the reaction volume. +the \gls{haba} assay (see below). \SI{2.5}{\nmol\of{\snb}\per\mg\of{\carrier}} +(unless otherwise noted) was added to carrier suspension and allowed to react +for \SI{60}{\minute} at \SI{700}{\rpm} of agitation. After the reaction, the +amount of biotin attached to the microcarriers was determined indirectly by +measuring the biotin in solution via the \gls{haba} assay (see below). The +carriers were then washed three times, which entailed adding sterile \gls{pbs} +in a 10:1 volumetric ratio, agitating at \SI{900}{\rpm} for \SI{10}{\minute}, +adding up to a 15:1 volumetric ratio (relative to reaction volume) of sterile +\gls{pbs}, centrifuging at \SI{1000}{\gforce} for \SI{1}{\minute}, and removing +all liquid back down to the reaction volume. The volume of the \gls{pbs} was +corrected by massing the tube and its contents and adding or removing \gls{pbs} +until the tube mass matched the ``reaction mass.'' -To coat with \gls{stp}, \SI{40}{\ug\per\mL} \product{\gls{stp}}{Jackson - Immunoresearch}{016-000-114} was added and allowed to react for -\SI{60}{\minute} at \SI{700}{RPM} of agitation. After the reaction, supernatant -was taken for the \product{\gls{bca} assay}{\thermo}{23225}, and the carriers -were washed analogously to the previous wash step to remove the biotin, except -two washes were done and the agitation time was \SI{30}{\minute}. Biotinylated +To coat the microcarriers with \product{\gls{stp}}{Jackson + Immunoresearch}{016-000-114}, \SI{2}{\ug\of{\stp}\per\mg\of{\carrier}} was +added and allowed to react for \SI{60}{\minute} at \SI{700}{RPM} of agitation. +After the reaction, \SI{400}{\ul} supernatant (regardless of tube size) was +taken for the \product{\gls{bca} assay}{\thermo}{23225} in order to indirectly +quantify \gls{stp} attachment. Prior to the assay, the supernatent was filtered +through a \SI{40}{\um} cell strainer to remove any stray microcarriers, which +could increase the \gls{bca} readout as the assay is protein-agnostic and each +microcarrier is approximately \SI{1}{\ug}. The carriers were washed analogously +to the previous wash step to remove biotin, except two wash cycles were used, +the agitation time was \SI{30}{\minute}, and the first cycle had an extra +\SI{400}{\ul} \gls{pbs} to make up for the volume removed for the \gls{bca} +assay. + +To coat with \glspl{mab}, sterile \product{\gls{bsa}}{\sigald}{A9576} was first +added to a final concentration of \SI{2}{\percent} in order to prevent +non-specific binding of the \glspl{mab} to the reaction tubes. Biotinylated \glspl{mab} against human CD3 \catnum{\bl}{317320} and CD28 \catnum{\bl}{302904} were combined in a 1:1 mass ratio and added to the carriers at -\SI{0.2}{\ug\of{\ab}\per\mg\of{\dms}}. Along with the \glspl{mab}, sterile -\product{\gls{bsa}}{\sigald}{A9576} was added to a final concentration of -\SI{2}{\percent} in order to prevent non-specific binding of the antibodies to -the reaction tubes. \glspl{mab} were allowed to bind to the carriers for -\SI{60}{\minute} with \SI{700}{\rpm} agitation. After binding, supernatants were -sampled to quantify remaining \gls{mab} concentration using an -\product{\anti{\gls{igg}} \gls{elisa} kit}{Abcam}{157719}. Fully functionalized -\glspl{dms} were washed in sterile \gls{pbs} analogous to the previous washing -step to remove excess \gls{stp}. They were washed once again in the cell culture -media to be used for the T cell expansion. +\SI{0.2}{\ug\of{\ab}\per\mg\of{\carrier}}. \glspl{mab} were allowed to bind to +the carriers for \SI{60}{\minute} with \SI{700}{\rpm} agitation. After binding, +\SI{400}{\ul} supernatant was sampled to indirectly quantify \gls{mab} +attachment using an \product{\anti{\gls{igg}} \gls{elisa} kit}{Abcam}{157719}. +Fully functionalized \glspl{dms} were washed in sterile \gls{pbs} analogous to +the previous washing step to remove excess \gls{stp}. \begin{table}[!h] \centering \caption{Microcarrier properties} @@ -1470,7 +1495,9 @@ media to be used for the T cell expansion. \input{../tables/carrier_properties.tex} \end{table} -The concentration of the final \gls{dms} suspension was found by taking a +Finished \glspl{dms} were washed once again in the cell culture media (analogous +to previous washing steps) to be used for the T cell expansion. The +concentration of the final \gls{dms} suspension was found by taking a \SI{50}{\uL} sample, plating in a well, and imaging the entire well. The image was then manually counted to obtain a concentration. Surface area for \si{\ab\per\um\squared} was calculated using the properties for \gls{cus} and @@ -1486,25 +1513,28 @@ ester linkages from binding to the avidin proteins in the \gls{haba}/avidin premix. All quantifications of \gls{haba} were performed on an Eppendorf D30 Spectrophotometer using \product{\SI{70}{\ul} cuvettes}{BrandTech}{759200}. The extinction coefficient at \SI{500}{\nm} for \gls{haba}/avidin was assumed to be -\SI{34000}{\per\cm\per\molar}. +\SI{34000}{\per\cm\per\molar}\footnote{\SI{500}{\nm} is normally used for the + \gls{haba} assay, but the spectrophotometer to which we had access only had + \SI{490}{\nm} as the closest wavelength; the extinction coefficient should + change little}. The \gls{stp} binding to the microcarriers was quantified indirectly using a \product{\gls{bca} kit}{\thermo}{23227} according to the manufacturer’s instructions, with the exception that the standard curve was made with known concentrations of purified \gls{stp} instead of \gls{bsa}. Absorbance at -\SI{592}{\nm} was quantified using a BioTek plate reader. +\SI{592}{\nm} was quantified using a \pltread{}. The \gls{mab} binding to the microcarriers was quantified indirectly using an \gls{elisa} assay per the manufacturer’s instructions, with the exception that the same \glspl{mab} used to coat the carriers were used as the standard for the -\gls{elisa} standard curve. +\gls{elisa} standard curve. This assay was quantified using a \pltread{}. Open biotin binding sites on the \glspl{dms} after \gls{stp} coating was quantified indirectly using \product{\gls{fitcbt}}{\thermo}{B10570}. Briefly, \SI{400}{\pmol\per\ml} \gls{fitcbt} were added to \gls{stp}-coated carriers and allowed to react for \SI{20}{\minute} at room temperature under constant agitation. The supernatant was quantified against a standard curve of -\gls{fitcbt} using a BioTek plate reader. +\gls{fitcbt} using a \pltread{}. \Gls{stp} binding was verified after the \gls{stp}-binding step visually by adding \gls{fitcbt} to the \gls{stp}-coated \glspl{dms}, resuspending in @@ -1523,7 +1553,7 @@ Cryopreserved primary human T cells were either obtained as sorted using \glspl{dms} or \product{\SI{3.5}{\um} CD3/CD28 magnetic beads}{\miltenyi}{130-091-441}. In the case of beads, T cells were activated at the manufacturer recommended cell:bead ratio of 2:1. In the case of -\glspl{dms}, cells were activated using \SI{2500}{\dms\per\cm\squared} unless +\glspl{dms}, cells were activated using \SI{1500}{\dms\per\cm\squared} unless otherwise noted. Initial cell density was \SIrange{2e6}{2.5e6}{\cell\per\ml} to in a 96 well plate with \SI{300}{\ul} volume. Serum-free media was either \product{OpTmizer}{\thermo}{A1048501} or @@ -1616,9 +1646,9 @@ transwell was quantified for total cells using \product{countbright Cytotoxicity of expanded \gls{car} T cells was assessed using a degranulation assay as previously described\cite{Schmoldt1975}. Briefly, \num{3e5} T cells were incubated with \num{1.5e5} target cells consisting of either \product{K562 - wild type cells}{ATCC}{CCL-243} or CD19- expressing K562 cells transformed -with \gls{crispr} (kindly provided by Dr.\ Yvonne Chen, UCLA)\cite{Zah2016}. -Cells were seeded in a flat bottom 96 well plate with \SI{1}{\ug\per\ml} + wild type cells}{ATCC}{CCL-243} or \cdp{19} K562 cells transformed with +\gls{crispr} (kindly provided by Dr.\ Yvonne Chen, UCLA)\cite{Zah2016}. Cells +were seeded in a flat bottom 96 well plate with \SI{1}{\ug\per\ml} \product{\acd{49d}}{eBioscience}{16-0499-81}, \SI{2}{\micro\molar} \product{monensin}{eBioscience}{ 00-4505-51}, and \SI{1}{\ug\per\ml} \product{\acd{28}}{eBioscience}{302914} (all functional grade \glspl{mab}) with @@ -1643,23 +1673,24 @@ prior to analyzing on a \bd{} Accuri \subsection{CAR Plasmid and Lentiviral Transduction} -The anti-CD19-CD8-CD137-CD3$\upzeta$ \gls{car} with the EF1$\upalpha$ +The anti-CD19-CD8-CD137-CD3$\upzeta$ \gls{car} sequence with the EF1$\upalpha$ promotor\cite{Milone2009} was synthesized (Aldevron) and subcloned into a -\product{FUGW}{Addgene}{14883} kindly provided by the Emory Viral Vector Core. -Lentiviral vectors were synthesized by the Emory Viral Vector Core or the -Cincinnati Children's Hospital Medical Center Viral Vector Core. RNA titer was -calculated using a \product{Lenti-X \gls{qpcr} titer kit}{Takara}{631235}. To -transduce primary human T cells, \product{retronectin}{Takara}{T100A} was coated -onto non-TC treated 96 well plates and used to immobilize lentiviral vector -particles according to the manufacturer's instructions. Briefly, retronectin -solution was adsorbed overnight at \SI{4}{\degreeCelsius} and blocked the next -day using \gls{bsa}. Prior to transduction, lentiviral supernatant was -spinoculated at \SI{2000}{\gforce} for \SI{2}{\hour} at \SI{4}{\degreeCelsius}. -T cells were activated in 96 well plates using beads or \glspl{dms} for -\SI{24}{\hour}, and then cells and beads/\glspl{dms} were transferred onto -lentiviral vector coated plates and incubated for another \SI{24}{\hour}. Cells -and beads/\glspl{dms} were removed from the retronectin plates using vigorous -pipetting and transferred to another 96 well plate wherein expansion continued. +\product{FUGW transfer plasmid}{Addgene}{14883} kindly provided by the Emory +Viral Vector Core. Lentiviral vectors were synthesized by the Emory Viral Vector +Core or the Cincinnati Children's Hospital Medical Center Viral Vector Core. RNA +titer was calculated using a \product{Lenti-X \gls{qpcr} titer + kit}{Takara}{631235}. To transduce primary human T cells, +\product{retronectin}{Takara}{T100A} was coated onto non-TC treated 96 well +plates and used to immobilize lentiviral vector particles according to the +manufacturer's instructions. Briefly, retronectin solution was adsorbed +overnight at \SI{4}{\degreeCelsius} and blocked the next day using \gls{bsa}. +Prior to transduction, lentiviral supernatant was spinoculated at +\SI{2000}{\gforce} for \SI{2}{\hour} at \SI{4}{\degreeCelsius}. T cells were +activated in 96 well plates using beads or \glspl{dms} for \SI{24}{\hour}, and +then cells and beads/\glspl{dms} were transferred onto lentiviral vector coated +plates and incubated for another \SI{24}{\hour}. Cells and beads/\glspl{dms} +were removed from the retronectin plates using vigorous pipetting and +transferred to another 96 well plate wherein expansion continued. % METHOD fill in missing product numbers \gls{bcma} \gls{car} lentiviral vector was synthesized in house as @@ -1697,19 +1728,36 @@ The equation for hydrolysis of \gls{snb} to biotin and \gls{nhs} is given by \ce{NHS-CO-Biotin + OH- -> NHS- + Biotin-COOH} \end{equation} -Measuring the hydrolysis of \gls{snb} was performed spectroscopically. \gls{snb} -was added to either \gls{di} water or \gls{pbs} in a UV-transparent 96 well -plate. Kinetic analysis using a BioTek plate reader began immediately after -prep, and readings at \SI{260}{\nm} were taken every minute for \SI{2}{\hour}. +Measuring the hydrolysis of \gls{snb} was performed spectroscopically as the +extinction coefficient of \ce{NHS-} is well-known. \gls{snb} was added to either +\gls{di} water or \gls{pbs} in a UV-transparent 96 well plate. Kinetic analysis +using a \pltread{} began immediately after prep, and readings at \SI{260}{\nm} +were taken every minute for \SI{2}{\hour}. The extinction coefficient of +\ce{NHS-} at \SI{260}{\nm} was assumed to be \SI{8600}{\per\cm\per\molar}. \subsection{Reaction Kinetics Quantification} -The diffusion of \gls{stp} into biotin-coated microcarriers was determined -experimentally. \SI{40}{\ug\per\ml} \gls{stp} was added to multiple batches of -biotin-coated microcarriers, and supernatents were taken at fixed intervals and -quantified for \gls{stp} protein using the \gls{bca} assay. +The reaction kinetics of \gls{stp} attaching to biotin-coated microcarriers was +determined experimentally. \SI{40}{\ug\per\ml} \gls{stp} was added to multiple +batches of biotin-coated microcarriers, and supernatents were taken at fixed +intervals and quantified for \gls{stp} protein using the \gls{bca} assay as +described above. -The geometric diffusivity of the microcarriers was determined using a +To model diffusion in the microcarriers, we assumed that its pores were large +enough that the interactions between the \gls{stp} and surfaces would be small. +This means that the apparent, macroscropic diffusion of a given species within +the microcarriers would only depend on the aqueous diffusion coefficient of +\gls{stp} and a fractional factor (the ``geometric diffusivity'') representing +the additional path length an \gls{stp} molecule would take in the microcarriers +due to the tortuousity and void fraction of its pore network. This is given in +\cref{eqn:stp_diffusion_3}. + +\begin{equation} + \label{eqn:stp_diffusion_3} + \gls{sym:appdiff}=\gls{sym:diff} \gls{sym:geodiff} +\end{equation} + +This geometric diffusivity of the microcarriers was determined using a pseudo-steady-state model. Each microcarrier was assumed to be a porous sphere with a fixed number of uniformly distributed ``receptors'' equal to the number of \gls{stp} molecules (here called ``ligands'') experimentally determined to @@ -1717,11 +1765,8 @@ bind to the microcarriers. Because the reaction rate between biotin and \gls{stp} is so fast (it is the strongest non-covalent bond in known existence), we assumed that the interface of unbound receptors (free biotin) shrunk as a function of \gls{stp} diffusing to the unbound biotin interface until the center -of the microcarriers was reached. We also assumed that the pores in the -microcarriers were large enough that the interactions between the \gls{stp} and -surfaces would be small, thus the geometric diffusivity could be represented as -a fraction of the diffusion coefficient of \gls{stp} in water. This model was -given by \cref{eqn:stp_diffusion_1,eqn:stp_diffusion_2,eqn:stp_diffusion_3}: +of the microcarriers was reached. This model was given by +\cref{eqn:stp_diffusion_1,eqn:stp_diffusion_2}: \begin{equation} \label{eqn:stp_diffusion_1} @@ -1738,24 +1783,22 @@ given by \cref{eqn:stp_diffusion_1,eqn:stp_diffusion_2,eqn:stp_diffusion_3}: {\gls{sym:vol} (1 / \gls{sym:rad} - 1 / \gls{sym:mcrad})} \end{equation} -\begin{equation} - \label{eqn:stp_diffusion_3} - \gls{sym:appdiff}=\gls{sym:diff} \gls{sym:geodiff} -\end{equation} - The diffusion rate of \gls{stp} was assumed to be \SI{6.2e-7}{\cm\squared\per\second}\cite{Kamholz2001}. Since all but $\beta$ was known, the experimental data was fit using these equations using \inlinecode{ode45} in MATLAB and least squares as the fitting error. These -equations were then used analogously to describe the reaction profile of -\glspl{mab} assuming a diffusion rate of +fitted equations were then used to simulate the reaction profile of \glspl{mab} +assuming a diffusion rate of \SI{4.8e-7}{\cm\squared\per\second}\cite{Sherwood1992}. To model the washing of the microcarriers, they once again were assumed to be porous spheres filled with whatever amount of reagent was left unbound from the previous step (which was assumed to be equal to concentration in the -supernatent). The diffusion out of the microcarriers is given by the following -partial differential equation and boundary conditions: +supernatent). The fitted geometric diffusivity from above was used in these +washing calculations, and \SI{5.0e-6}{\cm\squared\per\second}\cite{Niether2020} +was used as the diffusion coefficient for free biotin. The diffusion out of the +microcarriers is given by the following partial differential equation and +boundary conditions: \begin{equation} \label{eqn:stp_washing} @@ -1786,24 +1829,18 @@ partial differential equation and boundary conditions: \evalat{\gls{sym:bulkligconc}}{\gls{sym:time} = \infty}) / 2 \end{equation} -Note that in order to avoid solving a moving boundary value problem, the -concentration at the boundary of the microcarriers was fixed at the average of -the final and initial concentration expected to be observed in bulk. This should -be a reasonable assumption given that the volume inside the microcarriers is -tiny compared to the amount of volume added in the wash, thus the boundary +In order to avoid solving a moving boundary value problem, the concentration at +the boundary of the microcarriers was fixed at the average of the final and +initial concentration expected to be observed in bulk. This should be a +reasonable assumption given that the volume inside the microcarriers is tiny +compared to the amount of volume added in the wash, thus the boundary concentration should change little. -The same diffusion coefficients were used in determining the kinetics of the -washing steps, and \SI{5.0e-6}{\cm\squared\per\second}\cite{Niether2020} was -used as the diffusion coefficient for free biotin (which should be the only -reactive species left in solution after all the \gls{snb} has hydrolyzed). - All diffusion coefficients were taken to be valid at \gls{rt} and in \gls{di} water, which is a safe assumption given that our reaction medium was 1X -\gls{pbs}. - -See \cref{sec:appendix_binding} and \cref{sec:appendix_washing} for the MATLAB -code and derivations, as well as output in the case of the washing steps. +\gls{pbs}. See \cref{sec:appendix_binding} and \cref{sec:appendix_washing} for +the MATLAB code and derivations, as well as output in the case of the washing +steps. \subsection{Luminex Analysis}\label{sec:luminex_analysis} @@ -1850,23 +1887,22 @@ notebooks (eg OneNote files) was not easily parsable, and thus this data was summarized in YAML files. The data included in these YAML files included reagent characteristics (vendor, catalog number, lot number, manufacturing date), cell donor characteristics (age, \gls{bmi}, phenotype, demographic, gender), and all -experimental parameters such as the number of bead or \gls{dms} added. +experimental parameters such as the number of beads or \glspl{dms} added. To aggregate the data in a database, we wrote a program using Python, R, and Docker which retrieved the data from its source location and inserted the data -in a Postgres database (specifically Aurora implementation hosted on \gls{aws}). -This program included checks to ensure the integrity of source data (for -example, flagging entries which had a reagent whose manufacturing date was after -the date the experiment started, which signifies a human input error). - +in a PostgreSQL database (specifically the Aurora implementation hosted on +\gls{aws}). This program included checks to ensure the integrity of source data +(for example, flagging entries which had a reagent whose manufacturing date was +after the date the experiment started, which signifies a human input error). \subsection{Statistical Analysis}\label{sec:statistics} For 1-way \gls{anova} analysis with Tukey multiple comparisons test, significance was assessed using the \inlinecode{stat\_compare\_means} function with the \inlinecode{t.test} method from the \inlinecode{ggpubr} library in R. -For 2-way \gls{anova} analysis, the significance of main and interaction effects -was determined using the car library in R. +For 2-way \gls{anova} analysis, significance of main and interaction effects +was determined using the \inlinecode{car} library in R. For least-squares linear regression, statistical significance was evaluated the \inlinecode{lm} function in R. All results with categorical variables are @@ -1942,7 +1978,7 @@ properties of \gls{cus} and \gls{cug} were the same (\cref{tab:carrier_props}). We chose to continue with the \gls{cus}-based \glspl{dms}, which showed higher overall \gls{stp} binding compared to \gls{cug}-based \glspl{dms} (\cref{fig:cug_vs_cus}). We showed that by varying the concentration of -\gls{snb}, we were able to precisely control the amount of attached biotin +\gls{snb}, we were able to control the amount of attached biotin (\cref{fig:biotin_coating}), mass of attached \gls{stp} (\cref{fig:stp_coating}), and mass of attached \glspl{mab} (\cref{fig:mab_coating}). Furthermore, we showed that the microcarriers were @@ -1995,7 +2031,7 @@ of reaction parameters on biotin binding. The parameters included in this \gls{doe} were temperature, microcarrier mass, and \gls{snb} input mass. These were parameters that we specifically controlled but hypothesized might have some sensitivity on the final biotin mass attachment rate depending on their noise -and uncertainty. In particular, temperature was `controlled' only by allowing +and uncertainty. In particular, temperature was ``controlled'' only by allowing the microcarrier suspension to come to \gls{rt} after autoclaving. After performing a full factorial \gls{doe} with three center points as the target reaction conditions, we found that the final biotin binding mass is only highly @@ -2003,10 +2039,10 @@ dependent on biotin input concentration (\cref{fig:dms_qc_doe}). Overall, temperature had no effect and carrier mass had no effect at higher temperatures, but carrier mass had a slightly positive effect when temperature was low. This could be because lower temperature might make spontaneous decay of \gls{snb} -occur slower, which would give \gls{snb} molecule more opportunity to diffuse -into the microcarriers and react with amine groups to form attachments. It seems -that concentration only has a linear effect and doesn't interact with any of the -other variables, which is not surprisingly given the behavior observed in +occur slower, which would give \gls{snb} molecules more opportunity to diffuse +into the microcarriers and react with amine groups to form attachments. It +seemed that concentration only has a linear effect and doesn't interact with any +of the other variables, which is not surprising given the behavior observed in (\cref{fig:biotin_coating}) We also observed that the reaction pH does not influence the amount of biotin @@ -2016,7 +2052,7 @@ it also increases the number of \ce{OH-} groups which can spontaneously hydrolyze the \gls{snb} in solution (\cref{chem:snb_hydrolysis}). Furthermore, we observed that washing the microcarriers after autoclaving -increases the biotin binding rate (\cref{fig:dms_qc_washes}). While we did not +increased the biotin binding rate (\cref{fig:dms_qc_washes}). While we did not explore this further, one possible explanation for this behavior is that the microcarriers have some loose protein in the form of powder or soluble peptides that competes for \gls{snb} binding against the surface of the microcarriers, @@ -2031,14 +2067,14 @@ carefully control the timing between \gls{snb} solution preparation and addition to the microcarriers. We found that in the presence of \gls{di} water, \gls{snb} is extremely stable (\cref{fig:dms_snb_decay_curves}) where it decays rapidly in the presence of \gls{pbs} buffered to pH of 7.1. In fact, the \gls{di} water -curve actually decreases slightly, possibly due to \gls{snb} absorbing to the -plate surface. \gls{snb} is known to hydrolyze in the presence of \ce{OH-}, but -the lack of hydrolysis in \gls{di} water can be explained by the fact that -biotin itself is acidic, and thus the reaction is self-inhibitory in an -unbuffered and neutral pH system. Because we dissolve our \gls{snb} in \gls{di} -water prior to adding it to the microcarrier suspension (which itself is in -\gls{pbs}) this result indicated that hydrolysis is not of concern when adding -\gls{snb} within minutes. +curve actually decreased slightly, possibly due to \gls{snb} absorbing to the +plate surface. \gls{snb} is known to hydrolyze in the presence of \ce{OH-} +groups, but the lack of hydrolysis in \gls{di} water can be explained by the +fact that biotin itself is acidic, and thus the reaction is self-inhibitory in +an unbuffered and neutral pH system. Because we dissolve our \gls{snb} in +\gls{di} water prior to adding it to the microcarrier suspension (which itself +is in \gls{pbs}) this result indicated that hydrolysis is not of concern when +adding \gls{snb} within minutes. \begin{figure*}[ht!] \begingroup @@ -2078,7 +2114,7 @@ put in terms of fraction of input \gls{snb}, we observed that the curves are almost identical (\cref{fig:dms_biotin_rxn_frac}). Given this, the reaction step for biotin attached can be set to \SI{30}{\minute}\footnote{we actually used \SI{60}{\minute} as outlined in methods, which shouldn't make any difference - except save for being excessive according to this result}. + except for costing more time}. Next, we quantified the amount of \gls{stp} reacted with the surface of the biotin-coated microcarriers. Different batches of biotin-coated \glspl{dms} were @@ -2088,46 +2124,46 @@ using the \gls{bca} assay to indirectly quantify the amount of attached (\cref{fig:dms_stp_per_time}). Assuming a quasi-steady-state paradigm, we used this experimental binding data to compute the geometric diffusivity of the microcarriers and fit a continuous model for the \gls{stp} binding reaction. We -computed the number of `binding sites' using the maximum mass observed to bind +computed the number of ``receptors'' using the maximum mass observed to bind to the \gls{dms}, which should describe the upper-bound for reaction time (\cref{fig:stp_coating}). Using the diffusion rate of the \gls{stp} (\SI{6.2e-7}{\cm\squared\per\second}), we then calculated the geometric diffusivity of the microcarriers to be 0.190 (see \cref{eqn:stp_diffusion_1,eqn:stp_diffusion_2}). -Using this geometric diffusivity and the known diffusion coefficient of a -\gls{mab} protein in water, we calculated the binding of \glspl{mab} per time -onto the microcarriers (this obviously assumes that the effectively diffusivity -is independent of the protein used, which should be reasonable given that the -pores of the microcarriers are huge compared to the proteins, and we don't -expect any significant reaction between the protein and the microcarrier surface -save for the \gls{stp}-biotin binding reaction). Once again, we used the maximum -number of \glspl{mab} observed to determine the number of `binding sites' for -\glspl{mab} on the microcarriers, which should correspond to the upper-bound for -the reaction time (\cref{fig:mab_coating}). According to this model, the -\gls{mab} binding reaction should be complete within \SI{75}{\minute} under the -conditions used for our protocol (\cref{fig:dms_mab_per_time})\footnote{We - actually used \SI{60}{\minute} as describe in the method section as this model - was not updated with new parameters until recently; however, we should point - out that even at \SI{60}{\minute} the reaction appears to be - >\SI{95}{\percent} complete}. +Using this geometric diffusivity and the known diffusion coefficient of +\glspl{mab} in water, we calculated the binding of \glspl{mab} per time onto the +microcarriers (this obviously assumes that the effectively diffusivity is +independent of the protein used, which should be reasonable given that the pores +of the microcarriers are huge compared to the proteins, and we don't expect any +significant reaction between the protein and the microcarrier surface save for +the \gls{stp}-biotin binding reaction). Once again, we used the maximum number +of \glspl{mab} observed to determine the number of receptors for \glspl{mab} on +the microcarriers, which should correspond to the upper-bound for the reaction +time (\cref{fig:mab_coating}). According to this model, the \gls{mab} binding +reaction should be complete within \SI{75}{\minute} under the conditions used +for our protocol (\cref{fig:dms_mab_per_time})\footnote{we actually used + \SI{60}{\minute} as describe in the method section as this model was not + updated with new parameters until recently; however, we should point out that + even at \SI{60}{\minute} the reaction appears to be >\SI{95}{\percent} + complete}. Finally, we calculated the number of wash steps needed to remove the reagents between each step, including the time for each wash which required the geometric diffusivity of the microcarriers as calculated above. This is important, as failing to wash out residual free \gls{snb} (for example) could occupy binding sites on the \gls{stp} molecules, lowering the effective binding capacity of the -\gls{mab} downstream. Each wash was a 1:15 dilution (\SI{1}{\ml} reaction volume -in a \SI{15}{\ml} conical tube), and in the case of \gls{snb} we wished to wash -out enough biotin such that less than \SI{1}{\percent} of the binding sites in -\gls{stp} would be occupied. Given this dilution factor, a maximum of +\glspl{mab} downstream. Each wash was a 1:15 dilution (\SI{1}{\ml} reaction +volume in a \SI{15}{\ml} conical tube), and in the case of \gls{snb} we wished +to wash out enough biotin such that less than \SI{1}{\percent} of the binding +sites in \gls{stp} would be occupied. Given this dilution factor, a maximum of \SI{20}{\nmol} of biotin remaining \cref{fig:biotin_coating} \SI{2.9}{\nmol} biotin binding sites on \SI{40}{\ug} \gls{stp} (assuming 4 binding sites per \gls{stp} protein), this turned out to be 3 washes. By similar logic, using 2 washes after the \gls{stp} binding step will ensure that the number of free \gls{stp} binding sites is less than 20X the number of \gls{mab} molecules added\footnote{This step may benefit from an additional wash, as the number of - washes used here was develop when \SI{40}{\ug} rather than \SI{4}{\ug} + washes used here was determined when \SI{40}{\ug} rather than \SI{4}{\ug} \gls{mab} was used to coat the \gls{dms}, yielding a much wider margin. However, it is also not clear to what extent this matters, as the \gls{mab} have multiple biotin molecules per \gls{mab} protein, and thus one \gls{mab} @@ -2140,15 +2176,15 @@ microcarriers to be porous spheres, this time with an initial concentration of bulk concentration of the previous binding step, and calculated the amount of time it would take for the concentration profile inside the microcarriers to equilibrate to the bulk in the wash step. Using this model, we found that the -wash times for \gls{snb}, \gls{stp}, and \glspl{mab} was \SI{3}{\minute}, +wash time for \gls{snb}, \gls{stp}, and \glspl{mab} was \SI{3}{\minute}, \SI{15}{\minute}, and \SI{17}{\minute} respectively. We verified that the \gls{snb} was totally undetectable after washing (\cref{fig:dms_biotin_washed}). The other two species need to be verified in a similar manner; however, we should not that the washing time for both the \gls{stp} and \gls{mab} coating -steps were \SI{30}{\minute}, which is a significant margin of safety (albeit -one that could be optimized). +steps were \SI{30}{\minute}, which is a significant margin of safety (albeit one +that could be optimized). -MATLAB code and output for all the wash step calculations are given in +MATLAB code and output for all wash step calculations are given in \cref{sec:appendix_washing}. \subsection{DMSs Can Efficiently Expand T Cells Compared to Beads} @@ -2195,18 +2231,17 @@ MATLAB code and output for all the wash step calculations are given in We next sought to determine how our \glspl{dms} could expand T cells compared to state-of-the-art methods used in industry. All bead expansions were performed as per the manufacturer’s protocol, with the exception that the starting cell -densities were matched between the beads and carriers to -~\SI{2.5e6}{\cell\per\ml}. Throughout the culture we observed that T cells in -\gls{dms} culture grew in tight clumps on the surface of the \glspl{dms} as well -as inside the pores of the \glspl{dms} -(\cref{fig:dms_cells_phase,fig:dms_cells_fluor}). Furthermore, we observed that -the \glspl{dms} conferred greater expansion compared to traditional beads, and -significantly greater expansion after \SI{12}{\day} of culture -(\cref{fig:dms_expansion_bead}). We also observed no T cell expansion using -\glspl{dms} coated with an isotype control mAb compared to \glspl{dms} coated -with \acd{3}/\acd{28} \glspl{mab} (\cref{fig:dms_expansion_isotype}), confirming -specificity of the expansion method. Given that \il{2} does not lead to -expansion on its own, we know that the expansion of the T cells shown here is +densities were matched between the beads and \glspl{dms} to +~\SI{2.5e6}{\cell\per\ml}. We observed that T cells in \gls{dms} culture grew in +tight clumps on the surface of the \glspl{dms} as well as inside the pores of +the \glspl{dms} (\cref{fig:dms_cells_phase,fig:dms_cells_fluor}). Furthermore, +we observed that the \glspl{dms} conferred greater expansion compared to +traditional beads, and significantly greater expansion after \SI{12}{\day} of +culture (\cref{fig:dms_expansion_bead}). We also observed no T cell expansion +using \glspl{dms} coated with an isotype control mAb compared to \glspl{dms} +coated with \acd{3}/\acd{28} \glspl{mab} (\cref{fig:dms_expansion_isotype}), +confirming specificity of the expansion method. Given that \il{2} does not lead +to expansion on its own, we know that the expansion of the T cells shown here is due to the \acd{3} and \acd{28} \glspl{mab}\cite{Waysbort2013}. \begin{figure*}[ht!] @@ -2241,19 +2276,19 @@ usually present only on the cytoplasmic surface of the cell membrane, but flips to the outside when the cell becomes apoptotic. \gls{pi} stains the nucleus of the cell, but only penetrates necrotic cells which have a perforated cell membrane. When staining for these two markers and assessing via flow cytometry, -we observe that the \gls{dms}-expanded T cells have lower frequencies of +we observed that the \gls{dms}-expanded T cells have lower frequencies of apoptotic and necrotic cells (\cref{fig:apoptosis_annV}). Furthermore, we -stained our cultures with CellEvent dye, which is an indicator of \gls{cas37}, -which is activated in apoptotic cells. In line with the \gls{pi}/\gls{anv} -results, we observed that the \gls{dms} T cells had lower frequency of -\gls{cas37} expression, indicating less apoptosis for our method -(\cref{fig:apoptosis_cas}). Finally, we lysed our cells and stained for -\gls{bcl2}, which is also upregulated in apoptosis. In this case, some (but not -all) of the bead-expanded cultures showed higher \gls{bcl2} expression, which -could indicate more apoptosis in those groups (\cref{fig:apoptosis_bcl2}). None -of the \gls{dms} cultures showed similar heightened expression. Taken together, -these data suggest that the \gls{dms} platform at least in part achieves higher -expansion by lowering apoptosis of the cells in culture. +stained our cultures with CellEvent dye, an indicator of \gls{cas37} which is +activated in apoptotic cells. In line with the \gls{pi}/\gls{anv} results, we +observed that the \gls{dms} T cells had lower frequency of \gls{cas37} +expression, indicating less apoptosis for our method (\cref{fig:apoptosis_cas}). +Finally, we lysed our cells and stained for \gls{bcl2}, which is also +upregulated in apoptosis. In this case, some (but not all) of the bead-expanded +cultures showed higher \gls{bcl2} expression, which could indicate more +apoptosis in those groups (\cref{fig:apoptosis_bcl2}). None of the \gls{dms} +cultures showed similar heightened expression. Taken together, these data +suggest that the \gls{dms} platform at least in part achieves higher expansion +by lowering apoptosis. \begin{figure*}[ht!] \begingroup @@ -2281,19 +2316,19 @@ expansion by lowering apoptosis of the cells in culture. \input{../tables/inside_fraction_regression.tex} \end{table} -We also asked how many cells were inside the \glspl{dms} vs. free-floating in -suspension and/or loosely attached to the surface. We qualitatively verified the -presence of cells inside the \glspl{dms} using a \gls{mtt} stain to opaquely -mark cells and enable visualization on a brightfield microscope -(\cref{fig:dms_inside_bf}). After seeding \glspl{dms} at different densities and -expanding for \SI{14}{\day}, we filtered the \glspl{dms} out of the cell -suspension and digested them using dispase to free any cells attached on the -inner surface. We observed that approximately \SI{15}{\percent} of the total -cells after \SI{14}{\day} were on the interior surface of the \glspl{dms} +We also asked how many cells were inside the \glspl{dms} instead of +free-floating in suspension and/or loosely attached to the surface. We +qualitatively verified the presence of cells inside the \glspl{dms} using a +\gls{mtt} stain to opaquely mark cells and enable visualization on a brightfield +microscope (\cref{fig:dms_inside_bf}). After seeding \glspl{dms} at different +densities and expanding for \SI{15}{\day}, we filtered the \glspl{dms} out of +the cell suspension and digested them using dispase to free any cells attached +on the inner surface. We observed that approximately \SI{15}{\percent} of the +total cells after \SI{15}{\day} were on the interior surface of the \glspl{dms} (\cref{fig:dms_inside_regression,tab:inside_regression}). Performing linear regression on this data revealed that the percentage of T cells inside the \glspl{dms} does not depend on the initial starting cell density (at least when -harvested after \SI{14}{\day}) (\cref{tab:inside_regression}). +harvested after \SI{15}{\day}) (\cref{tab:inside_regression}). \subsection{DMSs Lead to Greater Expansion and High-Quality Phenotypes} @@ -2332,7 +2367,7 @@ improved clinical prognosis\cite{Gattinoni2011, Wang2018}. We measured the frequency of these subtypes by staining for CCR7 and CD62L. Using three donor lots, we noted again \glspl{dms} produced more T cells over a \SI{14}{\day} expansion than beads, with significant differences in number appearing as early -after \SI{5}{\day} (\cref{fig:dms_exp_fold_change}). Furthermore, we noted that +as \SI{5}{\day} (\cref{fig:dms_exp_fold_change}). Furthermore, we noted that \glspl{dms} produced more memory/naïve cells after \SI{14}{\day} when compared to beads for all donors (\cref{fig:dms_exp_mem,fig:dms_exp_cd4}) showing that the \gls{dms} platform is able to selectively expand potent, early @@ -2364,25 +2399,23 @@ true when observing the CD4+ and CD8+ fractions of the naïve/memory subset \label{fig:dms_phenotype} \end{figure*} -We also observed that, at least with the donors and conditions tested in these -experiments\footnote{these results were not always consistent, see the - metaanalysis at the end of this aim for an in-depth quantification of this - observation} that the fraction of \ptmem{} and \pth{} T cells was higher in -the \gls{dms} groups compared to the bead groups -(\cref{fig:dms_phenotype})\footnote{these where not the same donors as used for - \cref{fig:dms_exp}}. This result was seen for multiple donors. We should note -that in the case of \pthp{}, the donors we used had an initial \pthp{} that was -much higher (healthy donors generally have a CD4:CD8 ratio of 2:1), so the -proper interpretation of this is that the \pthp{} decreases less over the -culture period with the \gls{dms} platform as opposed to the beads (or -alternatively, the \gls{dms} has less preferential expansion for CD8 T cells). -We cannot say the same about the \ptmemp{} since we did not have the initial -data for this phenotype; however (although it should be the vast majority of -cells given that cryopreserved T cells from a healthy donor should generally be -composed of circulated memory and naive T cells). Taken together, these data -indicate the \gls{dms} platform has the capacity to expand higher numbers and -percentages of highly potent \ptmem{} and \pth{} T cells compared to -state-of-the-art bead technology. +We also observed that, at least among some donors and conditions\footnote{these + results were not always consistent, see the metaanalysis at the end of this + aim for an in-depth quantification of this observation} that the fraction of +\ptmem{} and \pth{} T cells was higher in the \gls{dms} groups compared to the +bead groups (\cref{fig:dms_phenotype})\footnote{these where not the same donors + as used for \cref{fig:dms_exp}}. Note that in the case of \pthp{}, the donors +we used had an initial \pthp{} that was much higher (healthy donors generally +have a CD4:CD8 ratio of 2:1), so the proper interpretation of this is that the +\pthp{} decreases less over the culture period with the \gls{dms} platform as +opposed to the beads (or alternatively, the \gls{dms} has less preferential +expansion for \cdp{8} T cells). We cannot say the same about the \ptmemp{} since +we did not have the initial data for this phenotype; (although memory and naive +cells should be the vast majority of cells given that \glspl{pbmc} is taken from +blood which has mostly these cell types). Taken together, these data indicate +the \gls{dms} platform has the capacity to expand higher numbers and percentages +of highly potent \ptmem{} and \pth{} T cells compared to state-of-the-art bead +technology. \subsection{DMSs Produce Functional CAR T Cells} @@ -2390,12 +2423,12 @@ After optimizing for naïve/memory and CD4 yield, we sought to determine if the \glspl{dms} were compatible with lentiviral transduction protocols used to generate \gls{car} T cells\cite{Tumaini2013, Lamers2014}. We added a \SI{24}{\hour} transduction step on day 1 of the \SI{14}{\day} expansion to -insert an anti-CD19 \gls{car}\cite{Milone2009} and subsequently measured the -surface expression of the \gls{car} on day 14 -(\cref{fig:car_cd19_flow,fig:car_cd19_endpoint}). We noted -that there was robust \gls{car} expression in over \SI{25}{\percent} of expanded -T cells, and there was no observable difference in \gls{car} expression between -beads and \glspl{dms}. +insert an anti-CD19 \gls{car}\cite{Milone2009} with a \gls{moi} of 10 and +subsequently measured the surface expression of the \gls{car} on day 14 +(\cref{fig:car_cd19_flow,fig:car_cd19_endpoint}). We noted that there was robust +\gls{car} expression in over \SI{25}{\percent} of expanded T cells, and there +was no observable difference in \gls{car} expression between beads and +\glspl{dms}. We also verified the functionality of expanded \gls{car} T cells using a degranulation assay\cite{Zheng2012}. Briefly, T cells were cocultured with @@ -2451,7 +2484,7 @@ showing that migration was likely independent of \gls{car} transduction. \caption[\acrshort{car} T Cell Functionality] {\glspl{dms} produce functional \gls{car} T cells. \subcap{fig:car_degran_flow}{Representative flow plot for - degenerating T cells.} + degranulating T cells.} \subcap{fig:car_degran_endpoint}{Endpoint plots for transduced or untransduced T cells stained with \cd{107a} for the degranulation assay.} \subcap{fig:car_degran_migration}{Endpoint plot for transmigration assay @@ -2461,9 +2494,9 @@ showing that migration was likely independent of \gls{car} transduction. \end{figure*} In addition to CD19 \gls{car} T cells, we also demonstrated that the \gls{dms} -platform can be used to expand \gls{car} T cells against \gls{bcma}. Analogously -to the case with CD19, \gls{dms} and bead produced similar fractions of \ptcar{} -cells (albeit in this case at day 7 and with an undefined \gls{moi}) +platform can be used to expand \gls{car} T cells against \gls{bcma}. Analogous +to CD19, \gls{dms} and bead produced similar fractions of \ptcar{} cells (albeit +in this case at day 7 and with an undefined \gls{moi}) (\cref{fig:car_bcma_percent}). Also consistent with CD19 and non-\gls{car} data, we also found that the number of \ptcar{} T cells was greater for \gls{dms} than for bead (\cref{fig:car_bcma_total}). @@ -2509,25 +2542,23 @@ for bead (\cref{fig:car_bcma_total}). \label{fig:grex_results} \end{figure*} -We also asked if the \gls{dms} platform could expand T cells in a static -bioreactor such a Grex. We incubated T cells in a Grex analogously to that for -plates and found that T cells in Grex bioreactors expanded as efficiently as -bead over \SI{14}{\day} and had similar viability -(\cref{fig:grex_results_fc,fig:grex_results_viability}). Furthermore, consistent -with past results, \glspl{dms}-expanded T cells had higher \pthp{} compared to -beads and higher \ptmemp{} compared to beads (\cref{fig:grex_mem,fig:grex_cd4}). -Overall the \ptmemp{} was much lower than that seen from cultures grown in -tissue-treated plates (\cref{fig:dms_phenotype_mem}). +We also asked if the \gls{dms} platform could expand T cells in a Grex +bioreactor. We incubated T cells in a Grex analogously to plates and found that +T cells in Grex bioreactors expanded as efficiently as beads over \SI{14}{\day} +and had similar viability +(\cref{fig:grex_results_fc,fig:grex_results_viability}). Consistent with past +results, \glspl{dms}-expanded T cells had higher \pthp{} and \ptmemp{} compared +to beads (\cref{fig:grex_mem,fig:grex_cd4}). Overall the \ptmemp{} was lower +than that seen in standard plates (\cref{fig:dms_phenotype_mem}). -These discrepancies might be explained in light of our other data as follows. -The Grex bioreactor has higher media capacity relative to its surface area, and -we did not move the T cells to a larger bioreactor as they grew in contrast with +These discrepancies might be explained in light of other data as follows. The +Grex bioreactor has higher media capacity relative to its surface area, and we +did not move the T cells to a larger bioreactor as they grew in contrast with our plate cultures. This means that the cells had higher growth area -constraints, which may have nullified any advantage to the expansion that we -seen elsewhere (\cref{fig:dms_exp_fold_change}). Furthermore, the higher growth -area could mean higher signaling and higher differentiation rate to -\glspl{teff}, which was why the \ptmemp{} was so low compared to other data -(\cref{fig:dms_phenotype_mem}). +constraints, which may have nullified any advantage to the expansion seen in +standard plates (\cref{fig:dms_exp_fold_change}). Furthermore, the higher growth +area could mean increased signaling and \gls{teff} differentiation, which was +why the \ptmemp{} was low compared to past data (\cref{fig:dms_phenotype_mem}). \begin{figure*}[ht!] \begingroup @@ -2543,9 +2574,9 @@ area could mean higher signaling and higher differentiation rate to We also quantified the cytokines released during the Grex expansion using Luminex. We noted that in nearly all cases, the \gls{dms}-expanded T cells released higher concentrations of cytokines compared to beads -(\cref{fig:grex_luminex}). This included higher concentrations of -pro-inflammatory cytokines such as GM-CSF, \gls{ifng}, and \gls{tnfa}. This -demonstrates that \gls{dms} could lead to more robust activation and fitness. +(\cref{fig:grex_luminex}), including higher concentrations of pro-inflammatory +cytokines such as GM-CSF, \gls{ifng}, and \gls{tnfa}. This demonstrates that +\glspl{dms} could lead to more robust activation. Taken together, these data suggest that \gls{dms} also lead to robust expansion in Grex bioreactors, although more optimization may be necessary to maximize the