From bda13878e5bd691f4b1564e932af3b018b565dd8 Mon Sep 17 00:00:00 2001 From: ndwarshuis Date: Thu, 22 Jul 2021 16:23:07 -0400 Subject: [PATCH] ADD a bunch of background stuff --- tex/thesis.bbl | 20 ++++++ tex/thesis.tex | 174 ++++++++++++++++++++++++++++++++++++++++++++++++- 2 files changed, 191 insertions(+), 3 deletions(-) diff --git a/tex/thesis.bbl b/tex/thesis.bbl index 94d9ebb..f27d776 100644 --- a/tex/thesis.bbl +++ b/tex/thesis.bbl @@ -207,4 +207,24 @@ \newblock \emph{\bibinfo{journal}{{BMC} Proceedings}} \textbf{\bibinfo{volume}{5}} (\bibinfo{year}{2011}). +\bibitem{Buck2016} +\bibinfo{author}{Buck, M.~D.} \emph{et~al.} +\newblock \bibinfo{title}{{Mitochondrial Dynamics Controls T Cell Fate through + Metabolic Programming}}. +\newblock \emph{\bibinfo{journal}{Cell}} \textbf{\bibinfo{volume}{166}}, + \bibinfo{pages}{114} (\bibinfo{year}{2016}). + +\bibitem{van_der_Windt_2012} +\bibinfo{author}{van~der Windt, G.~J.} \emph{et~al.} +\newblock \bibinfo{title}{Mitochondrial respiratory capacity is a critical + regulator of {CD}8+ t cell memory development}. +\newblock \emph{\bibinfo{journal}{Immunity}} \textbf{\bibinfo{volume}{36}}, + \bibinfo{pages}{68--78} (\bibinfo{year}{2012}). + +\bibitem{Spitzer2016} +\bibinfo{author}{Spitzer, M.~H.} \& \bibinfo{author}{Nolan, G.~P.} +\newblock \bibinfo{title}{Mass cytometry: Single cells, many features}. +\newblock \emph{\bibinfo{journal}{Cell}} \textbf{\bibinfo{volume}{165}}, + \bibinfo{pages}{780--791} (\bibinfo{year}{2016}). + \end{thebibliography} diff --git a/tex/thesis.tex b/tex/thesis.tex index 7713308..449a2ee 100644 --- a/tex/thesis.tex +++ b/tex/thesis.tex @@ -54,6 +54,10 @@ \newacronym{pdms}{PDMS}{polydimethylsiloxane} \newacronym{dc}{DC}{dendritic cell} \newacronym{il2}{IL2}{interleukin 2} +\newacronym{apc}{APC}{antigen presenting cell} +\newacronym{mhc}{MHC}{major histocompatibility complex} +\newacronym{elisa}{ELISA}{enzyme-linked immunosorbent assay} +\newacronym{nmr}{NMR}{nuclear magnetic resonance} %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % my commands @@ -257,6 +261,9 @@ quality in an industrial setting. \section*{overview} +% TODO this is basically the same as the first part of the backgound, I guess I +% can just trim it down + T cell-based immunotherapies have received great interest from clinicians and industry due to their potential to treat, and often cure, cancer and other diseases\cite{Fesnak2016,Rosenberg2015}. In 2017, Novartis and Kite Pharma @@ -405,20 +412,181 @@ conclusions in Chapter~\ref{conclusions}. \chapter{background and significance}\label{background} \section*{background} + +% TODO break this apart into mfg tech and T cell phenotypes/quality +% TODO consider adding a separate section on microcarriers and their use in +% bioprocess +% TODO add stuff about T cell licensing \subsection*{current T cell manufacturing technologies} -bla bla +\Gls{car} T cell therapy has received great interest from both academia and +industry due to its potential to treat cancer and other +diseases\cite{Fesnak2016, Rosenberg2015}. In 2017, Novartis and Kite Pharma +acquired FDA approval for \textit{Kymriah} and \textit{Yescarta} respectively, +two \gls{car} T cell therapies against B cell malignancies. Despite these +successes, \gls{car} T cell therapies are constrained by an expensive and +difficult-to-scale manufacturing process\cite{Roddie2019, Dwarshuis2017}. + +Of critical concern, state-of-the-art manufacturing techniques focus only on +Signal 1 and Signal 2-based activation via anti-CD3 and anti-CD28 \glspl{mab}, +typically presented on a microbead (Invitrogen Dynabead, Miltenyi MACS beads) or +nanobead (Miltenyi TransACT), but also in soluble forms in the case of antibody +tetramers (Expamer)\cite{Wang2016, Piscopo2017, Roddie2019, Bashour2015}. These +strategies overlook many of the signaling components present in the secondary +lymphoid organs where T cells normally expand. Typically, T cells are activated +under close cell-cell contact via \glspl{apc} such as \glspl{dc}, which present +peptide-\glspl{mhc} to T cells as well as a variety of other costimulatory +signals. These close quarters allow for efficient autocrine/paracrine signaling +among the expanding T cells, which secrete IL2 and other cytokines to assist +their own growth. Additionally, the lymphoid tissues are comprised of \gls{ecm} +components such as collagen, which provide signals to upregulate proliferation, +cytokine production, and pro-survival pathways\cite{Gendron2003, Ohtani2008, + Boisvert2007, Ben-Horin2004}. + +A variety of solutions have been proposed to make the T cell expansion process +more physiological. One strategy is to use modified feeder cell cultures to +provide activation signals similar to those of \glspl{dc}\cite{Forget2014}. +While this has the theoretical capacity to mimic several key components of the +lymph node, it is hard to reproduce on a large scale due to the complexity and +inherent variability of using cell lines in a fully \gls{gmp}-compliant manner. +Others have proposed biomaterials-based solutions to circumvent this problem, +including lipid-coated microrods\cite{Cheung2018}, 3D-scaffolds via either +Matrigel\cite{Rio2018} or 3d-printed lattices\cite{Delalat2017}, ellipsoid +beads\cite{meyer15_immun}, and \gls{mab}-conjugated \gls{pdms} +beads\cite{Lambert2017} that respectively recapitulate the cellular membrane, +large interfacial contact area, 3D-structure, or soft surfaces T cells normally +experience \textit{in vivo}. While these have been shown to provide superior +expansion compared to traditional microbeads, no method has been able to show +preferential expansion of functional memory and CD4 T cell populations. +Generally, T cells with a lower differentiation state such as memory cells have +been shown to provide superior anti-tumor potency, presumably due to their +higher potential to replicate, migrate, and engraft, leading to a long-term, +durable response\cite{Xu2014, Gattinoni2012, Fraietta2018, Gattinoni2011}. +Likewise, CD4 T cells are similarly important to anti-tumor potency due to their +cytokine release properties and ability to resist exhaustion\cite{Wang2018, + Yang2017}, and no method exists to preferentially expand the CD4 population +compared to state-of-the-art systems. + +Here we propose a method using microcarriers functionalized with anti-CD3 and +anti-CD28 \glspl{mab} for use in T cell expansion cultures. Microcarriers have +historically been used throughout the bioprocess industry for adherent cultures +such as stem cells and \gls{cho} cells, but not with suspension cells such as T +cells\cite{Heathman2015, Sart2011}. The carriers have a macroporous structure +that allows T cells to grow inside and along the surface, providing ample +cell-cell contact for enhanced autocrine and paracrine signaling. Furthermore, +the carriers are composed of gelatin, which is a collagen derivative and +therefore has adhesion domains that are also present within the lymph nodes. +Finally, the 3D surface of the carriers provides a larger contact area for T +cells to interact with the \glspl{mab} relative to beads; this may better +emulate the large contact surface area that occurs between T cells and +\glspl{dc}. \subsection*{strategies to optimize cell manufacturing} -bla bla +The \gls{dms} system has a number of parameters that can be optimized, and a +\gls{doe} is an ideal framework to test multiple parameters simultaneously. The +goal of \gls{doe} is to answer a data-driven question with the least number of +resources. It was developed in many non-biological industries throughout the +\nth{20} century such as the automotive and semiconductor industries where +engineers needed to minimize downtime and resource consumption on full-scale +production lines. + +% TODO add a bit more about the math of a DOE here + +\Glspl{doe} served three purposes in this dissertation. First, we used them as +screening tools, which allowed us to test many input parameters and filter out +the few that likely have the greatest effect on the response. Second, they were +used to make a robust response surface model to predict optimums using +relatively few resources, especially compared to full factorial or +one-factor-at-a-time approaches. Third, we used \glspl{doe} to discover novel +effects and interactions that generated hypotheses that could influence the +directions for future work. \subsection*{strategies to characterize cell manufacturing} -bla bla +A number of multiomics strategies exist which can generate rich datasets for T +cells. We will consider several multiomics strategies within this proposal: + +\begin{description} +\item[Luminex:] A multiplexed bead-based \gls{elisa} that can measure + many bulk (not single cell) cytokine concentrations simultaneously + in a media sample. Since this only requires media (as opposed to + destructively measuring cells) we will use this as a longitudinal + measurement. +\item[Metabolomics:] It is well known that T cells of different + lineages have different metabolic profiles; for instance memory T + cells have larger aerobic capacity and fatty acid + oxidation\cite{Buck2016, van_der_Windt_2012}. We will interrogate + key metabolic species using \gls{nmr} in collaboration with the + Edison Lab at the University of Georgia. This will be both a + longitudinal assay using media samples (since some metabolites may + be expelled from cells that are indicative of their phenotype) and + at endpoint where we will lyse the cells and interogate their entire + metabolome. +\item[Flow and Mass Cytometry:] Flow cytometry using fluorophores has been used + extensively for immune cell analysis, but has a practical limit of + approximately 18 colors\cite{Spitzer2016}. Mass cytometry is analogous to + traditional flow cytometry except that it uses heavy-metal \gls{mab} + conjugates, which has a practical limit of over 50 markers. This will be + useful in determining precise subpopulations and phenotypes that may be + influencing responses, especially when one considers that many cell types can + be defined by more than one marker combination. We will perform this at + endpoint. While mass cytometry is less practical than simple flow cytometers + such as the BD Accuri, we may find that only a few markers are required to + accurately predict performance, and thus this could easily translate to + industry using relatively cost-effective equipment. +\end{description} + +% TODO add a computational section + +% TODO add a section explaining causal inference since this is a big part of +% the end of aim 1 \section{Innovation} +\subsection{Innovation} + +Several aspects of this work are novel considering the state-of-the-art +technology for T cell manufacturing: + +\begin{itemize} +\item \Glspl{dms} offers a compelling alternative to state-of-the-art magnetic + bead technologies (e.g. DynaBeads, MACS-Beads), which is noteworthy because + the licenses for these techniques is controlled by only a few companies + (Invitrogen and Miltenyi respectively). Because of this, bead-based expansion + is more expensive to implement and therefore hinders companies from entering + the rapidly growing T cell manufacturing arena. Providing an alternative as we + are doing will add more options, increase competition among both raw material + and T cell manufacturers, and consequently drive down cell therapy market + prices and increase innovation throughout the industry. +\item This is the first technology for T cell immunotherapies that selectively + expands memory T cell populations with greater efficiency relative to + bead-based expansion Others have demonstrated methods that can achieve greater + expansion of T cells, but not necessarily specific populations that are known + to be potent. +\item We propose to optimize our systems using \gls{doe} methodology, which is a + strategy commonly used in other industries and disciplines but has yet to gain + wide usage in the development of cell therapies. \Glspl{doe} are advantageous + as they allow the inspection of multiple parameters simultaneously, allowing + efficient and comprehensive analysis of the system vs a one-factor-at-a-time + approach. We believe this method is highly relevant to the development of cell + therapies, not only for process optimization but also hypotheses generation. + Of further note, most \textit{in vivo} experiments are not done using a + \gls{doe}-based approach; however, a \gls{doe} is perfectly natural for a + large mouse study where one naturally desires to use as few animals as + possible. +\item The \gls{dms} system is be compatible with static bioreactors such as the + G-Rex which has been adopted throughout the cell therapy industry. Thus this + technology can be easily incorporated into existing cell therapy process that + are performed at scale. +\item We analyzed our system using a multiomics approach, which will enable the + discovery of novel biomarkers to be used as \glspl{cqa}. While this approach + has been applied to T cells previously, it has not been done in the context of + a large \gls{doe}-based model. This approach is aware of the whole design + space, and thus enables greater understanding of process parameters and their + effect on cell phenotype. +\end{itemize} + \chapter{aim 1}\label{aim1} \section{introduction}