ADD a bunch of T cell quality stuff
This commit is contained in:
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@ -2275,6 +2275,70 @@ CONCLUSIONS: We developed a simplified, semi-closed system for the initial selec
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publisher = {Elsevier {BV}},
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publisher = {Elsevier {BV}},
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}
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}
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@Article{Turtle2009,
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author = {Cameron J. Turtle and Hillary M. Swanson and Nobuharu Fujii and Elihu H. Estey and Stanley R. Riddell},
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journal = {Immunity},
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title = {A Distinct Subset of Self-Renewing Human Memory {CD}8+ T Cells Survives Cytotoxic Chemotherapy},
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year = {2009},
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month = {nov},
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number = {5},
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pages = {834--844},
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volume = {31},
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doi = {10.1016/j.immuni.2009.09.015},
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publisher = {Elsevier {BV}},
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}
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@Article{Donia2012,
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author = {M. Donia and N. Junker and E. Ellebaek and M. H. Andersen and P. T. Straten and I. M. Svane},
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journal = {Scandinavian Journal of Immunology},
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title = {Characterization and Comparison of `Standard' and `Young' Tumour-Infiltrating Lymphocytes for Adoptive Cell Therapy at a Danish Translational Research Institution},
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year = {2012},
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month = {jan},
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number = {2},
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pages = {157--167},
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volume = {75},
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doi = {10.1111/j.1365-3083.2011.02640.x},
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publisher = {Wiley},
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}
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@Article{Sheih2020,
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author = {Alyssa Sheih and Valentin Voillet and Laïla-Aïcha Hanafi and Hannah A. DeBerg and Masanao Yajima and Reed Hawkins and Vivian Gersuk and Stanley R. Riddell and David G. Maloney and Martin E. Wohlfahrt and Dnyanada Pande and Mark R. Enstrom and Hans-Peter Kiem and Jennifer E. Adair and Raphaël Gottardo and Peter S. Linsley and Cameron J. Turtle},
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journal = {Nature Communications},
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title = {Clonal kinetics and single-cell transcriptional profiling of {CAR}-T cells in patients undergoing {CD}19 {CAR}-T immunotherapy},
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year = {2020},
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month = {jan},
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number = {1},
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volume = {11},
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doi = {10.1038/s41467-019-13880-1},
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publisher = {Springer Science and Business Media {LLC}},
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}
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@Article{Lee2013,
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author = {Agnes Fermin Lee and Peter A. Sieling and Delphine J. Lee},
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journal = {{OncoImmunology}},
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title = {Immune correlates of melanoma survival in adoptive cell therapy},
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year = {2013},
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month = {feb},
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number = {2},
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pages = {e22889},
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volume = {2},
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doi = {10.4161/onci.22889},
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publisher = {Informa {UK} Limited},
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}
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@Article{Wang2013,
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author = {Weirong Wang and Chunfang Yan and Jiye Zhang and Rong Lin and Qinqin Lin and Lina Yang and Feng Ren and Jianfeng Zhang and Meixi Ji and Yanxiang Li},
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journal = {Apoptosis},
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title = {{SIRT}1 inhibits {TNF}-$\upalpha$-induced apoptosis of vascular adventitial fibroblasts partly through the deacetylation of {FoxO}1},
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year = {2013},
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month = {mar},
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number = {6},
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pages = {689--701},
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volume = {18},
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doi = {10.1007/s10495-013-0833-7},
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publisher = {Springer Science and Business Media {LLC}},
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}
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@Comment{jabref-meta: databaseType:bibtex;}
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@Comment{jabref-meta: databaseType:bibtex;}
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@Comment{jabref-meta: grouping:
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@Comment{jabref-meta: grouping:
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155
tex/thesis.tex
155
tex/thesis.tex
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@ -65,8 +65,11 @@
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\newacronym{tcr}{TCR}{T cell receptor}
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\newacronym{tcr}{TCR}{T cell receptor}
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\newacronym{act}{ACT}{adoptive cell therapies}
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\newacronym{act}{ACT}{adoptive cell therapies}
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\newacronym{qc}{QC}{quality control}
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\newacronym{qc}{QC}{quality control}
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\newacronym{tn}{T\textsubscript{n}}{naive T cell}
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\newacronym{tcm}{T\textsubscript{cm}}{central memory T cell}
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\newacronym{tcm}{T\textsubscript{cm}}{central memory T cell}
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\newacronym{tscm}{T\textsubscript{scm}}{stem-memory T cell}
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\newacronym{tscm}{T\textsubscript{scm}}{stem-memory T cell}
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\newacronym{tem}{T\textsubscript{em}}{effector-memory T cell}
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\newacronym{teff}{T\textsubscript{eff}}{effector T cell}
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\newacronym{car}{CAR}{chimeric antigen receptor}
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\newacronym{car}{CAR}{chimeric antigen receptor}
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\newacronym[longplural={monoclonal antibodies}]{mab}{mAb}{monoclonal antibody}
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\newacronym[longplural={monoclonal antibodies}]{mab}{mAb}{monoclonal antibody}
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\newacronym{ecm}{ECM}{extracellular matrix}
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\newacronym{ecm}{ECM}{extracellular matrix}
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@ -695,54 +698,6 @@ are almost 1000 clinical trials using \gls{car} T cells.
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% TODO there are other T cells like virus-specific T cells and gd T cells, not
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% TODO there are other T cells like virus-specific T cells and gd T cells, not
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% that they matter...
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% that they matter...
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\subsection*{current T cell manufacturing technologies}
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Despite these success of T cell therapies (especially \gls{car} T cell
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therapies) they are constrained by an expensive and difficult-to-scale
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manufacturing process\cite{Roddie2019, Dwarshuis2017}.
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Of critical concern, state-of-the-art manufacturing techniques focus only on
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Signal 1 and Signal 2-based activation via \acd{3} and \acd{28} \glspl{mab},
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typically presented on a microbead (Invitrogen Dynabead, Miltenyi MACS beads) or
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nanobead (Miltenyi TransACT), but also in soluble forms in the case of antibody
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tetramers (Expamer)\cite{Wang2016, Piscopo2017, Roddie2019, Bashour2015}. These
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strategies overlook many of the signaling components present in the secondary
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lymphoid organs where T cells normally expand. Typically, T cells are activated
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under close cell-cell contact via \glspl{apc} such as \glspl{dc}, which present
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peptide-\glspl{mhc} to T cells as well as a variety of other costimulatory
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signals. These close quarters allow for efficient autocrine/paracrine signaling
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among the expanding T cells, which secrete gls{il2} and other cytokines to
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assist their own growth.
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% Additionally, the lymphoid tissues are comprised of
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% \gls{ecm} components such as collagen, which provide signals to upregulate
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% proliferation, cytokine production, and pro-survival pathways\cite{Gendron2003,
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% Ohtani2008, Boisvert2007, Ben-Horin2004}.
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A variety of solutions have been proposed to make the T cell expansion process
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more physiological. One strategy is to use modified feeder cell cultures to
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provide activation signals similar to those of \glspl{dc}\cite{Forget2014}.
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While this has the theoretical capacity to mimic several key components of the
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lymph node, it is hard to reproduce on a large scale due to the complexity and
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inherent variability of using cell lines in a fully \gls{gmp}-compliant manner.
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Others have proposed biomaterials-based solutions to circumvent this problem,
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including lipid-coated microrods\cite{Cheung2018}, 3D-scaffolds via either
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Matrigel\cite{Rio2018} or 3d-printed lattices\cite{Delalat2017}, ellipsoid
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beads\cite{meyer15_immun}, and \gls{mab}-conjugated \gls{pdms}
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beads\cite{Lambert2017} that respectively recapitulate the cellular membrane,
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large interfacial contact area, 3D-structure, or soft surfaces T cells normally
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experience \textit{in vivo}. While these have been shown to provide superior
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expansion compared to traditional microbeads, no method has been able to show
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preferential expansion of functional memory and CD4 T cell populations.
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Generally, T cells with a lower differentiation state such as memory cells have
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been shown to provide superior anti-tumor potency, presumably due to their
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higher potential to replicate, migrate, and engraft, leading to a long-term,
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durable response\cite{Xu2014, Gattinoni2012, Fraietta2018, Gattinoni2011}.
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Likewise, CD4 T cells are similarly important to anti-tumor potency due to their
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cytokine release properties and ability to resist exhaustion\cite{Wang2018,
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Yang2017}, and no method exists to preferentially expand the CD4 population
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compared to state-of-the-art systems.
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\subsection{cell sources in T cell manufacturing}
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\subsection{cell sources in T cell manufacturing}
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T cells for cell manufacturing can be obtained broadly via two paradigms:
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T cells for cell manufacturing can be obtained broadly via two paradigms:
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@ -830,12 +785,104 @@ cells\cite{Gerdemann2011}.
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\subsection{overview of T cell quality}
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\subsection{overview of T cell quality}
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% memory
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T cells are highly heterogeneous and can exist in a variety of states and
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% CD4
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subtypes, many of which can be measured (at least indirectly) though biomarkers
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% viability
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such as cell surface proteins. Identifying and understanding these biomarkers
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% degranulation
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are the basis for \glspl{cqa} which can be used to for process control, release
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% RCV testing
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criteria, and initial cell source screening.
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% cytokine secretion
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One of the most important dimensions of T cell quality is that of
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differentiation. T cells begin their life in circulation (eg after they exit the
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thymus) as naive T cells. When they become activated in the secondary lymph node
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organs, they differentiate from \gls{tn} to \gls{tscm}, \gls{tcm}, \gls{tem},
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and finally \gls{teff}\cite{Gattinoni2012}. Subtypes earlier in this process are
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generally called `memory' or `memory-like' cells (eg \gls{tscm} and \gls{tcm}),
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and have been shown to have increased potency toward a variety of tumors,
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presumably due to their higher capacity for self-renewal and replication,
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enhanced migratory capacity, and/or increased engraftment potential\cite{Xu2014,
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Gattinoni2012, Fraietta2018, Gattinoni2011, Turtle2009}. The capacity for
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self-renewal is especially important for T cells therapies, as evidenced by the
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fact that \gls{til} therapies with longer telomeres tend to work
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better\cite{Donia2012}. Additionally, clonal diversity decreases following the
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infusion of \gls{car} T cell therapies, which demonstrates that only a few
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clones are self-renewing and therefore responsible for the overall
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response\cite{Sheih2020}. Memory T cells can be quantified easily using surface
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markers such as CD62L, CCR7, CD27, CD45RA, and CD45RO. Furthermore, memory
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markers are inversely related to exhaustion markers which are negatively
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associated with clinical outcomes\cite{Lee2013}. These cells in particular are
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seen in patients with chronic immune activation such as patients with chronic
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cancers.
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In addition to memory, the other major axis by which T cells may be classified
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is the CD4/CD8 ratio. CD4 (`helper') T cells are responsible for secreting
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cytokines which coordinate the immune response while CD8 (`killer') T cell
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responsible for killing tumor or infected cells using specialized lytic enzymes.
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Since CD8 T cells actually perform the killing function, it seems intuitive that
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CD8 T cells would be most important for anti-tumor immunotherapies. However, in
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mouse models with glioblastoma, survival was negatively impacted when CD4 T
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cells were removed\cite{Wang2018}. Furthermore, CD4 T cells have been shown to
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have cytotoxic properties on their own and also show resistance to T cell
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exhaustion compared to CD8 T cells\cite{Yang2017}. While T cell products with a
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defined ratio of CD4 and CD8 T cells have been utilized, they are more expensive
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than products with undefined ratios as the T cells need to be sorted and
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recombined, adding additional complexity\cite{Turtle2016}.
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While less of a focus in this dissertation, other quality markers exists to
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assess the overall killing potential and safety of the T cell product. Numerous
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methods exists to detect the killing capacity of \gls{car} T cells, many of
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which involve either measuring the lysis of a target cell using a dye or a
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radioactive tracer, by measuring the degranulation of the T cells themselves, or
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by measuring a cytokine that is secreted upon T cell activation and killing such
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as \gls{ifng}. Furthermore, the viability of T cells may be assessed using a
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number of methods, including exclusion dyes such as \gls{aopi} or a functional
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assay to detect metabolism. Finally, for the purposes of safety, T cell products
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using retro- or lentiviral vectors as their means of gene-editing must be tested
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for replication competent vectors\cite{Wang2013} and for contamination via
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bacteria or other pathogens.
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\subsection*{current T cell manufacturing technologies}
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Despite these success of T cell therapies (especially \gls{car} T cell
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therapies) they are constrained by an expensive and difficult-to-scale
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manufacturing process\cite{Roddie2019, Dwarshuis2017}.
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Of critical concern, state-of-the-art manufacturing techniques focus only on
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Signal 1 and Signal 2-based activation via \acd{3} and \acd{28} \glspl{mab},
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typically presented on a microbead (Invitrogen Dynabead, Miltenyi MACS beads) or
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nanobead (Miltenyi TransACT), but also in soluble forms in the case of antibody
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tetramers (Expamer)\cite{Wang2016, Piscopo2017, Roddie2019, Bashour2015}. These
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strategies overlook many of the signaling components present in the secondary
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lymphoid organs where T cells normally expand. Typically, T cells are activated
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under close cell-cell contact via \glspl{apc} such as \glspl{dc}, which present
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peptide-\glspl{mhc} to T cells as well as a variety of other costimulatory
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signals. These close quarters allow for efficient autocrine/paracrine signaling
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among the expanding T cells, which secrete gls{il2} and other cytokines to
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assist their own growth.
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A variety of solutions have been proposed to make the T cell expansion process
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more physiological. One strategy is to use modified feeder cell cultures to
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provide activation signals similar to those of \glspl{dc}\cite{Forget2014}.
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While this has the theoretical capacity to mimic several key components of the
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lymph node, it is hard to reproduce on a large scale due to the complexity and
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inherent variability of using cell lines in a fully \gls{gmp}-compliant manner.
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Others have proposed biomaterials-based solutions to circumvent this problem,
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including lipid-coated microrods\cite{Cheung2018}, 3D-scaffolds via either
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Matrigel\cite{Rio2018} or 3d-printed lattices\cite{Delalat2017}, ellipsoid
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beads\cite{meyer15_immun}, and \gls{mab}-conjugated \gls{pdms}
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beads\cite{Lambert2017} that respectively recapitulate the cellular membrane,
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large interfacial contact area, 3D-structure, or soft surfaces T cells normally
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experience \textit{in vivo}. While these have been shown to provide superior
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expansion compared to traditional microbeads, no method has been able to show
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preferential expansion of functional memory and CD4 T cell populations.
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Generally, T cells with a lower differentiation state such as memory cells have
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been shown to provide superior anti-tumor potency, presumably due to their
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higher potential to replicate, migrate, and engraft, leading to a long-term,
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durable response\cite{Xu2014, Gattinoni2012, Fraietta2018, Gattinoni2011}.
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Likewise, CD4 T cells are similarly important to anti-tumor potency due to their
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cytokine release properties and ability to resist exhaustion\cite{Wang2018,
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Yang2017}, and no method exists to preferentially expand the CD4 population
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compared to state-of-the-art systems.
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\subsection*{integrins and T cell signaling}
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\subsection*{integrins and T cell signaling}
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