ADD a bunch of discussion stuff

2021-07-25 22:53:14 -04:00 · 2021-07-25 22:53:14 -04:00 · 3b28dc5612
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 \section{discussion}
 % TODO this is fluffy
 We have developed a T cell expansion system that recapitulates key features of
 the in vivo lymph node microenvironment using DMSs functionalized with
 activating mAbs. This strategy provided superior expansion with higher number of
 naïve/memory and CD4+ T cells compared to state-of-the-art microbead technology
 (Figure 2). Other groups have used biomaterials approaches to mimic the in vivo
 microenvironment13–15,17,34; however, to our knowledge this is the first system
 that specifically drives naïve/memory and CD4+ T cell formation in a scalable,
 potentially bioreactor-compatible manufacturing process.
 Memory and naïve T cells have been shown to be important clinically. Compared to
 effectors, they have a higher proliferative capacity and are able to engraft for
 months; thus they are able to provide long-term immunity with smaller
 doses19,35. Indeed, less differentiated T cells have led to greater survival
 both in mouse tumor models and human patients20,36,37. Furthermore, clinical
 response rates have been positively correlated with T cell expansion, implying
 that highly-proliferative naïve and memory T cells are a significant
 contributor18,38. Circulating memory T cells have also been found in complete
 responders who received CAR T cell therapy39.
 Similarly, CD4 T cells have been shown to play an important role in CAR T cell
 immunotherapy. It has been shown that CAR T doses with only CD4 or a mix of CD4
 and CD8 T cells confer greater tumor cytotoxicity than only CD8 T cells22,40.
 There are several possible reasons for these observations. First, CD4 T cells
 secrete proinflammatory cytokines upon stimulation which may have a synergistic
 effect on CD8 T cells. Second, CD4 T cells may be less prone to exhaustion and
 may more readily adopt a memory phenotype compared to CD8 T cells22. Third, CD8
 T cells may be more susceptible than CD4 T cells to dual stimulation via the CAR
 and endogenous T Cell Receptor (TCR), which could lead to overstimulation,
 exhaustion, and apoptosis23. Despite evidence for the importance of CD4 T cells,
 more work is required to determine the precise ratios of CD4 and CD8 T cell
 subsets to be included in CAR T cell therapy given a disease state.
 % TODO this might be more appropriate for aim 2b where I actually talk about
 % the signaling and why this might matter
 There are several plausible explanations for the observed phenotypic differences
 between beads and DMSs. First, the DMSs are composed of a collagen derivative
 (gelatin); collagen has been shown to costimulate activated T cells via α1β1 and
 α2β1 integrins, leading to enhanced proliferation, increased IFNγ production,
 and upregulated CD25 (IL2Rα) surface expression8,10,11,41,42. Second, there is
 evidence that providing a larger contact area for T cell activation provides
 greater stimulation16,43; the DMSs have a rougher interface than the 5 µm
 magnetic beads, and thus could facilitate these larger contact areas. Third, the
 DMSs may allow the T cells to cluster more densely compared to beads, as
 evidenced by the large clusters on the outside of the DMSs (Figure 1f) as well
 as the significant fraction of DMSs found within their interiors (Supplemental
 Figure 2a and b). This may alter the local cytokine environment and trigger
 different signaling pathways. Particularly, IL15 and IL21 are secreted by T
 cells and known to drive memory phenotype44–46. We noted that the IL15 and IL21
 concentration was higher in a majority of samples when comparing beads and DMSs
 across multiple timepoints (Supplemental Figure 18) in addition to many other
 cytokines. IL15 and IL21 are added exogenously to T cell cultures to enhance
 memory frequency,45,47 and our data here suggest that the DMSs are better at
 naturally producing these cytokines and limiting this need. Furthermore, IL15
 unique signals in a trans manner in which IL15 is presented on IL15R to
 neighboring cells48. The higher cell density in the DMS cultures would lead to
 more of these trans interactions, and therefore upregulate the IL15 pathway and
 lead to more memory T cells.
 % TODO this mentions the DOE which is in the next aim
 When analyzing all our experiments comprehensively using causal inference, we
 found that all three of our responses were significantly increased when
 controlling for covariates (Figure 3, Table 2). By extension, this implies that
 not only will DMSs lead to higher fold change overall, but also much higher fold
 change in absolute numbers of memory and CD4+ T cells. Furthermore, we found
 that using a Grex bioreactor is detrimental to fold change and memory percent
 while helping CD4+. Since there are multiple consequences to using a Grex
 compared to tissue-treated plates, we can only speculate as to why this might be
 the case. Firstly, when using a Grex we did not expand the surface area on which
 the cells were growing in a comparable way to that of polystyrene plates. In
 conjunction with our DOE data {Figure X} which shows that high DMS
 concentrations favor CD4+ and don’t favor memory fraction, one possible
 explanation is that the T cells spent longer times in highly activating
 conditions (since the beads and DMSs would have been at higher per-area
 concentrations in the Grex vs polystyrene plates). Furthermore, the simple fact
 that the T cells spent more time at high surface densities could simply mean
 that the T cells didn’t expands as much due to spacial constraints. This would
 all be despite the fact that Grex bioreactors are designed to lead to better T
 cell expansion due to their gas-permeable membranes and higher media-loading
 capacities. If anything, our data suggests we were using the bioreactor
 sub-optimally, and the hypothesized causes for why our T cells did not expand
 could be verified with additional experiments varying the starting cell density
 and/or using larger bioreactors.
 A key question in the space of cell manufacturing is that of donor variability.
 To state this precisely, this is a second order interaction effect that
 represents the change in effect of treatment (eg bead vs DMS) given the donor.
 While our meta-analysis was relatively large compared to many published
 experiments usually seen for technologies at this developmental stage, we have a
 limited ability in answering this question. We can control for donor as a
 covariate, and indeed our models show that many of the donor characteristics are
 strongly associated with each response on average, but these are first order
 effects and represent the association of age, gender, demographic, etc given
 everything else in the model is held constant. Second order interactions require
 that our treatments be relatively balanced and random across each donor, which
 is a dubious assumption for our dataset. However, this can easily be solved by
 performing more experiments with these restrictions in mind, which will be a
 subject of our future work.
 Furthermore, this dataset offers an interesting insight toward novel hypothesis
 that might be further investigated. One limitation of our dataset is that we
 were unable to investigate the effects of time using a method such as
 autoregression, and instead relied on aggregate measures such as the total
 amount of a reagent added over the course of the expansion. Further studies
 should be performed to investigate the temporal relationship between phenotype,
 cytokine concentrations, feed rates, and other measurements which may perturb
 cell cultures, as this will be the foundation of modern process control
 necessary to have a fully-automated manufacturing system.
 In addition to larger numbers of potent T cells, other advantages of our DMS
 approach are that the DMSs are large enough to be filtered (approximately 300
 µm) using standard 40 µm cell filters or similar. If the remaining cells inside
 that DMSs are also desired, digestion with dispase or collagenase may be used.
 Collagenase D may be selective enough to dissolve the DMSs yet preserve surface
 markers which may be important to measure as critical quality attributes CQAs
 {Figure X}. Furthermore, our system should be compatible with
 large-scale static culture systems such as the G-Rex bioreactor or perfusion
 culture systems, which have been previously shown to work well for T cell
 expansion12,50,51. The microcarriers used to create the DMSs also have a
 regulatory history in human cell therapies that will aid in clinical
 translation.; they are already a component in an approved retinal pigment
 epithelial cell product for Parkinson’s patients, and are widely available in 30
 countries26.
 It is important to note that all T cell cultures in this study were performed up
 to 14 days. Others have demonstrated that potent memory T cells may be obtained
 simply by culturing T cells as little as 5 days using traditional beads30. It is
 unknown if the naïve/memory phenotype of our DMS system could be further
 improved by reducing the culture time, but we can hypothesize that similar
 results would be observed given the lower number of doublings in a 5 day
 culture. We should also note that we investigated one subtype (\ptmem{}) in
 this study. Future work will focus on other memory subtypes such as tissue
 resident memory and stem memory T cells, as well as the impact of using the DMS
 system on the generation of these subtypes.
 % TODO this sounds sketchy
 Another advantage is that the DMS system appears to induce a faster growth rate
 of T cells given the same IL2 concentration compared to beads (Supplemental
 Figure 8) along with retaining naïve and memory phenotype. This has benefits in
 multiple contexts. Firstly, some patients have small starting T cell populations
 (such as infants or those who are severely lymphodepleted), and thus require
 more population doublings to reach a usable dose. Our data suggests the time to
 reach this dose would be reduced, easing scheduling a reducing cost. Secondly,
 the allogeneic T cell model would greatly benefit from a system that could
 create large numbers of T cells with naïve and memory phenotype. In contrast to
 the autologous model which is currently used for Kymriah and Yescarta,
 allogeneic T cell therapy would reduce cost by spreading manufacturing expenses
 across many doses for multiple patients52. Since it is economically advantageous
 to grow as many T cells as possible in one batch in the allogeneic model
 (reduced start up and harvesting costs, fewer required cell donations), the DMSs
 offer an advantage over current technology.
 % TODO this is already stated in the innovation section
 It should be noted that while we demonstrate a method providing superior
 performance compared to bead-based expansion, the cell manufacturing field would
 tremendously benefit from simply having an alternative to state-of-the-art
 methods. The patents for bead-based expansion are owned by few companies and
 licensed accordingly; having an alternative would provide more competition in
 the market, reducing costs and improving access for academic researchers and
 manufacturing companies.
 % TODO this isn't relevent to this aim but should be said somewhere
 Finally, while we have demonstrated the DMS system in the context of CAR T
 cells, this method can theoretically be applied to any T cell immunotherapy
 which responds to anti-CD3/CD28 mAb and cytokine stimulation. These include
 tumor infiltrating lymphocytes (TILs), virus-specific T cells (VSTs), T cells
 engineered to express γδTCR (TEGs), γδ T cells, T cells with transduced-TCR, and
 CAR-TCR T cells53–58. Similar to CD19-CARs used in liquid tumors, these T cell
 immunotherapies would similarly benefit from the increased proliferative
 capacity, metabolic fitness, migration, and engraftment potential characteristic
 of naïve and memory phenotypes59–61. Indeed, since these T cell immunotherapies
 are activated and expanded with either soluble mAbs or bead-immobilized mAbs,
 our system will likely serve as a drop-in substitution to provide these
 benefits.
 \chapter{aim 2}\label{aim2}
 \section{introduction}