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ADD result for spade stuff

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Nathan Dwarshuis 2021-07-28 17:59:19 -04:00
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tex/thesis.tex
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@ -40,6 +40,8 @@
\renewcommand{\glossarysection}[2][]{} % remove glossary title
\makeglossaries
\newacronym{act}{ACT}{adoptive cell therapies}
\newacronym{tcm}{T\textsubscript{cm}}{central memory T cell}
\newacronym{tscm}{T\textsubscript{scm}}{stem-memory T cell}
\newacronym{car}{CAR}{chimeric antigen receptor}
\newacronym[longplural={monoclonal antibodies}]{mab}{mAb}{monoclonal antibody}
\newacronym{ecm}{ECM}{extracellular matrix}
@ -2083,7 +2085,7 @@ provide these benefits.
\section{introduction}
\section{methods}
\subsection{collagenase digestion}
\subsection{DMSs temporal modulation}
% TODO The concentration for the surface marker cleavage experiment was much
% higher, if that matters
@ -2097,6 +2099,10 @@ media normally used to feed the cells during the regular media addition cycle at
day 4. Cultures were then incubated as described in \cref{sec:tcellculture}, and
the \glspl{dms} were verified to have been digested after \SI{24}{\hour}.
Adding \gls{dms} was relatively much simpler; the number of \gls{dms} used per
area on day 0 was scaled up by 3 on day 4 to match the change from a 96 well
plate to a 24 well plate, effectively producing a constant activation signal.
\subsection{mass cytometry and clustering analysis}
T cells were stained using a \product{34 \gls{cytof} marker
@ -2144,6 +2150,22 @@ To block soluble \gls{il15}, we supplemented analogously with
\subsection{adding or removing DMSs alters expansion and phenotype}
% TODO state what collagenase actually targets
We hypothesized that adding or removing \gls{dms} in the middle of an active
culture would alter the activation signal and hence the growth trajectory and
phenotype of T cells. While adding \glspl{dms} was simple, the easiest way to
remove \glspl{dms} was to use enzymatic digestion. Collagenase is an enzyme that
specifically targets the blabla domain on collagen. Since our \glspl{dms} are
composed of porcine-derived collagen, this enzyme should target the \gls{dms}
while sparing the cells. We tested this specific hypothesis using either
\gls{colb}, \gls{cold} or \gls{hbss}, and stained the cells using a typical
marker panel to assess if any of the markers were cleaved off by the enzyme
which would bias our final readout. We observed that the marker histograms in
the \gls{cold} group were similar to that of the buffer group, while the
\gls{colb} group visibly lowered CD62L and CD4, indicating partial
enzymatic cleavage (\cref{fig:collagenase_fx}). Based on this result, we used
\gls{cold} moving forward.
% TODO this figure is tall and skinny like me
\begin{figure*}[ht!]
\begingroup
@ -2157,6 +2179,22 @@ To block soluble \gls{il15}, we supplemented analogously with
\label{fig:collagenase_fx}
\end{figure*}
When either adding more \glspl{dms}, removing \glspl{dms} using \gls{cold}, or
doing nothing, we observed that, counterintuitively, cell growth seemed to be
inhibited in the \textit{added} group while the cells seemed to grow faster in
the \textit{removed} group relative to the \textit{no change} group
(\cref{fig:add_rem_growth}). Additionally, the \textit{removed} group seemed to
have a negative growth rate in the final \SI{4}{\day} of culture, indicating
that either the lack activation signal had slowed the cell growth down or that
the cells were growing fast enough to outpace the media feeding schedule. The
viability was the same between all groups, indicating that this negative growth
rate and the lower growth rate in the \textit{added} group were likely not due
to cell death (\cref{fig:add_rem_viability}). Interestingly, the \textit{added}
group had significantly higher \pth{} cells compared to the \textit{no change}
group, and the inverse was true for the \textit{removed} group
(\cref{fig:add_rem_cd4}). These results show that the growth rate and phenotype
are fundamentally altered by changing the number of \glspl{dms} temporally.
% TODO this figure still says "carrier"
\begin{figure*}[ht!]
\begingroup
@ -2178,7 +2216,39 @@ To block soluble \gls{il15}, we supplemented analogously with
\label{fig:add_rem}
\end{figure*}
We next asked what the effect of removing the \glspl{dms} would have on other
phenotypes, specifically \gls{tcm} and \gls{tscm} cells. To this end we stained
cells using a 34-marker mass cytometry panel and analyzed them using a Fluidigm
Helios. After pooling the \gls{fcs} file events from each group and analyzing
them via \gls{spade} we see that there is a strong bifurcation of CD4 and CD8 T
cells. We also observe that among CD27, CD45RA, and CD45RO (markers commonly
used to identify \gls{tcm} and \gls{tscm} subtypes) we see clear `metaclusters'
composed of individual \gls{spade} clusters which are high for that marker
(\cref{fig:spade_msts}). We then gated each of these metaclusters according to
their marker levels and assigned them to one of three phenotypes for both the
CD4 and CD8 compartments: \gls{tcm} (high CD45RO, low CD45RA, high CD27),
\gls{tscm} (low CD45RO, high CD45RA, high CD27), and `transitory' \gls{tscm}
cells (mid CD45RO, mid CD45RA, high CD27). Together these represent low
differentiated cells which should be highly potent as anti-tumor therapies.
When quantifying the number of cells from each experimental group in these
phenotypes, we clearly see that the number of lower differentiated cells is much
higher in the \textit{no change} or \textit{removed} groups compared to the
\textit{added} group (\cref{fig:spade_quant}). Furthermore, the \textit{removed}
group had a much higher fraction of \gls{tscm} cells compared to the \textit{no
change} group, which had more `transitory \gls{tscm} cells'. The majority of
these cells were \cdp{8} cells. When analyzing the same data using \gls{tsne},
we observe a higher fraction of CD27 and lower fraction of CD45RO in the the
\textit{removed} group (\cref{fig:spade_tsne_all}). When manually gating on the
CD27+CD45RO- population, we see there is higher density in the \textit{removed}
group, indicating more of this population (\cref{fig:spade_tsne_stem}).
Together, these data indicate that removing \glspl{dms} at lower timepoints
leads to potentially higher expansion, lower \pthp{}, and higher fraction of
lower differentiated T cells such as \gls{tscm}, and adding \gls{dms} seems to
do the inverse.
% TODO this needs some better annotations
% TODO put the quant graph before the tsne stuff
\begin{figure*}[ht!]
\begingroup