ADD spade gating figure

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Nathan Dwarshuis 2021-07-30 13:35:31 -04:00
parent d2ebb84d91
commit 35850690e8
2 changed files with 9275 additions and 31 deletions

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@ -2723,8 +2723,6 @@ T cells were stained using a \product{34 \gls{cytof} marker
used according to the manufacturers instructions. \numrange{2e6}{3e6} stained used according to the manufacturers instructions. \numrange{2e6}{3e6} stained
cells per group were analyzed on a Fluidigm Helios. cells per group were analyzed on a Fluidigm Helios.
% FIGURE add the spade gating diagram from the paper
Unbiased cell clusters were obtained using \gls{spade} analysis by pooling three Unbiased cell clusters were obtained using \gls{spade} analysis by pooling three
representative \gls{fcs} files and running the \gls{spade} pipeline with k-means representative \gls{fcs} files and running the \gls{spade} pipeline with k-means
clustering (k = 100), arcsinh transformation with cofactor 5, density clustering (k = 100), arcsinh transformation with cofactor 5, density
@ -2829,36 +2827,18 @@ are fundamentally altered by changing the number of \glspl{dms} temporally.
\label{fig:add_rem} \label{fig:add_rem}
\end{figure*} \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 \begin{figure*}[ht!]
phenotypes, we clearly see that the number of lower differentiated cells is much \begingroup
higher in the \textit{no change} or \textit{removed} groups compared to the
\textit{added} group (\cref{fig:spade_quant}). Furthermore, the \textit{removed} \includegraphics{../figures/spade_gates.png}
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 \endgroup
these cells were \cdp{8} cells. When analyzing the same data using \gls{tsne}, \caption[SPADE Gating Strategy]
we observe a higher fraction of CD27 and lower fraction of CD45RO in the the {Gating strategy for quantifying early-differentiated T cells via
\textit{removed} group (\cref{fig:spade_tsne_all}). When manually gating on the \gls{spade}.}
CD27+CD45RO- population, we see there is higher density in the \textit{removed} \label{fig:spade_gates}
group, indicating more of this population (\cref{fig:spade_tsne_stem}). \end{figure*}
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 this needs some better annotations
% TODO put the quant graph before the tsne stuff % TODO put the quant graph before the tsne stuff
@ -2890,6 +2870,38 @@ do the inverse.
\label{fig:spade} \label{fig:spade}
\end{figure*} \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,fig:spade_gates}). 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.
\subsection{blocking integrin binding does not alter expansion or phenotype} \subsection{blocking integrin binding does not alter expansion or phenotype}
% BACKGROUND add background into why integrins are important % BACKGROUND add background into why integrins are important