From 35850690e8815ea7c2d39cb19a74cad14a372fd1 Mon Sep 17 00:00:00 2001 From: ndwarshuis Date: Fri, 30 Jul 2021 13:35:31 -0400 Subject: [PATCH] ADD spade gating figure --- figures/spade_gates.svg | 9232 +++++++++++++++++++++++++++++++++++++++ tex/thesis.tex | 74 +- 2 files changed, 9275 insertions(+), 31 deletions(-) create mode 100644 figures/spade_gates.svg diff --git a/figures/spade_gates.svg b/figures/spade_gates.svg new file mode 100644 index 0000000..564db00 --- /dev/null +++ b/figures/spade_gates.svg @@ -0,0 +1,9232 @@ + + + + + + + + + + + + image/svg+xml + + + + + + + + diff --git a/tex/thesis.tex b/tex/thesis.tex index f2d8562..cfad655 100644 --- a/tex/thesis.tex +++ b/tex/thesis.tex @@ -2723,8 +2723,6 @@ T cells were stained using a \product{34 \gls{cytof} marker used according to the manufacturer’s instructions. \numrange{2e6}{3e6} stained 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 representative \gls{fcs} files and running the \gls{spade} pipeline with k-means 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} \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. +\begin{figure*}[ht!] + \begingroup + + \includegraphics{../figures/spade_gates.png} + + \endgroup + \caption[SPADE Gating Strategy] + {Gating strategy for quantifying early-differentiated T cells via + \gls{spade}.} + \label{fig:spade_gates} +\end{figure*} % TODO this needs some better annotations % TODO put the quant graph before the tsne stuff @@ -2890,6 +2870,38 @@ do the inverse. \label{fig:spade} \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} % BACKGROUND add background into why integrins are important