tagc_trec/presentation.tex

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%Page de titre:
\title[]{\emoji{dna} TREC mediated oncogenesis in human immature T lymphoid malignancies
preferentially involves \textit{ZFP36L2} --- Molecular Cancer}

\author{Dr. Thomas Steimlé}

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    \centering
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    \hspace*{5cm}
    \includegraphics[height=1.5cm]{Images/logo_tagc.png}
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\date{\today}


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\begin{document}

\begin{frame}
\maketitle
\thispagestyle{empty}

\end{frame}


\begin{frame}{\emoji{drop-of-blood} Background --- Thymopoiesis}
  \begin{itemize}
    \item<1-> During thymopoiesis (HSC $\Rightarrow$ T-cell), the phenotypic diversity of 
    the antigen receptor (TCR) is acquired.
  \end{itemize}
  \centering
    \includegraphics<1>[width=.5\textwidth]{Images/dev_thym.png}
    \includegraphics<2>[width=.6\textwidth]{Images/Tcr_str.png}
\end{frame}

\begin{frame}{\emoji{drop-of-blood} Background --- V(D)J recombination}
  \begin{itemize}
    \item<1-> This process involves a series of genome recombination of the different TCR loci 
    followed by \alert{proliferation and selection of functionnal non self-reacting TCR}.
  \end{itemize}
  \centering
    \includegraphics<1>[width=.7\textwidth]{Images/MaturLt.png}
    \includegraphics<2>[width=.7\textwidth]{Images/TCRBschema.jpg}
\end{frame}

\begin{frame}{\emoji{dna} Background --- V(D)J recombination}
  \begin{columns}
    \begin{column}{.5\textwidth}
      \begin{itemize}
        \item V(D)J recombination is a \alert{threat to genomic stability}, 
        prone to induce \alert{DSB occurring in genes outside of the TCR loci}, 
        followed by erroneous repair resultating in SV.
        \item This oncogenetic process is responsible of well known genetic alterations 
        in T-ALL (particulary translocations accountable of ectopic expression of oncogenes 
        \textit{TLX1}, \textit{TAL1} etc\dots)$^1$.

        \footnotetext{
          \tiny
          1. Larmonie, Nicole S D et al. “Breakpoint sites disclose the role of the V(D)J recombination machinery 
          in the formation of T-cell receptor (TCR) and non-TCR associated aberrations in T-cell 
          acute lymphoblastic leukemia.” Haematologica vol. 98,8 (2013): 1173-84
        }
      \end{itemize}
    \end{column}
    \begin{column}{.6\textwidth}
      \begin{figure}
        \centering
        \includegraphics[width=.8\textwidth]{Images/transloc_oncogenes.png}
      \end{figure}
    \end{column}
  \end{columns}
\end{frame}

\begin{frame}{\emoji{dna} Background --- T-cell receptor excision circles (TRECs) }
  \begin{columns}
    \begin{column}{.5\textwidth}
      \begin{figure}
        \includegraphics[width=\textwidth]{Images/trec.png}
      \end{figure}
    \end{column}
    \begin{column}{.5\textwidth}
      \begin{itemize}
        \item During recombination deleted parts of the loci are circulized into TRECs.
        \item Similar to transposons, the reintegration of TRECs has been implicated in the 
        \alert{deregulation or inactivation of targeted genes}.
      \end{itemize}
    \end{column}
  \end{columns}

  \footnotetext{
    \tiny
    Curry, John D et al. “Chromosomal reinsertion of broken RSS ends during T cell development.” The Journal of 
    experimental medicine vol. 204,10 (2007): 2293-303. doi:10.1084/jem.20070583
  }
\end{frame}

{\setbeamercolor{background canvas}{bg=bgturq}
\begin{frame}[c]
  \metroset{block=fill}
  \begin{alertblock}{{\centering \large Hypothesis} }
    \begin{itemize}
      \item In T-ALL, we could find with molecular biology tools insertions of those TRECs.
      \item With the same tools we could also find all the translocations which involves the TCR.
    \end{itemize}
  \end{alertblock}
\end{frame}
}

\begin{frame}{\emoji{triangular-ruler} Material \& Method}
  \begin{itemize}
    \item<1-> We used our extensed collection of \alert{T-ALL samples at diagnostic n = 1533}.
    \item<2-> We designed a NGS capture assay with \alert{capture probes} mapped at multiple parts of de TCR \delta { } locus.
    \item<3-> We developed a specific software to analysed aligned reads and call SV \url{https://github.com/Dr-TSteimle/sv-finder}.
  \end{itemize}
  \begin{figure}
    \centering
    \includegraphics<2>[width=\textwidth]{Images/Probes_TRD.png}
    \includegraphics<3>[width=.8\textwidth]{Images/assemblage.png}
  \end{figure}
\end{frame}

\begin{frame}{\emoji{bar-chart} Results --- \textit{TRD} translocations --- Validation cohort}
  \begin{itemize}
    \item To validate our method, we used a previously published cohort of 264 cases analysed with \alert{\textit{TRD} 
    dual-color FISH probe}$^1$.
    \item \alert{Se = 98.1\%} [95\% CI 96-99] and \alert{Sp = 97.7\%}
    \item The 4 FN cases are in fact TRECs insertions inside \textit{ZFP36L2} 
    that couldn't have been seen with FISH !
  \end{itemize}
  \begin{center}
    \includegraphics[width=.3\textwidth]{Images/confusion.png}
  \end{center}
  \vspace{1cm}
  \footnotetext[1]{
    \tiny
    Le Noir, Sandrine et al. “Extensive molecular mapping of TCRα/δ- and TCRβ-involved 
    chromosomal translocations reveals distinct mechanisms of oncogene activation in T-ALL.” 
    Blood vol. 120,16 (2012): 3298-309. doi:10.1182/blood-2012-04-425488
  }
\end{frame}

\begin{frame}{\emoji{bar-chart} Results --- \textit{TRD} translocations --- Discovery cohort}
  \begin{figure}
    \includegraphics[height=.8\textheight]{Images/distribution.png}
  \end{figure}
\end{frame}

\begin{frame}{\emoji{dart} Results --- \textit{TRD} translocations --- Discovery cohort}
  \Wider[4em]{
    \setlength\columnsep{1pt}
    \vspace{0.8cm}
    \begin{multicols}{3}
      \includegraphics[width=.35\textwidth]{Images/circos_tlx1.png}
      \includegraphics[width=.35\textwidth]{Images/circos_lmo2.png}
      \includegraphics[width=.35\textwidth]{Images/circos_tal1.png}
    \end{multicols}
  }
\end{frame}

\begin{frame}{\emoji{round-pushpin} Results --- \textit{TRD} translocations --- Discovery cohort}
  We confirmed all TRECs insertions with sanger sequencing and OGM.
  \begin{figure}
    \includegraphics[width=\textwidth]{Images/ZFP36L2_lolli.pdf}
    \includegraphics[width=\textwidth]{Images/sanger.png}
    \includegraphics[width=.7\textwidth]{Images/bionano_trec.png}
  \end{figure}
\end{frame}

{\setbeamercolor{background canvas}{bg=bgturq}
\begin{frame}[c]
  \metroset{block=fill}
  \vspace{.5cm}
  \begin{alertblock}{{\centering \large Conclusions} }
    \begin{itemize}
      \item We developed a \alert{highly accurate and sensitive method} that enables precise characterization 
      of \textit{TRD} structural variations. This method can be applied at diagnosis without incurring 
      any additional costs.
      \item Our findings provide confirmation that \alert{recurrent TRECs insertions} are present in cases of 
      T-ALL.
      \item Using our method, we have observed that these recurrent \alert{TRECs insertions predominantly 
      disrupt the \textit{ZFP36L2} gene}.
      \item The tumor suppressor \textit{ZFP36L2} is well-established to be involved in V(D)J recombination, 
      but further clarifications are needed regarding its specific role in oncogenesis. Our findings will 
      help in the characterization of this tumor suppressor.
    \end{itemize}
  \end{alertblock}
\end{frame}
}

\begin{frame}{\emoji{thinking-face} My PhD --- Epigenetic Rationnal}
  \begin{itemize}
    \item<1-> The aforementioned results contribute to the \alert{understanding of the dysregulation of proto-oncogenes} 
    such as \textit{TAL1}, \textit{TLX1} or \textit{TLX3}.
    \item<2-> Despite extensive investigation, \alert{the molecular mechanisms} underlying the dysregulation of these oncogenes, 
    \alert{remain elusive in many cases}. 
    \item<3-> It has been demonstrated that \alert{tumor cells acquire enhancers}\footnotemark[1] through intergenic 
    sequence mutations that enable binding of transcription factors.
  \end{itemize}
  \begin{figure}
    \centering
    \includegraphics<3>[width=.75\textwidth]{Images/bradner_cis_small.png}
  \end{figure}
  \footnotetext[1]{Bradner JE, et al. Cancer. Cell. 2017 Feb 9;168(4):629-643}
\end{frame}

\begin{frame}{\emoji{thinking-face} My PhD --- Epigenetic Rationnal}
  \begin{itemize}
   \item The presence of upstream \alert{indels in \textit{TAL1} leads to the formation of a neo-enhancer}$^1$.
   \item It has also been shown that the transcription factor \alert{MYB can bind to this neo-enhancers}$^2$.
  \end{itemize}
  \begin{figure}
    \includegraphics[width=.46\textwidth]{Images/tal_ins.png}
  \end{figure}
  \footnotetext[1]{
    \tiny
    Navarro JM et al. Nat Commun. 2015;6:6094}
  \footnotetext[2]{
    \tiny
    Smith, C et al. “TAL1 activation in T-cell acute lymphoblastic leukemia: a 
  novel oncogenic 3' neo-enhancer.” Haematologica vol. 108,5 1259-1271. 1 May. 2023}
\end{frame}

{\setbeamercolor{background canvas}{bg=bgturq}
\begin{frame}[c]
  \vspace{.6cm}
  \metroset{block=fill}
  \begin{alertblock}{{\centering \large Hypothesis} }
    \begin{itemize}
      \item[A]<1-> By taking a pan-genomic approach, it is possible to identify numerous \alert{intergenic 
      alterations correlated with the cis deregulation of adjacent genes} (correlation between 
      transcriptome RNA-seq and ChIP-seq).
      \item[B]<2-> Some of these genes are expected to be known oncogenes, while others have 
      the potential to be \alert{novel oncogenes} (discovery).
      \item[C]<3-> It is likely that these specific alterations are the causative factors 
      for the cis deregulation of adjacent genes (functional experiments).
      \item[D]<4-> Based on these alterations, it is possible to stratify patients into 
      groups with similar \alert{prognoses}.
      \item[E]<5-> The \alert{characterization of the deregulation mechanisms and the discovered oncogenes} 
      should help identify vulnerabilities that can be targeted by treatment.
      \item[F]<6-> This treatment may prove to be \alert{more effective with fewer side effects} compared 
      to the currently prescribed polychemotherapy.
    \end{itemize}
  \end{alertblock}
\end{frame}
}

\begin{frame}{\emoji{white-check-mark} What's already done}
  \begin{itemize}
    \item[\emoji{white-check-mark}] Alignement and copy number analysis of more than 260 RNA-seq
  \end{itemize}
  \begin{figure}
    \includegraphics[width=\textwidth]{Images/fdt_hm.png}
  \end{figure}
\end{frame}

\begin{frame}{\emoji{white-check-mark} What's already done}
  \begin{itemize}
    \item[\emoji{white-check-mark}]<1-> Alignement and copy number analysis of more than 260 RNA-seq
    \item[\emoji{white-check-mark}]<1-> Alignement and copy number analysis of 72 ChIP-seq (H3K4me4 and H4K27ac).
    \item[\emoji{white-check-mark}]<2-> We have developed a high-performance tool that optimizes memory usage and 
    speed for correlating variably expressed genes with depth of ChIP-seq peaks. Specifically, our tool 
    efficiently handles a large dataset consisting of 10,036 gene expressions and 84,839 ChIP-seq positions, 
    resulting in a total of 851,444,204 correlations.
    \item[\emoji{white-check-mark}]<3-> Calling of genetic alterations sequenced by ChIP-seq.
  \end{itemize}
\end{frame}

\begin{frame}{\emoji{dart} First results}
  With these filters:
  \begin{itemize}
    \item Recurrent mutations in the same ChIP-seq peak (> 1 case) with enrichment of the alternative allele (AF > 0.6).
    \item Cases with the mutations should have correlated genes (Pearson coefficient > 0.7) 
    significantly upregulated (t-test p value < 0.05)
  \end{itemize}
  \begin{figure}
    \includegraphics[width=\textwidth]{Images/hm_1.png}
  \end{figure}
  \vspace{.5cm}
  \begin{figure}
    \includegraphics[width=\textwidth]{Images/hm_2.png}
  \end{figure}
\end{frame}

\begin{frame}{\emoji{knocked-out-face} Caveats}
  \begin{itemize}
    \item<1-> Most of intergenic alterations are \alert{SNPs}.
    \item<2-> Complexe alterations like \alert{indels and SV are difficult to call with ChIP-seq small reads}.
    \item[$\rightarrow$]<3-> We are implementing \alert{longreads sequencing} with the Oxford Nanopore Promethion for 
    resolving complex genomic regions, detecting structural variations, and studying repetitive elements.
  \end{itemize}
  \begin{figure}
    \includegraphics<3>[width=.4\textwidth]{Images/promethion.png}
  \end{figure}
\end{frame}

\begin{frame}{\emoji{flying-saucer} Longreads pipeline}
  \begin{itemize}
    \item<1-> We will conduct a \alert{whole-genome sequencing of 150 T-ALL cases along with their corresponding constitutional samples}.
    \item<2-> Our objective is to implement a pipeline capable of \alert{assembling long reads and generating a diploid 
    reference genome} for each of the cases.
  \end{itemize}
  \begin{figure}
    \includegraphics<2->[width=\textwidth]{Images/lr_pipe.png}
  \end{figure}
  
  \footnotetext[1]{
    \tiny
    Kolmogorov, Mikhail et al. “Assembly of long, error-prone reads using repeat graphs.” Nature biotechnology 
    vol. 37,5 (2019): 540-546. doi:10.1038/s41587-019-0072-8}
\end{frame}

\begin{frame}{\emoji{flying-saucer} Longreads pipeline}
  \begin{itemize}
    \item<1-> We will conduct a \alert{whole-genome sequencing of 150 T-ALL cases along with their corresponding constitutional samples}.
    \item<1-> Our objective is to implement a pipeline capable of \alert{assembling long reads and generating a diploid 
    reference genome} for each of the cases.
    \item<1-> The alignment of somatic reads on it and the subsequent calling of somatic variants, 
    especially \alert{structural variations} (SV), will be of significant interest.
    \item<2-> By aligning our current RNA-seq and ChIP-seq data using this approach, we will be able to \alert{phase gene 
    expression} and identify \alert{allele-enriched epigenetic marks} more efficiently.
    \item<3-> We will also have access to \alert{phased methylation of CpG islands} with the same technic.
  \end{itemize}
\end{frame}

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