<?xml version="1.0" encoding="UTF-8"?>
<STUDY_SET xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
  <STUDY center_name="GEO" alias="GSE201647" accession="SRP372418">
    <IDENTIFIERS>
      <PRIMARY_ID>SRP372418</PRIMARY_ID>
      <EXTERNAL_ID namespace="BioProject" label="primary">PRJNA832482</EXTERNAL_ID>
      <EXTERNAL_ID namespace="GEO">GSE201647</EXTERNAL_ID>
    </IDENTIFIERS>
    <DESCRIPTOR>
      <STUDY_TITLE>SSN-seq: Multiplexed single-cell transcriptomic profiling via genetic barcoding with shielded small nucleotides</STUDY_TITLE>
      <STUDY_TYPE existing_study_type="Other"/>
      <STUDY_ABSTRACT>To facilitate scalable longitudinal profiling of single cells we developed a universal permanent genetic cell barcoding technology based on the expression of shielded small nucleotides coupled with single-cell RNA-seq (SSN-seq). SSN barcodes are highly expressed and contain direct-capture sequences to enable recovery of distinct barcodes directly in each single-cell transcriptome allowing cell identity history to be recorded over time, in parallel with cell identity. SSN-seq is compatible with both 3' and 5' single-cell profiling and is readily adaptable to numerous cell types including human primary T cells and CAR T cells making it a promising tool for rapidly improving adoptive cell therapies and expanding their functionality. We applied SSN-seq to track the dynamics of CAR T cell states at the time of infusion and upon isolation from in vivo tumor rechallenge model. Our study identified that a novel combination of cytokines and small molecule inhibitors used for CAR T cells manufactured ex vivo, promotes the expansion of persistent CD4+ memory T cell populations in vivo. Together, these results demonstrate the utility of our method for multiplexed perturbation experiments that reveal the dynamics of cell states over time, with a high degree of confidence. Overall design: scRNA-seq of SSN-barcoded cells in vitro and in vivo</STUDY_ABSTRACT>
      <CENTER_PROJECT_NAME>GSE201647</CENTER_PROJECT_NAME>
    </DESCRIPTOR>
    <STUDY_LINKS>
      <STUDY_LINK>
        <XREF_LINK>
          <DB>pubmed</DB>
          <ID>37652986</ID>
        </XREF_LINK>
      </STUDY_LINK>
    </STUDY_LINKS>
  </STUDY>
</STUDY_SET>
