<?xml version="1.0" encoding="UTF-8"?>
<STUDY_SET xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
  <STUDY center_name="GEO" alias="GSE232086" accession="SRP436729">
    <IDENTIFIERS>
      <PRIMARY_ID>SRP436729</PRIMARY_ID>
      <EXTERNAL_ID namespace="BioProject" label="primary">PRJNA970798</EXTERNAL_ID>
      <EXTERNAL_ID namespace="GEO">GSE232086</EXTERNAL_ID>
    </IDENTIFIERS>
    <DESCRIPTOR>
      <STUDY_TITLE>Epigenetic heterogeneity and transcriptional drivers of triple-negative breast cancer [ChIP-Seq]</STUDY_TITLE>
      <STUDY_TYPE existing_study_type="Other"/>
      <STUDY_ABSTRACT>Triple-negative breast cancer (TNBC) is a heterogeneous disease with limited treatment options. To characterize TNBC heterogeneity and treatment response, we combined functional and molecular profiling with computational analysis tools. Using these approaches, we defined transcriptional, epigenetic, and metabolic subtypes, and identified subtype-driving super-enhancers. Single cell RNA sequencing analyses revealed relative homogeneity of the three major transcriptional subtypes (luminal, basal and mesenchymal) within tumors. We found that mesenchymal TNBCs are more similar to mesenchymal neuroblastoma and rhabdoid tumors than to other TNBC subtypes, and the PRRX1 transcription factor serves as a key driver of these tumors. By directly regulating the transcription of mesenchymal genes, PRRX1 is sufficient for inducing the mesenchymal subtype but is not required for its maintenance. Overall design: Duplicate H3K27ac ChIP-seq of 2 TNBC cell lines with TET-inducible expression of wild type or DNA-binding mutant PRRX1, with and without doxycycline treatment, at two time points</STUDY_ABSTRACT>
      <CENTER_PROJECT_NAME>GSE232086</CENTER_PROJECT_NAME>
    </DESCRIPTOR>
    <STUDY_LINKS>
      <STUDY_LINK>
        <XREF_LINK>
          <DB>pubmed</DB>
          <ID>38100350</ID>
        </XREF_LINK>
      </STUDY_LINK>
    </STUDY_LINKS>
    <STUDY_ATTRIBUTES>
      <STUDY_ATTRIBUTE>
        <TAG>parent_bioproject</TAG>
        <VALUE>PRJNA837247</VALUE>
      </STUDY_ATTRIBUTE>
    </STUDY_ATTRIBUTES>
  </STUDY>
</STUDY_SET>
