<?xml version="1.0" encoding="UTF-8"?>
<STUDY_SET xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
  <STUDY center_name="GEO" alias="GSE104154" accession="SRP118702">
    <IDENTIFIERS>
      <PRIMARY_ID>SRP118702</PRIMARY_ID>
      <EXTERNAL_ID namespace="BioProject" label="primary">PRJNA411830</EXTERNAL_ID>
      <EXTERNAL_ID namespace="GEO">GSE104154</EXTERNAL_ID>
    </IDENTIFIERS>
    <DESCRIPTOR>
      <STUDY_TITLE>Single Cell Analysis of Pulmonary Fibrotic Mesenchymal Cells Indicates a New Subtype</STUDY_TITLE>
      <STUDY_TYPE existing_study_type="Transcriptome Analysis"/>
      <STUDY_ABSTRACT>Stromal  taxonomy consists of multiple cell subtypes that play a critical role in tissue repair or regeneration, fibrosis, inflammation, angiogenesis and tumor formation. However, their identities are not fully understood, as these conventional classified populations have historically been defined by restricted sets of markers. We performed single-cell RNA sequencing to investigate stromal mesenchymal cells (MCs) in normal and fibrotic mouse lung. Interrogated patterns of signature genes, lncRNAs, extracellular and plasma membrane genes, and top transcription factors expression were defined to characterize and classify 7 MC types in normal status. A specific new subset was discovered in fibrotic stage. Delineation of their differentiation trajectory was achieved by a machine learning method. This collection of transcriptional scRNA-seq data uncovered core information and provided a valuable resource for understanding the mesenchymal landscape in fibrotic diseases. Overall design: Stratification of lung mesenchymal subtypes in normal and fibrotic stages.</STUDY_ABSTRACT>
      <CENTER_PROJECT_NAME>GSE104154</CENTER_PROJECT_NAME>
    </DESCRIPTOR>
    <STUDY_LINKS>
      <STUDY_LINK>
        <XREF_LINK>
          <DB>pubmed</DB>
          <ID>29590628</ID>
        </XREF_LINK>
      </STUDY_LINK>
      <STUDY_LINK>
        <XREF_LINK>
          <DB>pubmed</DB>
          <ID>34108218</ID>
        </XREF_LINK>
      </STUDY_LINK>
    </STUDY_LINKS>
  </STUDY>
</STUDY_SET>
