Scholarlink

<p>The use of single-cell RNA sequencing in clinical and translational research is limited by the challenge of identifying cell-type-specific, targetable molecular changes in individual patients and cross-species differences. Here we created an integrated single-cell kidney atlas including over 1 million cells from 140 samples, defining more than 70 conserved cell states in human and rodent models. We developed CellSpectra, a computational tool that quantifies changes in gene expression coordination across cellular functions, which we applied to kidney and lung cancer data. This tool powers our patient-level single-cell functional profiling report, which highlights cell-type-specific changes in the coordination of pathway gene expression in individuals. Our cross-species atlas facilitates the selection of a rodent model that closely reflects the cellular and pathway-level signatures observed in patient samples, advancing the application of single-cell methodologies in clinical precision medicine. Finally, using experimental models, we demonstrate how our informatics approach can be applied for the potential selection of suitable therapeutics.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Analysis of individual patient pathway coordination in a cross-species single-cell kidney atlas

  • 期刊论文

  • 发表日期：

    2025年8月7日

查看全文
  • Konstantin A. Klötzer,
  • Amin Abedini,
  • Shen Li,
  • Michael S. Balzer,
  • Xiujie Liang,
  • Jonathan Levinsohn,
  • Eunji Ha,
  • Bernhard Dumoulin,
  • Jonathan J. Hogan,
  • Ghazal Quinn,
  • Roy D. Bloom,
  • Max Schuller,
  • Kathrin Eller,
  • Balazs Halmos,
  • Nancy R. Zhang,
  • Katalin Susztak

摘要

The use of single-cell RNA sequencing in clinical and translational research is limited by the challenge of identifying cell-type-specific, targetable molecular changes in individual patients and cross-species differences. Here we created an integrated single-cell kidney atlas including over 1 million cells from 140 samples, defining more than 70 conserved cell states in human and rodent models. We developed CellSpectra, a computational tool that quantifies changes in gene expression coordination across cellular functions, which we applied to kidney and lung cancer data. This tool powers our patient-level single-cell functional profiling report, which highlights cell-type-specific changes in the coordination of pathway gene expression in individuals. Our cross-species atlas facilitates the selection of a rodent model that closely reflects the cellular and pathway-level signatures observed in patient samples, advancing the application of single-cell methodologies in clinical precision medicine. Finally, using experimental models, we demonstrate how our informatics approach can be applied for the potential selection of suitable therapeutics.