<p>Cell-free nucleic acid (cfNA) liquid biopsy offers a versatile, noninvasive alternative to needle biopsy procedures for the diagnosis or surveillance of a broad range of diseases and physiological conditions. Although these noninvasive molecular measurements enable diagnostic biomarker discovery, they often lack the cellular resolution afforded by invasive needle biopsy. Cell type-specific changes frequently form the basis of disease and contribute to the molecular changes observed in a cfNA liquid biopsy. Recent experimental and computational advances in cfNA detection, alongside detailed molecular definitions across cell types of the human body from single-cell transcriptomic data, can enable cell type inference. In this Review, we delineate the respective strengths of cell-free DNA and cell-free RNA relative to the diagnostic use case. We then describe computational frameworks to infer cell type contributions in cfNA and the distinct opportunity afforded by single-cell transcriptomic data. Finally, we highlight current applications, future directions, and outstanding questions related to this paradigm in cfNA liquid biopsy.</p>

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Cell type inference in cell-free nucleic acid liquid biopsy

  • Sevahn K. Vorperian,
  • Lucas M. Dennis,
  • Anna Hupalowska,
  • Jennifer E. Rood,
  • Stephen R. Quake

摘要

Cell-free nucleic acid (cfNA) liquid biopsy offers a versatile, noninvasive alternative to needle biopsy procedures for the diagnosis or surveillance of a broad range of diseases and physiological conditions. Although these noninvasive molecular measurements enable diagnostic biomarker discovery, they often lack the cellular resolution afforded by invasive needle biopsy. Cell type-specific changes frequently form the basis of disease and contribute to the molecular changes observed in a cfNA liquid biopsy. Recent experimental and computational advances in cfNA detection, alongside detailed molecular definitions across cell types of the human body from single-cell transcriptomic data, can enable cell type inference. In this Review, we delineate the respective strengths of cell-free DNA and cell-free RNA relative to the diagnostic use case. We then describe computational frameworks to infer cell type contributions in cfNA and the distinct opportunity afforded by single-cell transcriptomic data. Finally, we highlight current applications, future directions, and outstanding questions related to this paradigm in cfNA liquid biopsy.