Evidence map›Paper›PMID 41299043›Full record

ReviewNature biotechnology2025

Cell type inference in cell-free nucleic acid liquid biopsy.

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

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Sevahn K VorperianGenentech Research and Early Development, Genentech Inc., South San Francisco, CA, USA. vorperian.sevahn@gene.com.ORCID http://orcid.org/0000-0003-0418-5260
Lucas M DennisFoundation Medicine, Foundation Medicine Inc., Boston, MA, USA.ORCID http://orcid.org/0000-0002-5299-8066
Anna HupalowskaGenentech Research and Early Development, Genentech Inc., South San Francisco, CA, USA.ORCID http://orcid.org/0009-0008-9875-8405
Jennifer E RoodGenentech Research and Early Development, Genentech Inc., South San Francisco, CA, USA.ORCID http://orcid.org/0000-0002-9489-0731
Stephen R QuakeDepartment of Bioengineering, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-1613-0809

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Cell-Free Nucleic AcidsHumansLiquid BiopsySingle-Cell AnalysisTranscriptomeCell-Free Nucleic Acids

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.