Evidence map›Paper›PMID 42426463›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Utilizing Magnetic Microraft Technology for Single-Cell Isolation of CTCs from Whole Blood for scRNA-Seq Transcriptomic Characterization.

Terri Clister, Rosalyn M Fey, Zachary R Garrison, Khanh Doan, Heather Branchaud, Connor M Hall, Rebecca A Nichols, Rajan P Kulkarni

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Terri ClisterDepartment of Dermatology, Oregon Health & Science University, Portland, OR, 97239, USA.
Rosalyn M FeyDepartment of Dermatology, Oregon Health & Science University, Portland, OR, 97239, USA.
Zachary R GarrisonDepartment of Dermatology, Oregon Health & Science University, Portland, OR, 97239, USA.
Khanh DoanDepartment of Dermatology, Oregon Health & Science University, Portland, OR, 97239, USA.
Heather BranchaudDepartment of Dermatology, Oregon Health & Science University, Portland, OR, 97239, USA.
Connor M HallDepartment of Dermatology, Oregon Health & Science University, Portland, OR, 97239, USA.
Rebecca A NicholsDepartment of Dermatology, Oregon Health & Science University, Portland, OR, 97239, USA.
Rajan P KulkarniDepartment of Dermatology, Oregon Health & Science University, Portland, OR, 97239, USA. kulkarnr@ohsu.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Circulating tumor cells (CTCs) are emerging biomarkers for cancer prognosis, yet existing methods to isolate CTCs from liquid biopsies rely on cell surface markers, which restrict the heterogeneity of the sampled cells. Here, we describe a method for the detection of disease-specific CTCs from peripheral blood using both positive and negative enrichment strategies. We also implement the newly designed Smart-seq3 library preparation protocol, allowing for the sequencing of full-length CTC transcripts at the single-cell level. We demonstrate the utility of this isolation method by isolating melanoma cells spiked into healthy blood, followed by single-cell RNA-seq.

Indexed as

Cell SeparationNeoplastic Cells, CirculatingRNA-SeqSingle-Cell AnalysisTranscriptomeBiomarkers, TumorCell Line, TumorGene Expression ProfilingHumansMelanomaSingle-Cell Gene Expression AnalysisBiomarkers, TumorCirculating tumor cells (CTCs)Microraftssc-RNAseqSingle cellTranscriptomic analysis

Identifiers

PMID42426463

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.