Evidence map›Paper›PMID 39668068›Full record

ArticleJournal of the American Society of Cytopathology

Comparative analysis of Ficoll-Hypaque and CytoLyt techniques for blood removal in breast cancer malignant effusions: effects on RNA quality and sequencing outcomes.

Gloria H Sura, Kevin Tran, Alexander J Trevarton, Michal Marczyk, Chunxiao Fu, Lili Du, Jiaxin Qu, Rosanna Lau, Amy Tasto, Rebekah E Gould and 5 more

Abstract readComparative Study
In one paragraph

Article in Journal of the American Society of Cytopathology. 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. Review
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

15 authors.

Gloria H SuraDepartments of Anatomic Pathology and Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Kevin TranDepartments of Anatomic Pathology and Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Alexander J TrevartonDepartments of Anatomic Pathology and Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas; School of Biological Sciences, The University of Auckland, Auckland, New Zealand.
Michal MarczykDepartment of Data Science and Engineering, Silesian University of Technology, Gliwice, Poland; Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut.
Chunxiao FuDepartments of Anatomic Pathology and Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas; Delphi Diagnostics, Austin, Texas.
Lili DuDepartments of Anatomic Pathology and Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Jiaxin QuDepartments of Anatomic Pathology and Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Rosanna LauDepartments of Anatomic Pathology and Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas; Delphi Diagnostics, Austin, Texas.
Amy TastoDepartments of Anatomic Pathology and Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Rebekah E GouldDepartments of Anatomic Pathology and Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Agata TinnirelloDepartments of Anatomic Pathology and Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Bruno V SinnInstitute of Pathology, Charité Universitätsmedizin Berlin, Berlin, Germany.
Lajos PusztaiYale Cancer Center, Yale School of Medicine, New Haven, Connecticut.
Christos HatzisYale Cancer Center, Yale School of Medicine, New Haven, Connecticut.
W Fraser SymmansDepartments of Anatomic Pathology and Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas; Delphi Diagnostics, Austin, Texas. Electronic address: fsymmans@mdanderson.org.

Funding

Integrating Biospecimen Science Into The Development Of RNA-Based Clinical Assays For Patients With Metastatic Breast CancerU01CA215547 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI SYMMANS, WILLIAM F · 2017 to 2021
$1.6M
NCI NIH HHS U01 CA215547
6 · The paper itself

Abstract

introductionTo optimize RNA sequencing (RNA-seq) outcomes, we investigated preanalytical variables in malignant effusions containing metastatic breast cancer. We compared 2 processing methods-Ficoll-Hypaque density gradient enrichment and CytoLyt hemolysis-focusing on their effects on RNA quality, transcript abundance, and variant detection from cytospin slides, relative to fresh-frozen samples. Additionally, we compared read-based and Unique Molecular Identifier (UMI)-based library preparation methods. MATERIALS AND

methodsThirteen malignant effusion specimens from metastatic breast cancer were processed using both the Ficoll-Hypaque and Cytolyt methods. RNA was extracted from fresh-frozen samples stored in RNA preservative and from cytospin slides fixed in Carnoy's solution. RNA quality was evaluated using RNA integrity number (RIN) and the percentage of fragments >200 bases (DV200). Sequencing was conducted with both read- and UMI-based methods.

resultsPurified RNA was more fragmented by the Cytolyt method (mean RIN: 3.56, DV200: 78.97%), compared to the Ficoll-Hypaque method (mean RIN: 6.29, DV200: 88.08%). Sequencing data had high concordance correlation coefficient (CCC) for measurements of gene expression, whether from Cytolyt or Ficoll-Hypaque treated samples, and whether using the UMI- or read-based sequencing methods (read-based mean CCC: 0.967 from Cytolyt versus 0.974 from Ficoll-Hypaque, UMI-based mean CCC: 0.972 from Cytolyt versus 0.977 from Ficoll-Hypaque).

conclusionsDespite the increased RNA fragmentation with the Cytolyt, RNA-seq data quality was comparable across Cytolyt and Ficoll-Hypaque methods. Both clearing methods are viable for short-read RNA-seq analysis, with read and UMI-based approaches performing similarly.

Indexed as

Breast NeoplasmsFicollPleural Effusion, MalignantRNA, NeoplasmFemaleHumansMiddle AgedSequence Analysis, RNAFicollRNA, NeoplasmCytology processingCytopathologyEffusionFixativeMolecularRNA sequencingUnique molecular identifiers

Identifiers

PMID39668068
PMCPMC12938591

What OpenQuestion holds

Textmetadata
LicenceTDM
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.