Evidence map›Paper›PMID 40539671›Full record

ArticleJournal of cellular and molecular medicine2025

Signalling Network Analysis of Blood Mononuclear Cells From Clinical Samples by Bivariate Correlation.

David Kaplan, Hillard M Lazarus, Jason Valent, Faiz Anwer, Sandra Mazzoni, Christy Samaras, Louis Williams, Megan Nakashima, Mazen Hanna, Shahzad Raza and 2 more

Abstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

12 authors.

David KaplanCellPrint Biotechnology LLC, Shaker Heights, Ohio, USA.ORCID 0000-0002-7069-9254
Hillard M LazarusCellPrint Biotechnology LLC, Shaker Heights, Ohio, USA.ORCID 0000-0002-1159-5607
Jason ValentDepartment of Hematology and Medical Oncology, Taussig Cancer Center, Cleveland Clinic Foundation, Cleveland, Ohio, USA.
Faiz AnwerDepartment of Hematology and Medical Oncology, Taussig Cancer Center, Cleveland Clinic Foundation, Cleveland, Ohio, USA.
Sandra MazzoniDepartment of Hematology and Medical Oncology, Taussig Cancer Center, Cleveland Clinic Foundation, Cleveland, Ohio, USA.
Christy SamarasDepartment of Hematology and Medical Oncology, Taussig Cancer Center, Cleveland Clinic Foundation, Cleveland, Ohio, USA.
Louis WilliamsDepartment of Hematology and Medical Oncology, Taussig Cancer Center, Cleveland Clinic Foundation, Cleveland, Ohio, USA.
Megan NakashimaDepartment of Hematology and Medical Oncology, Taussig Cancer Center, Cleveland Clinic Foundation, Cleveland, Ohio, USA.
Mazen HannaDepartment of Hematology and Medical Oncology, Taussig Cancer Center, Cleveland Clinic Foundation, Cleveland, Ohio, USA.
Shahzad RazaDepartment of Hematology and Medical Oncology, Taussig Cancer Center, Cleveland Clinic Foundation, Cleveland, Ohio, USA.
Eric ChristianCellPrint Biotechnology LLC, Shaker Heights, Ohio, USA.
Jack KhouriDepartment of Hematology and Medical Oncology, Taussig Cancer Center, Cleveland Clinic Foundation, Cleveland, Ohio, USA.

Funding

CellPrint Biotechnology LLCJohnson and Johnson Innovation
6 · The paper itself

Abstract

Signalling networks have been assessed in blood cells by assessing individual phosphoantigens. We considered the possibility that bivariate correlations involving a series of signalling molecules could be used to delineate functional signalling networks in cells from clinical samples. Here, we describe a novel approach to signalling network analysis using enhanced flow cytometry to provide increased resolving power and restricted-dimensional cytometry which simplifies the analysis so that the precision of the analysis is optimised. This approach has been validated in short-term cultures by recapitulating known tenets of two distinct pathways. Additionally, new findings from our unique approach provide both expanded and nuanced views of signalling circuits. Applying our technology platform to blood mononuclear cells from patients with plasma cell disorders, we identified cell-type specific features of signalling pathways by distinct patterns of bivariate correlations. The intermolecular relationships between signalling analytes provide a description of the signalling network in blood cells from clinical samples. Consequently, our approach has the potential to assess how the blood mononuclear cell-type specific signalling network affects pathophysiology and pathogenesis.

Indexed as

Leukocytes, MononuclearSignal TransductionFlow CytometryHumansAL amyloidosisapoptosisMGUSmyelomaperipheral blood mononuclear cellsphosphoantigensplasma cell dyscrasiasignalling pathwaysSTING pathway

Identifiers

PMID40539671
PMCPMC12179811

What OpenQuestion holds

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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.