Evidence map›Paper›PMID 39352924›Full record

ArticlePLoS computational biology2024

Quantitative modeling of signaling in aggressive B cell lymphoma unveils conserved core network.

Bertram Klinger, Isabel Rausch, Anja Sieber, Helmut Kutz, Vanessa Kruse, Marieluise Kirchner, Philipp Mertins, Arnd Kieser, Nils Blüthgen, Dieter Kube

Abstract read
In one paragraph

Article in PLoS computational biology, 2024. 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

10 authors.

Bertram KlingerInstitute of Pathology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.ORCID 0000-0003-0242-1506
Isabel RauschClinic of Hematology and Medical Oncology, University Medical Centre Goettingen, Göttingen, Germany.
Anja SieberInstitute of Pathology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.ORCID 0000-0001-6588-8547
Helmut KutzResearch Unit Gene Vectors, Helmholtz Center Munich-German Research Center for Environmental Health, Munich, Germany.
Vanessa KruseClinic of Hematology and Medical Oncology, University Medical Centre Goettingen, Göttingen, Germany.
Marieluise KirchnerCore Unit Proteomics, Berlin Institute of Health at Charité-Universitaetsmedizin Berlin and Max-Delbrueck-Center for Molecular Medicine, Berlin, Germany.ORCID 0000-0002-7049-534X
Philipp MertinsCore Unit Proteomics, Berlin Institute of Health at Charité-Universitaetsmedizin Berlin and Max-Delbrueck-Center for Molecular Medicine, Berlin, Germany.ORCID 0000-0002-2245-528X
Arnd KieserResearch Unit Gene Vectors, Helmholtz Center Munich-German Research Center for Environmental Health, Munich, Germany.ORCID 0000-0003-0783-1950
Nils BlüthgenInstitute of Pathology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.ORCID 0000-0002-0171-7447
Dieter KubeClinic of Hematology and Medical Oncology, University Medical Centre Goettingen, Göttingen, Germany.ORCID 0000-0001-7760-525X

Funding

Bundesinstitut für Risikobewertung 60-0102-01.P61Deutsche Krebshilfe 70114307Federal Ministry of Education and Research (BMBF) 031A428B
6 · The paper itself

Abstract

B cell receptor (BCR) signaling is required for the survival and maturation of B cells and is deregulated in B cell lymphomas. While proximal BCR signaling is well studied, little is known about the crosstalk of downstream effector pathways, and a comprehensive quantitative network analysis of BCR signaling is missing. Here, we semi-quantitatively modelled BCR signaling in Burkitt lymphoma (BL) cells using systematically perturbed phosphorylation data of BL-2 and BL-41 cells. The models unveiled feedback and crosstalk structures in the BCR signaling network, including a negative crosstalk from p38 to MEK/ERK. The relevance of the crosstalk was verified for BCR and CD40 signaling in different BL cells and confirmed by global phosphoproteomics on ERK itself and known ERK target sites. Compared to the starting network, the trained network for BL-2 cells was better transferable to BL-41 cells. Moreover, the BL-2 network was also suited to model BCR signaling in Diffuse large B cell lymphoma cells lines with aberrant BCR signaling (HBL-1, OCI-LY3), indicating that BCR aberration does not cause a major downstream rewiring.

Indexed as

Lymphoma, B-CellReceptors, Antigen, B-CellSignal TransductionBurkitt LymphomaCell Line, TumorComputational BiologyHumansModels, BiologicalPhosphorylationReceptors, Antigen, B-Cell

Identifiers

PMID39352924
PMCPMC11469524

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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.