Evidence map›Paper›PMID 40839679›Full record

ArticlePLoS computational biology2025

A computational workflow for assessing drug effects on temporal signaling dynamics reveals robustness in stimulus-specific NFκB signaling.

Emily R Bozich, Xiaolu Guo, Jennifer L Wilson, Alexander Hoffmann

Abstract read
In one paragraph

Article in PLoS computational biology, 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. Review
  2. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Emily R BozichDepartment of Bioengineering, University of California, Los Angeles, California, United States of America.ORCID https://orcid.org/0000-0002-7480-8227
Xiaolu GuoInstitute for Quantitative and Computational Biosciences, University of California, Los Angeles, California, United States of America.ORCID https://orcid.org/0000-0002-5740-2428
Jennifer L WilsonDepartment of Bioengineering, University of California, Los Angeles, California, United States of America.
Alexander HoffmannInstitute for Quantitative and Computational Biosciences, University of California, Los Angeles, California, United States of America.ORCID https://orcid.org/0000-0002-5607-3845

Funding

Characterizing functional states of macrophages via their stimulus-responsesR01AI173214 · NIAID · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Alexander Hoffmann · 2023 to 2026
$2.8M
Understanding cascading cellular protein responses following multi-protein stimuli using network modeling and real-world evidenceR35GM147114 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Jennifer Lynn Wilson · 2022 to 2026
$1.6M
NIAID NIH HHS R01 AI173214NIGMS NIH HHS R35 GM147114
6 · The paper itself

Abstract

Single-cell studies of signal transduction have revealed complex temporal dynamics that determine downstream biological function. For example, the stimulus-specific dynamics of the transcription factor NFκB specify stimulus-specific gene expression programs, and loss of specificity leads to disease. Thus, it is intriguing to consider drugs that may restore signaling specificity in disease contexts, or reduce activity but maintain signaling specificity to avoid unwanted side effects. However, while steady-state dose-response relationships have been the focus of pharmacological studies, there are no established methods for quantifying drug impact on stimulus-response signaling dynamics. Here we evaluated how drug treatments affect the stimulus-specificity of NFκB activation dynamics and its ability to accurately code ligand identity and dose. Specifically, we simulated the dynamic NFκB trajectories in response to 15 stimuli representing various immune threats under treatment of 10 representative drugs across 20 dosage levels. To quantify the effects on coding capacity, we introduced a Stimulus Response Specificity (SRS) score and a stimulus confusion score. We constructed stimulus confusion maps by employing epsilon network clustering in the trajectory space and in various dimensionally reduced spaces: canonical polyadic decomposition (CPD), functional principal component analysis (fPCA), and NFκB signaling codons (i.e., established, informative dynamic features). Our results indicated that the SRS score and the stimulus confusion map based on signaling codons are best-suited to quantify stimulus-specific NFκB dynamics confusion under pharmacological perturbations. Using these tools we found that temporal coding capacity of the NFκB signaling network is generally robust to a variety of pharmacological perturbations, thereby enabling the targeting of stimulus-specific dynamics without causing broad side-effects.

Indexed as

Computational BiologyModels, BiologicalNF-kappa BSignal TransductionComputer SimulationDose-Response Relationship, DrugHumansWorkflowNF-kappa B

Identifiers

PMID40839679
PMCPMC12370059

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.