ArticleBiomolecules2020
Can We Assume the Gene Expression Profile as a Proxy for Signaling Network Activity?
Article in Biomolecules, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Sex chromosome aneuploidy impacts on human gene expression and regulation: a systematic review.Molecular medicine (Cambridge, Mass.) · 2025Pooled it
- DORSSAA: Drug-Target interactOmics Resource Based on Stability/Solubility Alteration Assay.Molecular & cellular proteomics : MCP · 2026Article
- Application of perturbation gene expression profiles in drug discovery-From mechanism of action to quantitative modelling.Frontiers in systems biology · 2023Review
- Identification of phenotype-specific networks from paired gene expression-cell shape imaging data.Genome research · 2022Article
- Protein complexes detection based on node local properties and gene expression in PPI weighted networks.BMC bioinformatics · 2022Article
- Involvement of immune system and Epithelial-Mesenchymal-Transition in increased invasiveness of clustered circulatory tumor cells in breast cancer.BMC medical genomics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 5 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Studying relationships among gene products by expression profile analysis is a common approach in systems biology. Many studies have generalized the outcomes to the different levels of central dogma information flow and assumed a correlation of transcript and protein expression levels. However, the relation between the various types of interaction (i.e., activation and inhibition) of gene products to their expression profiles has not been widely studied. In fact, looking for any perturbation according to differentially expressed genes is the common approach, while analyzing the effects of altered expression on the activity of signaling pathways is often ignored. In this study, we examine whether significant changes in gene expression necessarily lead to dysregulated signaling pathways. Using four commonly used and comprehensive databases, we extracted all relevant gene expression data and all relationships among directly linked gene pairs. We aimed to evaluate the ratio of coherency or sign consistency between the expression level as well as the causal relationships among the gene pairs. Through a comparison with random unconnected gene pairs, we illustrate that the signaling network is incoherent, and inconsistent with the recorded expression profile. Finally, we demonstrate that, to infer perturbed signaling pathways, we need to consider the type of relationships in addition to gene-product expression data, especially at the transcript level. We assert that identifying enriched biological processes via differentially expressed genes is limited when attempting to infer dysregulated pathways.
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Registered trials
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.