ArticleNature communications2023
Quantification of ligand and mutation-induced bias in EGFR phosphorylation in direct response to ligand binding.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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.
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.
Who cites it
10 citing papers in PubMed, 11 citations in OpenAlex.
- Mechanisms and Manifestations of Ligand Bias in Signaling: Focus on Receptor Tyrosine Kinases.Chemical reviews · 2026Review
- Differential ErbB receptor dimerization modulates the ability of EGF receptor ligands to regulate metabolic flux.The Journal of biological chemistry · 2026Article
- Design, Synthesis of Novel Quinazolinone Derivatives and Evaluation of EGFR Kinase Inhibition Activity via In Vitro and In Silico Studies.Chemical biology & drug design · 2026Article
- Predicting and interpreting protein and phosphoprotein abundance from pan-cancer and single-cell transcriptomes.iScience · 2026Article
- The role of kinase domain dimerization in EGFR activation.Structure (London, England : 1993) · 2026Article
- PKC-iota drives EGFR-TKI resistance in EGFR-mutated NSCLC by phosphorylating FASN to reprogram lipid metabolism.Translational lung cancer research · 2026Article
- Allosteric modulation of NF1 GAP: Differential distributions of catalytically competent populations in loss-of-function and gain-of-function mutants.Protein science : a publication of the Protein Society · 2025Article
- Probing phosphorylation events in biological membranes: The transducer function.Biochimica et biophysica acta. Biomembranes · 2024Review
- Article
- How Neuromembrane Lipids Modulate Membrane Proteins: Insights from G-Protein-Coupled Receptors (GPCRs) and Receptor Tyrosine Kinases (RTKs).Cold Spring Harbor perspectives in biology · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Signaling bias is the ability of a receptor to differentially activate downstream signaling pathways in response to different ligands. Bias investigations have been hindered by inconsistent results in different cellular contexts. Here we introduce a methodology to identify and quantify bias in signal transduction across the plasma membrane without contributions from feedback loops and system bias. We apply the methodology to quantify phosphorylation efficiencies and determine absolute bias coefficients. We show that the signaling of epidermal growth factor receptor (EGFR) to EGF and TGFα is biased towards Y1068 and against Y1173 phosphorylation, but has no bias for epiregulin. We further show that the L834R mutation found in non-small-cell lung cancer induces signaling bias as it switches the preferences to Y1173 phosphorylation. The knowledge gained here challenges the current understanding of EGFR signaling in health and disease and opens avenues for the exploration of biased inhibitors as anti-cancer therapies.
Indexed as
Identifiers
What OpenQuestion holds
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.