ReviewCancers2022
Fluorescence Imaging of Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitor Resistance in Non-Small Cell Lung Cancer.
Review in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 8 citations in OpenAlex.
- Predictive modeling of peripheral blood EGFR positivity in patients with advanced primary non-small cell lung cancer.Translational lung cancer research · 2026Article
- DR.DEGMON: self-explainable deep neural network for drug-induced cell viability prediction incorporating differentially expressed genes and gene ontology.BMC medical genomics · 2026Article
- Recent Progress in Treating Airway Mucus Hypersecretion by Targeting the Epidermal Growth Factor Receptor Signaling Pathway.Pediatric discovery · 2026Review
- Programmed Cell Death Protein 10 (PDCD10) Regulates Vesicle Trafficking and Contributes to the Progression of Clear Cell Renal Cell Carcinoma.Journal of extracellular vesicles · 2025Article
- ZD6474 attenuates TGF-β1-induced fibrosis in human Tenon fibroblasts and inhibits neovascularization via AKT-mTOR signaling pathway.International ophthalmology · 2023Article
- A predictive model of computed tomography and clinical features of EGFR gene mutation in lung adenocarcinoma.Science progressArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Non-small cell lung cancer (NSCLC) is a complex disease often driven by activating mutations or amplification of the epidermal growth factor receptor (EGFR) gene, which expresses a transmembrane receptor tyrosine kinase. Targeted anti-EGFR treatments include small-molecule tyrosine kinase inhibitors (TKIs), among which gefitinib and erlotinib are the best studied, and their function more often imaged. TKIs block EGFR activation, inducing apoptosis in cancer cells addicted to EGFR signals. It is not understood why TKIs do not work in tumours driven by EGFR overexpression but do so in tumours bearing classical activating EGFR mutations, although the latter develop resistance in about one year. Fluorescence imaging played a crucial part in research efforts to understand pro-survival mechanisms, including the dysregulation of autophagy and endocytosis, by which cells overcome the intendedly lethal TKI-induced EGFR signalling block. At their core, pro-survival mechanisms are facilitated by TKI-induced changes in the function and conformation of EGFR and its interactors. This review brings together some of the main advances from fluorescence imaging in investigating TKI function and places them in the broader context of the TKI resistance field, highlighting some paradoxes and suggesting some areas where super-resolution and other emerging methods could make a further contribution.
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.