ArticleEcancermedicalscience2015
miRNAs and resistance to EGFR-TKIs in EGFR-mutant non-small cell lung cancer: beyond 'traditional mechanisms' of resistance.
Article in Ecancermedicalscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 13 citations in OpenAlex.
- MiRNA-Based Therapies for Lung Cancer: Opportunities and Challenges?Biomolecules · 2023Review
- Cell Behavior of Non-Small Cell Lung Cancer Is at EGFR and MicroRNAs Hands.International journal of molecular sciences · 2021Review
- Article
- Mechanism research of miR-34a regulates Axl in non-small-cell lung cancer with gefitinib-acquired resistance.Thoracic cancer · 2020Article
- Overcoming acquired resistance of gefitinib in lung cancer cells without T790M by AZD9291 or Twist1 knockdown in vitro and in vivo.Archives of toxicology · 2019Article
- Potential Regulatory Roles of MicroRNAs and Long Noncoding RNAs in Anticancer Therapies.Molecular therapy. Nucleic acids · 2018Review
- Plasma microRNA alterations between EGFR-activating mutational NSCLC patients with and without primary resistance to TKI.Oncotarget · 2017Article
- miRNAs as Biomarkers and Therapeutic Targets in Non-Small Cell Lung Cancer: Current Perspectives.Targeted oncology · 2017Review
- MicroRNA In Lung Cancer: Novel Biomarkers and Potential Tools for Treatment.Journal of clinical medicine · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) have dramatically changed the prognosis of advanced non-small cell lung cancers (NSCLCs) that harbour specific EGFR activating mutations. However, the efficacy of an EGFR-TKI is limited by the onset of acquired resistance, usually within one year, in virtually all treated patients. Moreover, a small percentage of EGFR-mutant NSCLCs do not respond to an EGFR-TKI, thus displaying primary resistance. At the present time, several mechanisms of either primary and acquired resistance have been elucidated, and new drugs are currently under preclinical and clinical development in order to overcome resistance to treatment. Nevertheless, there still remains much to be thoroughly investigated, as so far research has mainly focused on the role of proteincoding genes involved in resistance to EGFR-TKIs. On the other hand, in line with the data underscoring the relevance of non-coding RNAs in the pathogenesis of lung cancer and modulation of response to systemic therapies, microRNAs (miRNAs) have been supposed to play an important role in resistance to EGFR-TKIs. The aim of this review is to briefly summarise the existing relationship between miRNAs and resistance to EGFR-TKIs, and also focusing on the possible clinical applications of miRNAs in reverting and overcoming such resistance.
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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.