ReviewGenes2025
The miR-200 Family in Non-Small-Cell Lung Cancer: Molecular Mechanisms, Clinical Applications, and Therapeutic Implications.
Review in Genes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Exosomes and lung cancer: Biogenesis, pathogenic mechanisms, biomarkers, and therapeutic applications.The Journal of international medical research · 2026Review
- Identification of a CSC-Associated miRNA Signature in NSCLC and Functional Characterization of hsa-let-7a-3p.Biomedicines · 2026Article
- A Multi-Level miRNA Regulatory Network Associated with IRF1 Expression in Non-Small Cell Lung Cancer: In Silico Identification of Candidate Biomarkers for Immunotherapy Response.International journal of molecular sciences · 2026Article
- MicroRNA-regulated signaling and tumor microenvironment modulation in lung cancer: mechanistic insights and translational opportunities.Cancer cell international · 2026Review
- Comparable Efficacy of Chitosan/miR-200b-3p and Lipofectamine/miR-200b-3p Delivered by Pluronic F127 Hydrogel to Facilitate Diabetic Wound Healing.International journal of nanomedicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Non-small-cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality worldwide, demanding improved biomarkers and therapeutic approaches. This review synthesizes the extensive evidence positioning the miR-200 family as a master regulator of NSCLC progression. We detail the core molecular circuitry centered on the bistable, double-negative feedback loop between miR-200 and the ZEB1/ZEB2 transcription factors, which governs epithelial-mesenchymal transition (EMT). This review connects this central mechanism to critical clinical challenges, including the development of resistance to EGFR-targeted therapies and the regulation of immune evasion through PD-L1 expression and CD8+ T cell infiltration. We evaluate the strong clinical evidence for the miR-200 family's utility as a diagnostic, prognostic, and predictive biomarker. Finally, we explore emerging therapeutic strategies that target this network, including miRNA replacement, epigenetic reactivation, and rational combinations with immunotherapy and targeted agents. We synthesize evidence positioning the miR-200/ZEB feedback circuit as a central regulatory node in NSCLC that links EMT with therapeutic resistance and immune evasion. Beyond summarizing associations, we interpret how this circuitry could inform biomarker development and rational combinations with targeted and immune therapies. Given heterogeneous study designs and non-standardized assays, translational claims remain provisional; we outline immediate priorities for assay harmonization and biomarker-stratified trials.
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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.