ArticleBritish journal of cancer2024
Circulating miRNA panels as a novel non-invasive diagnostic, prognostic, and potential predictive biomarkers in non-small cell lung cancer (NSCLC).
Article in British journal of cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 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
34 citing papers in PubMed.
- Circulating MicroRNAs in non-small cell lung cancer: Clinical potential, analytic pitfalls, and barriers to implementation.The journal of liquid biopsy · 2026Review
- Single-cell and spatial transcriptomics identify a JUNB+ neutrophil subset enriched in immune-excluded regions of lung adenocarcinoma.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026Article
- Multi-Institutional Integration of Circulating miRNAs and Protein Tumor Markers for Early Lung Cancer Detection.JTO clinical and research reports · 2026Article
- Clinical significance of miRNAs and exosomal miRNAs in non-small cell lung cancer: diagnostic, prognostic, and therapeutic perspectives.Journal of human genetics · 2026Review
- An RNase domain-dependent microRNA detection with DNA-spiked nanocage for accurate cancer diagnosis.Nature communications · 2026Article
- Identification of PI3K alpha inhibitors through large-scale virtual screening and integrated molecular modeling, biophysical characterization, and ADMET profiling.Scientific reports · 2026Article
- MiR-23c Regulates the Resistance to Gefitinib in EGFR Mutant Non-Small-Cell Lung Cancer Cells.Cells · 2026Article
- miR-542-3p targets TTF1 to regulate proliferation, invasion, and migration of lung adenocarcinoma via the MAPK signaling pathway.Scientific reports · 2026Article
- Transcriptomic and multi-layer variant analysis identifies STAT3 and HIF1A as central regulators of regulated cell death pathways in lung squamous cell carcinoma.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Article
- Review
- Biologically Informed Treatment Approaches Toward Personalized Therapeutic Strategies in Lung Cancer.International journal of molecular sciences · 2026Article
- Research progress of MicroRNA in lung cancer.Discover oncology · 2026Review
- Integrative multiomic profiling of cfDNA methylation and EV-miRNAs identifies immunotherapy-outcome molecular subtypes in NSCLC.Journal for immunotherapy of cancer · 2026Article
- Article
- Targeting Oncogenic miRNAs in NSCLC: Therapeutic Strategies and Emerging Approaches.Cancer management and research · 2026Review
- Translational insights into miR-126 and miR-423: biomarkers and therapeutic targets in cancer, cardiovascular, metabolic and kidney diseases.Frontiers in molecular biosciences · 2026Review
- The clinical significance of circulating microRNAs as biomarkers in lung cancer diagnosis and prognosis.Discover oncology · 2025Review
- hsa-let-7b-5p-associated BUB1/TMPO-AS1 ceRNA axis identified as a potential biomarker in lung adenocarcinoma.Cell division · 2025Article
- Blood-Based miRNA Panels for Timely Detection of Non-Small-Cell Lung Cancer: From Biomarker Discovery to Clinical Translation.International journal of molecular sciences · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNon-small cell lung cancer (NSCLC) is characterised by its aggressiveness and poor prognosis. Early detection and accurate prediction of therapeutic responses remain critical for improving patient outcomes. In the present study, we investigated the potential of circulating microRNA (miRNA) as non-invasive biomarkers in patients with NSCLC.
methodsWe quantified miRNA expression in plasma from 122 participants (78 NSCLC; 44 healthy controls). Bioinformatic tools were employed to identify miRNA panels for accurate NSCLC diagnosis. Validation was performed using an independent publicly available dataset of more than 4000 NSCLC patients. Next, we correlated miRNA expression with clinicopathological information to identify independent prognostic miRNAs and those predictive of anti-PD-1 treatment response.
resultsWe identified miRNA panels for lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) diagnosis. The LUAD panel consists of seven circulating miRNAs (miR-9-3p, miR-96-5p, miR-147b-3p, miR-196a-5p, miR-708-3p, miR-708-5p, miR-4652-5p), while the LUSC panel comprises nine miRNAs (miR-130b-3p, miR-269-3p, miR-301a-5p, miR-301b-5p, miR-744-3p, miR-760, miR-767-5p, miR-4652-5p, miR-6499-3p). Additionally, miR-135b-5p, miR-196a-5p, miR-31-5p (LUAD), and miR-205 (LUSC) serve as independent prognostic markers for survival. Furthermore, two miRNA clusters, namely miR-183/96/182 and miR-767/105, exhibit predictive potential in anti-PD-1-treated LUAD patients.
conclusionsCirculating miRNA signatures demonstrate diagnostic and prognostic value for NSCLC and may guide treatment decisions in clinical practice.
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.