ReviewTranslational cancer research2024
Exosomal microRNAs in lung cancer: a narrative review.
Review in Translational cancer research, 2024. 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
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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.
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Who cites it
9 citing papers in PubMed.
- Identification of Potential Exosomal miRNA-mRNA Regulatory Network Relevant to Tuberculous-Associated Lung Cancer.Biomedicines · 2026Article
- Cancer-Derived Exosomes: A Cross-Cancer Comparative Analysis of Exosomal Proteins and MicroRNAs.International journal of molecular sciences · 2026Review
- Cell-type Specific Alteration ofbioRxiv : the preprint server for biology · 2026Article
- MicroRNA-regulated signaling and tumor microenvironment modulation in lung cancer: mechanistic insights and translational opportunities.Cancer cell international · 2026Review
- Progression and Metastasis of Lung Cancer: Clinical Features, Molecular Mechanisms, and Clinical Managements.MedComm · 2025Review
- MiR-301a-3p Promotes Triple-Negative Breast Cancer Progression via PTEN Suppression in Tumor Cells and the Microenvironment.World journal of oncology · 2025Article
- Exosomal biomarkers and therapeutics in lung cancer: a narrative review on their role in early detection and targeted treatment.Translational lung cancer research · 2025Review
- Dendritic Cell-Derived Exosomes: Next Generation of Cancer Immunotherapy.Biomedicines · 2025Review
- Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Objective: Exosomes are nanoscale extracellular vesicles secreted by cells, which can release bioactive macromolecules, such as microRNA (miRNA) to receptor cells. Exosomes can efficiently penetrate various biological barriers which mediate intercellular communication. MiRNA are a class of non-coding RNA that primarily regulate messenger RNA (mRNA) at the post-transcriptional level. MiRNA is abundant in exosomes, which plays an important role by being transported and released through exosomes secreted by lung cancer cells. This review aims to elucidate the roles of exosome-derived miRNAs in lung cancer. Methods: We focused on the roles of exosome-derived miRNAs in cancer occurrence and development, including angiogenesis, cell proliferation, invasion, metastasis, immune escape, drug resistance, and their clinical value as new diagnostic and prognostic markers for lung cancer. Key Content and Findings: Exosomal miRNA can not only affect angiogenesis of lung cancer, induce epithelial-mesenchymal transformation, and promote reprogramming of tumor microenvironment, but also affect immune regulation and drug resistance transmission and participate in regulating lung cancer cell proliferation. Therefore, understanding the regulatory roles of exosomal miRNAs in tumor invasion and metastasis can provide new ideas for the treatment of lung cancer. Conclusions: Exosomal miRNA can provide some unique ideas on how to improve the efficiency of diagnosis and treatment of lung cancer in the future. Targeting tumor-specific exosomal miRNA represents a new strategy for clinical treatment of lung cancer, which can provide potential non-invasive biomarkers in the early diagnosis of lung cancer. Investigation of the involvement of exosomal miRNAs in the occurrence and progression of tumors can yield new opportunities for the clinical diagnosis and treatment of lung cancer.
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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.