ReviewCell death discovery2025
Exosomal circRNAs: key modulators in breast cancer progression.
Review in Cell death discovery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- The role of targeted exosomes in improving drug delivery in breast cancer: challenges and prospects.Molecular biology reports · 2026Review
- The updated role of exosomes in cancer diagnosis and therapy.Discover oncology · 2026Review
- Exosomal circRNAs in hepatocellular carcinoma: Implications for the development and therapeutic resistance of hepatocellular carcinoma (Review).International journal of oncology · 2026Review
- Circular RNA Hsa_circ_0062403 Acts as a Potential Prognostic Biomarker for Early Recurrence of Hepatocellular Carcinoma.International journal of general medicine · 2026Article
- Unravelling the nexus of non-coding RNAs in cancer stemness and therapeutic drug resistance.Frontiers in cell and developmental biology · 2026Review
- CircTranslational oncology · 2025Article
- CircRNA in non‑small cell lung cancer: Potential biomarkers and therapeutic targets (Review).Molecular medicine reports · 2025Review
- Exploring the Clinical Transformation of circRNA as a Biomarker in Breast Cancer.Cancer control : journal of the Moffitt Cancer CenterReview
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
Breast cancer (BC) poses significant challenges globally, necessitating a deeper understanding of its complexities. Exosomes are cell-specific secreted extracellular vesicles of interest, characterized by a lipid bilayer structure. Exosomes can carry a variety of bioactive components, including nucleic acids, lipids, amino acids, and small molecules, to mediate intercellular signaling. CircRNAs are a novel class of single-stranded RNA molecules, characterized by a closed-loop structure. CircRNAs mainly exert ceRNA functions to intricately modulate gene expression and signaling pathways in breast cancer, influencing tumor progression and therapeutic responses. The unique packaging of circRNAs within exosomes serves as novel genetic information transmitters, facilitating communication between BC cells and microenvironmental cells, thereby regulating critical aspects of BC progression, immune evasion, and drug resistance. Besides, exosomal circRNAs possess the capabilities of serving as diagnostic and therapeutic biomarkers of BC, due to their stability, specificity, and regulatory roles in tumorigenesis and metastasis. Therefore, this review aims to elucidate the novel roles and mechanisms of exosomal circRNAs in BC progression, as well as their potential for diagnosis and therapeutics. The ongoing investigations of exosomal circRNAs will potentially revolutionize treatment paradigms and improve patient outcomes of BC.
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.