ReviewCell proliferation2026
Non-Coding RNAs in Breast Cancer Radioresistance: Mechanisms, Functional Roles and Translational Potentials.
Review in Cell proliferation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- The neuroimmune axis in breast cancer: from mechanistic insights to clinical applications.BMC medicine · 2026Review
- Non-Coding RNAs in Breast Cancer Radioresistance: Mechanisms, Functional Roles and Translational Potentials.Cell proliferation · 2026Review
- The role of epigenetic alterations in canine mammary cancer.The Journal of reproduction and development · 2026Review
- Current Perspectives on Radiosensitizers in Cancer Radiotherapy.International journal of nanomedicine · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Breast cancer remains the most prevalent malignancy among women, and radiotherapy plays a pivotal role in reducing local recurrence and improving prognosis. However, the emergence of radioresistance in a subset of patients significantly compromises treatment efficacy, underscoring the need for a deeper understanding of the underlying molecular mechanisms. In recent years, non-coding RNAs (ncRNAs) have emerged as key regulators of gene expression and have garnered increasing attention for their roles in mediating radioresistance in breast cancer. This review systematically summarises the major molecular mechanisms by which ncRNAs contribute to breast cancer radioresistance, including cell cycle regulation, DNA damage repair, programmed cell death (e.g., apoptosis, autophagy and ferroptosis), oxidative stress response, tumour microenvironment remodelling and maintenance of cancer stem cell properties. On the translational front, RNA-based therapeutic approaches-including antisense oligonucleotides (ASOs), small interfering RNAs (siRNAs), miRNA mimics and CRISPR/Cas9-offer promising avenues for radiosensitisation, yet face substantial clinical hurdles. These include immune activation, poor delivery specificity, intracellular trafficking barriers and limited stability. Advances in chemical modifications and nanoparticle-based delivery systems-such as redox-responsive nanocarriers-have shown potential in enhancing the efficacy and safety of ncRNA-targeted therapies. Despite encouraging progress, clinical translation remains constrained by a lack of methodological standardisation, insufficient high-quality clinical data, limited biomarker reliability, suboptimal target selection and unresolved safety concerns. Future efforts should prioritise optimisation of delivery platforms, validation of multi-ncRNA biomarker panels in large, multicentre cohorts and integration of multi-omics data to reconstruct comprehensive regulatory networks, ultimately accelerating the clinical deployment of ncRNA-based radiosensitisation strategies.
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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.