ArticleCancer medicine2025
Text Mining Strategy Identifies Gene Networks Under Control of miR-21 in Breast Cancer Development.
Article in Cancer medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Text Mining Strategy Identifies Gene Networks Under Control of miR-21 in Breast Cancer Development.Cancer medicine · 2025Article
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
backgroundMicroRNAs (miRNAs) are small regulatory molecules that play a critical role in various biological processes by regulating gene expression. They have emerged as crucial players in cancer development, including breast cancer. However, individual research studies may be subject to specific biases.
methodsTo gain a more comprehensive understanding of miRNA involvement in breast cancer, we employed a large-scale analysis of miRNA studies retrieved from PubMed. Our approach involved tokenizing abstracts to identify key biomedical entities (e.g., miRNA, gene, disease) and constructing miRNA-cancer co-occurrence networks using bioinformatic analysis.
resultsThis analysis revealed miR-21 as the most frequently studied miRNA in breast cancer research, with a significant difference compared to other miRNAs. Network analysis identified SMAD3, PIK3R1, STAT3, and TP53 as key regulators potentially affecting pathways like TGF-β signaling and p53 signaling. Additionally, our analysis suggests that genes associated with miR-21 are often downregulated in tumors and exhibit a positive correlation with T cell infiltration, particularly CD8+ T cells, potentially indicating a favorable prognosis.
conclusionOur findings highlight miR-21 as a central regulatory hub and potential biomarker in breast cancer. While informative, the results are derived from literature-based data and may be influenced by text-mining limitations, underscoring the need for experimental validation.
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.