ArticleInternational journal of molecular sciences2025
Comparison Bioinformatic Analysis of Extracellular Vesicles-Related Genes and MicroRNAs in Breast Cancer.
Article in International journal of molecular sciences, 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
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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
1 citing paper in PubMed.
- AINR: attention-guided implicit neural representations for spatial domain identification in spatial transcriptomics.Bioinformatics advances · 2026Article
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Breast cancer (BC) remains a leading cause of cancer-related mortality in women, with treatment challenges due to the lack of targeted therapies. Extracellular vesicles (EVs) play a crucial role in BC progression by carrying bioactive molecules. This study analyzed EV-associated molecules (ENPEP, TIMP1, CD36, MARCKS, DAB2, CXCL14, miR-181b-5p, miR-222-3p) using bioinformatics tools. We used GEPIA2; Human Protein Atlas (HPA) 24.0; bc-GenExMiner v5.1; UALCAN 2022; Kaplan-Meier plotter 2025; ENCORI database v2.0; Enrichr-KG web tool 2021; Cancer Hallmark Enrichment tool 2025; Tumor, Normal, and Metastatic (TNM) plot database 2025; MicroRNA Target Prediction Database 6.0; TargetScan 8.0; and STRING database 12.0. CD36, DAB2, and CXCL14 were significantly downregulated, while TIMP1 was upregulated in BC tissues (
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