ArticleJournal of applied genetics2024
Blood-based microRNA profiling unveils complex molecular dynamics in breast cancer.
Article in Journal of applied genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 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
2 citing papers in PubMed, 2 citations in OpenAlex.
- Enhancing the miRNA Detection Sensitivity of DNA Origami Book Biosensors Using Lock Modifications and a Polymer Additive.Small (Weinheim an der Bergstrasse, Germany) · 2025Article
- Unveiling miRNA30b's Role in Suppressing ADAM12 to Combat Triple-Negative Breast Cancer.The breast journal · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBreast cancer, a genetically intricate disease with diverse subtypes, exhibits heightened incidence globally. In this study, we aimed to investigate blood-based microRNAs (miRNAs) as potential biomarkers for breast cancer. The primary objectives were to explore the role of miRNAs in cancer-related processes, assess their differential expression between breast cancer patients and healthy individuals, and contribute to a deeper understanding of the molecular underpinnings of breast cancer.
methodsMiRNA extraction was performed on 40 breast cancer patients and adjacent normal tissues using a commercial RNA isolation kit. Total RNA quantification and quality assessment were conducted with advanced technologies. MiRNA profiling involved reverse transcription, labeling, and hybridization on Agilent human miRNA arrays (V2). Bioinformatics analysis utilized the DIANA system for target gene prediction and the DIANA-mirPath tool for pathway enrichment analysis. Selected miRNAs underwent validation through quantitative real-time PCR.
resultsPrincipal component analysis revealed overlapping miRNA expression patterns in primary and malignant breast tumors, underscoring the genetic complexity involved. Statistical analysis identified 54 downregulated miRNAs in malignant tumors and 38 in primary tumors compared to controls. Bioinformatics analysis implicated several pathways, including Wnt, TGF-b, ErbB, and MAPK signaling. Validation through qRT-PCR confirmed altered expression of hsa-miR-130a, hsa-miR-21, hsa-miR-223, and hsa-let-7c key miRNAs, highlighting their significance in breast cancer. The results from microarray were further validated by qPCR and the expression of which are downregulated in breast cancer was detected.
conclusionThis study provides significant insights into distinct miRNA expression patterns in normal and malignant breast tissues. The overlapping miRNA profiles in primary and malignant tumors underscore the complexity of genetic regulation in breast cancer. The identification of deregulated miRNAs and affected pathways contributes to our understanding of breast cancer pathogenesis. The validated miRNAs hold potential as diagnostic and prognostic markers, offering avenues for further clinical exploration in breast cancer research.
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.