ArticleOncology letters2019
MicroRNA-16 sensitizes drug-resistant breast cancer cells to Adriamycin by targeting Wip1 and Bcl-2.
Article in Oncology letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 14 citations in OpenAlex.
- IKBKE downregulation increases chemosensitivity through pyroptosis mediated by the caspase-3/GSDME pathway in pancreatic cancer.Journal of experimental & clinical cancer research : CR · 2026Article
- Non-coding RNAs, a double-edged sword in breast cancer prognosis.Cancer cell international · 2025Review
- eIF3b-driven autophagy and Wnt/β-catenin crosstalk: a novel regulatory axis in adriamycin resistance of breast cancer.Oncology reviews · 2025Review
- Modulatory effects of miRNAs in doxorubicin resistance: A mechanistic view.Functional & integrative genomics · 2024Review
- The related miRNAs involved in doxorubicin resistance or sensitivity of various cancers: an update.Cancer chemotherapy and pharmacology · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Clinical evidence indicates that drug resistance is a major obstacle in the treatment of breast cancer (BC). Drug resistance results in the disease being uncontrollable, and leads to high mortality rates. The aim of the present study was to investigate the chemosensitizing effect of microRNA (miR)-16 on Adriamycin (ADM)-resistant BC cells and the associated mechanisms. BC tumors from 40 patients were collected and reverse transcription-quantitative PCR was used to examine the expression of miR-16. ADM-sensitive (MCF-7/S) and -resistant (MCF-7/A) BC cell lines were used to determine the expression of miR-16 prior to and following transfection with miR-16 mimics or inhibitor. The effects of increased and decreased miR-16 expression on the chemosensitivity of BC cells to ADM was analyzed using MTT, colony survival and flow cytometry assays. miR-16 was found to regulate wild-type p53-induced phosphatase 1 (Wip1) and Bcl-2 expression, as confirmed by western blotting, immunofluorescence staining and luciferase reporter assays. miR-16 expression in drug-resistant tumor tissues and cells was decreased, compared with that the drug-sensitive equivalents. Overexpression of miR-16 in MCF-7/A was associated with a sharp downregulation of Wip1 and Bcl-2 expression, leading to increased ADM-induced cell apoptosis and sensitization of MCF-7/A cells to ADM treatment. Taken together, the results demonstrate that miR-16 may serve as an effective chemosensitizing target to enhance the effects of chemotherapy in drug-resistant BC cells with high Wip1 and Bcl-2 expression. This provides a novel approach to improving the chemotherapeutic efficacy in drug-resistant BC via regulation of miRs.
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.