ArticleHereditas2020
Microarray data analysis reveals gene expression changes in response to ionizing radiation in MCF7 human breast cancer cells.
Article in Hereditas, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 18 citations in OpenAlex.
- Systems biology-driven identification of biomarkers and significant pathways in radiation-induced hormone-sensitive cancers.Discover oncology · 2025Article
- The expression of establishment of cohesion 1 homolog 2 (ESCO2) in tumor cells and its research progress as a therapeutic target.European journal of medical research · 2025Review
- Identification of Hub of the Hub-Genes From Different Individual Studies for Early Diagnosis, Prognosis, and Therapies of Breast Cancer.Bioinformatics and biology insights · 2024Article
- Article
- Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer.Medicina (Kaunas, Lithuania) · 2023Article
- FOXD1 promotes EMT and cell stemness of oral squamous cell carcinoma by transcriptional activation of SNAI2.Cell & bioscience · 2021Article
- Investigation of Candidate Genes and Pathways in Basal/TNBC Patients by Integrated Analysis.Technology in cancer research & treatmentArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe aim of this study was to identify potential therapeutic target genes for breast cancer (BC) by the investigation of gene expression changes after ionizing radiation (IR) in BC cells. Gene expression profile GSE21748, including BC cell line MCF-7 samples at different time points after IR treatment, were downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified in different time points following IR compared with cell samples before IR, respectively. Gene ontology functions and The Kyoto Encyclopedia of Genes and Genomes pathways of the overlapping DEGs were enriched using DAVID. Transcription factor (TFs)-encoding genes were identified from the overlapping DEGs, followed by construction of transcriptional regulatory network and co-expression network.
resultsA total of 864 overlapping DEGs were identified, which were significantly enriched in regulation of cell proliferation and apoptosis, and cell cycle process. We found that FOXD1, STAT6, XBP1, STAT2, LMO2, TFAP4, STAT3, STAT1 were hub nodes in the transcriptional regulatory network of the overlapping DEGs. The co-expression network of target genes regulated by STAT3, STAT1, STAT6 and STAT2 included some key genes such as BCL2L1.
conclusionSTAT1, STAT2, STAT3, STAT6, XBP1, BCL2L1, CYB5D2, ESCO2, and PARP2 were significantly affected by IR and they may be used as therapeutic gene targets in the treatment of BC.
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.