ArticleTechnology in cancer research & treatment
Screening of Prognostic Factors in Early-Onset Breast Cancer.
Article in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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The trial behind it
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Who cites it
10 citing papers in PubMed, 17 citations in OpenAlex.
- Bioinformatic Characterization of Genes That Are Correlated to the Progression of Breast Cancer to Breast Cancer Brain Metastasis.Cancer reports (Hoboken, N.J.) · 2025Article
- Prognostic analysis of early-onset and late-onset nasopharyngeal carcinoma: a retrospective study.Discover oncology · 2024Article
- Targeted Therapies and Drug Resistance in Advanced Breast Cancer, Alternative Strategies and the Way beyond.Cancers · 2024Review
- Exploring Tumor-Immune Interactions in Co-Culture Models of T Cells and Tumor Organoids Derived from Patients.International journal of molecular sciences · 2023Review
- Inhibition of squalene epoxidase linking with PI3K/AKT signaling pathway suppresses endometrial cancer.Cancer science · 2023Article
- Bioinformatics and network-based screening and discovery of potential molecular targets and small molecular drugs for breast cancer.Frontiers in pharmacology · 2022Article
- Targeting the key cholesterol biosynthesis enzyme squalene monooxygenasefor cancer therapy.Frontiers in oncology · 2022Review
- Article
- Squalene epoxidase expression is associated with breast tumor progression and with a poor prognosis in breast cancer.Oncology letters · 2021Article
- Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGene expression profiles from early-onset breast cancer and normal tissues were analyzed to explore the genes and prognostic factors associated with breast cancer.
methodsGSE109169 and GSE89116 were obtained from the database of Gene Expression Omnibus. We firstly screened the differentially expressed genes between tumor samples and normal samples from patients with early-onset breast cancer. Based on database for annotation, visualization and intergrated discovery (DAVID) tool, functional analysis was calculated. Transcription factor-target regulation and microRNA-target gene network were constructed using the tool of transcriptional regulatory relatitionships unraveled by sentence-based text mining (TRRUST) and miRWalk2.0, respectively. The prognosis-related survival information was compiled based on The Cancer Genome Atlas breast cancer clinical data.
resultsA total of 708 differentially expressed genes from GSE109169 data sets and 358 differentially expressed genes from GSE89116 data sets were obtained, of which 122 common differentially expressed genes including 102 uniformly downregulated genes and 20 uniformly upregulated genes were screened. Protein-protein interaction network with a total of 83 nodes and 157 relationship pairs was obtained, and genes in protein-protein interaction, such as peroxisome proliferator-activated receptor γ,
conclusions
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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.