ArticleBioengineered2021
Identification of significant genes and therapeutic agents for breast cancer by integrated genomics.
Article in Bioengineered, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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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
6 citing papers in PubMed.
- Breast cancer prediction based on gene expression data using interpretable machine learning techniques.Scientific reports · 2025Article
- Case-Case Genome-Wide Analyses Identify Subtype-Informative Variants That Confer Risk for Breast Cancer.Cancer research · 2024Article
- A multi-tissue, splicing-based joint transcriptome-wide association study identifies susceptibility genes for breast cancer.American journal of human genetics · 2024Article
- Unraveling the MicroRNA tapestry: exploring the molecular dynamics of locoregional recurrent rectal cancer.Frontiers in oncology · 2024Article
- Cocktail hepatocarcinoma therapy by a super-assembled nano-pill targeting XPO1 and ATR synergistically.Journal of pharmaceutical analysis · 2023Article
- Long non-coding RNA MRPS30 divergent transcript can be detected in the cytoplasm of triple-negative breast cancer cells and is targeted by microRNA-130b.Bioengineered · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Breast cancer is the most commonly diagnosed malignancy in women; thus, more cancer prevention research is urgently needed. The aim of this study was to predict potential therapeutic agents for breast cancer and determine their molecular mechanisms using integrated bioinformatics. Summary data from a large genome-wide association study of breast cancer was derived from the UK Biobank. The gene expression profile of breast cancer was from the Oncomine database. We performed a network-wide association study and gene set enrichment analysis to identify the significant genes in breast cancer. Then, we performed Gene Ontology analysis using the STRING database and conducted Kyoto Encyclopedia of Genes and Genomes pathway analysis using Cytoscape software. We verified our results using the Gene Expression Profile Interactive Analysis, PROgeneV2, and Human Protein Atlas databases. Connectivity map analysis was used to identify small-molecule compounds that are potential therapeutic agents for breast cancer. We identified 10 significant genes in breast cancer based on the gene expression profile and genome-wide association study. A total of 65 small-molecule compounds were found to be potential therapeutic agents for breast cancer.
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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.