ArticleCancer cell international2019
Identification of potential key genes and pathways predicting pathogenesis and prognosis for triple-negative breast cancer.
Article in Cancer cell international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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29 citing papers in PubMed, 45 citations in OpenAlex.
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- Identification of a minimum number of genes to predict triple-negative breast cancer subgroups from gene expression profiles.Human genomics · 2022Article
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- Role of opiorphin genes in prostate cancer growth and progression.Future oncology (London, England) · 2021Article
- Identification of potential core genes and pathways predicting pathogenesis in head and neck squamous cell carcinoma.Bioscience reports · 2021Article
- Identification of potential oncogenes in triple-negative breast cancer based on bioinformatics analyses.Oncology letters · 2021Article
- Profiles of immune cell infiltration and immune-related genes in the tumor microenvironment of esophageal squamous cell carcinoma.BMC medical genomics · 2021Article
Corrections and comments
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Authors and funding
15 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTriple negative breast cancer (TNBC) is a specific subtype of breast cancer with a poor prognosis due to its aggressive biological behaviour and lack of therapeutic targets. We aimed to explore some novel genes and pathways related to TNBC prognosis through bioinformatics methods as well as potential initiation and progression mechanisms.
methodsBreast cancer mRNA data were obtained from The Cancer Genome Atlas database (TCGA). Differential expression analysis of cancer and adjacent cancer, as well as, triple negative breast cancer and non-triple negative breast cancer were performed using R software. The key genes related to the pathogenesis were identified by functional and pathway enrichment analysis and protein-protein interaction network analysis. Based on univariate and multivariate Cox proportional hazards model analyses, a gene signature was established to predict overall survival. Receiver operating characteristic curve was used to evaluate the prognostic performance of our model.
resultsBased on mRNA expression profiling of breast cancer patients from the TCGA database, 755 differentially expressed overlapping mRNAs were detected between TNBC/non-TNBC samples and normal tissue. We found eight hub genes associated with the cell cycle pathway highly expressed in TNBC. Additionally, a novel six-gene (
conclusionsThe eight hub genes we identified might be tightly correlated with TNBC pathogenesis. The 6-mRNA signature established might act as an independent biomarker with a potentially good performance in predicting overall survival.
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