ArticleEvolutionary bioinformatics online2020
Identification of Metastasis-Associated Genes in Triple-Negative Breast Cancer Using Weighted Gene Co-expression Network Analysis.
Article in Evolutionary bioinformatics online, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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Who cites it
9 citing papers in PubMed, 13 citations in OpenAlex.
- Single-cell transcriptome analysis in ovarian steroid cell tumors-not otherwise specified.Journal of ovarian research · 2026Article
- High Expression of IGSF10 Confers an Inhibitory Effect on the Progression of Lung Adenocarcinoma.Journal of cellular and molecular medicine · 2025Article
- Epigenetic regulation of breast ductal carcinoma in situ by miR-217 through DNMT1 and Hedgehog-GLI pathway.Journal of cell communication and signaling · 2025Article
- Deregulated miRNA Expression in Triple-Negative Breast Cancer of Ancestral Genomic-Characterized Latina Patients.International journal of molecular sciences · 2023Article
- Mechanical manipulation of cancer cell tumorigenicity via heat shock protein signaling.Science advances · 2023Article
- Integrative multiomics analysis identifies a metastasis-related gene signature and the potential oncogenic role of EZR in breast cancer.Oncology research · 2022Article
- Integrated Bioinformatics Analysis for the Screening of Hub Genes and Therapeutic Drugs in Androgen Receptor-Positive TNBC.Disease markers · 2022Article
- Role of germline variants in the metastasis of breast carcinomas.Oncotarget · 2022Article
- RUNX1T1, a potential prognostic marker in breast cancer, is co-ordinately expressed with ERα, and regulated by estrogen receptor signalling in breast cancer cells.Molecular biology reports · 2021Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Triple-negative breast cancer (TNBC) is the most aggressive and fatal sub-type of breast cancer. This study aimed to identify metastasis-associated genes that could serve as biomarkers for TNBC diagnosis and prognosis. RNA-seq data and clinical information on TNBC from the Cancer Genome Atlas were used to conduct analyses. Expression data were used to establish co-expression modules using average linkage hierarchical clustering. We used weighted gene co-expression network analysis to explore the associations between gene sets and clinical features and to identify metastasis-associated candidate biomarkers. The K-M plotter website was used to explore the association between the expression of candidate biomarkers and patient survival. In addition, receiver operating characteristic curve analysis was used to illustrate the diagnostic performance of candidate genes. The pale turquoise module was significantly associated with the occurrence of metastasis. In this module, 64 genes were identified, and its functional enrichment analysis revealed that they were mainly associated with transcriptional misregulation in cancer, microRNAs in cancer, and negative regulation of angiogenesis. Further, 4 genes,
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Registered trials
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