ArticleMolecular medicine reports2020
Identification of key genes as potential biomarkers for triple‑negative breast cancer using integrating genomics analysis.
Article in Molecular medicine reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.
- Unraveling Biomarker Signatures in Triple-Negative Breast Cancer: A Systematic Review for Targeted Approaches.International journal of molecular sciences · 2024Pooled it
- CAECC-Subtyper: A Novel Convolutional Autoencoder Framework for Integrating Multi-omics Data in Cancer Subtyping.Biochemical genetics · 2026Article
- Identification of metabolism-associated molecular classification and prognostic genes for medulloblastoma based on bioinformatics analysis.Clinics (Sao Paulo, Brazil) · 2026Article
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- Comprehensive analysis of mRNA and lncRNA expression for predicting lymph node metastasis in cervical cancer: a novel seven-gene signature approach.Frontiers in genetics · 2025Article
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- Identification of a Potential PGK1 Inhibitor with the Suppression of Breast Cancer Cells Using Virtual Screening and Molecular Docking.Pharmaceuticals (Basel, Switzerland) · 2024Article
- A novel bioinformatic approach reveals cooperation between Cancer/Testis genes in basal-like breast tumors.Oncogene · 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
- Identification of DDIT4 as a potential prognostic marker associated with chemotherapeutic and immunotherapeutic response in triple-negative breast cancer.World journal of surgical oncology · 2023Article
- Targeting KK-LC-1 inhibits malignant biological behaviors of triple-negative breast cancer.Journal of translational medicine · 2023Article
- Biomarkers derived from CmP signal network in triple negative breast cancers.Translational breast cancer research : a journal focusing on translational research in breast cancer · 2023Review
- Identification of a five genes prognosis signature for triple-negative breast cancer using multi-omics methods and bioinformatics analysis.Cancer gene therapy · 2022Article
- Lift the Veil of Breast Cancers Using 4 or Fewer Critical Genes.Cancer informatics · 2022Article
- Article
- Machine learning assisted analysis of breast cancer gene expression profiles reveals novel potential prognostic biomarkers for triple-negative breast cancer.Computational and structural biotechnology journal · 2022Article
- Cloning and Functional Analysis of Rat Tweety-Homolog 1 Gene Promoter.Neurochemical research · 2021Article
- Multi-Gene Testing Overview with a Clinical Perspective in Metastatic Triple-Negative Breast Cancer.International journal of molecular sciences · 2021Review
- Multiomics analysis reveals CT83 is the most specific gene for triple negative breast cancer and its hypomethylation is oncogenic in breast cancer.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Triple‑negative breast cancer (TNBC) accounts for the worst prognosis of all types of breast cancers due to a high risk of recurrence and a lack of targeted therapeutic options. Extensive effort is required to identify novel targets for TNBC. In the present study, a robust rank aggregation (RRA) analysis based on genome‑wide gene expression datasets involving TNBC patients from the Gene Expression Omnibus (GEO) database was performed to identify key genes associated with TNBC. A total of 194 highly ranked differentially expressed genes (DEGs) were identified in TNBC vs. non‑TNBC. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis was utilized to explore the biological functions of the identified genes. These DEGs were mainly involved in the biological processes termed positive regulation of transcription from RNA polymerase II promoter, negative regulation of apoptotic process, response to drug, response to estradiol and negative regulation of cell growth. Genes were mainly involved in the KEGG pathway termed estrogen signaling pathway. The aberrant expression of several randomly selected DEGs were further validated in cell lines, clinical tissues and The Cancer Genome Atlas (TCGA) cohort. Furthermore, all the top‑ranked DEGs underwent survival analysis using TCGA database, of which overexpression of 4 genes (FABP7, ART3, CT83, and TTYH1) were positively correlated to the life expectancy (P<0.05) of TNBC patients. In addition, a model consisting of two genes (FABP7 and CT83) was identified to be significantly associated with the overall survival (OS) of TNBC patients by means of Cox regression, Kaplan‑Meier, and receiver operating characteristic (ROC) analyses. In conclusion, the present study identified a number of key genes as potential biomarkers involved in TNBC, which provide novel insights into the tumorigenesis of TNBC at the gene level and may serve as independent prognostic factors for TNBC prognosis.
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