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Updated: Dec 30, 2025
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Identification of key genes as potential biomarkers for triple‑negative breast cancer using integrating genomics
Guansheng Zhong1, Weiyang Lou2, Qinyan Shen3
1Department of Thyroid and Breast Surgery, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, Zhejiang 310014, P.R. China.
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.
Insights
This study identifies key genes linked to triple-negative breast cancer (TNBC) prognosis. Overexpression of FABP7 and CT83 may serve as independent prognostic factors for TNBC patients, offering new therapeutic targets.
Area of Science:
- Genomics
- Oncology
- Bioinformatics
Background:
- Triple-negative breast cancer (TNBC) presents a poor prognosis due to high recurrence rates and limited targeted therapies.
- Identifying novel therapeutic targets and biomarkers is crucial for improving TNBC patient outcomes.
Purpose of the Study:
- To identify key genes associated with TNBC using genome-wide gene expression data.
- To explore the biological functions and pathways of these identified genes.
- To validate the prognostic significance of candidate genes in TNBC.
Main Methods:
- Robust rank aggregation (RRA) analysis on Gene Expression Omnibus (GEO) datasets for TNBC patients.
- Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis.
- Validation of differentially expressed genes (DEGs) in cell lines, clinical tissues, and The Cancer Genome Atlas (TCGA) cohort; survival analysis using TCGA data.
Main Results:
- 194 highly ranked DEGs were identified between TNBC and non-TNBC samples.
- Enrichment analysis revealed involvement in transcription regulation, apoptosis, drug response, and estrogen signaling.
- Overexpression of FABP7, ART3, CT83, and TTYH1 correlated with improved TNBC patient survival (P<0.05).
- A two-gene model (FABP7 and CT83) significantly associated with overall survival (OS) in TNBC patients.
Conclusions:
- The study identified several key genes as potential biomarkers for TNBC.
- These findings offer novel insights into TNBC tumorigenesis at the gene level.
- FABP7 and CT83 may serve as independent prognostic factors for TNBC, guiding future therapeutic strategies.
