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Studying Triple Negative Breast Cancer Using Orthotopic Breast Cancer Model
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Studying Triple Negative Breast Cancer Using Orthotopic Breast Cancer Model

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Integrated network analysis and machine learning approach for the identification of key genes of triple-negative

Leimarembi Devi Naorem1, Mathavan Muthaiyan1, Amouda Venkatesan1

  • 1Centre for Bioinformatics, School of Life Sciences, Pondicherry University, Pondicherry, India.

Journal of Cellular Biochemistry
|October 11, 2018
PubMed

Insights

Researchers identified key genes and cell cycle pathways in triple-negative breast cancer (TNBC). This discovery offers potential new therapeutic targets for this aggressive cancer subtype, improving treatment options.

Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • Triple-negative breast cancer (TNBC) is aggressive with poor prognosis, lacking targeted therapies beyond chemotherapy.
  • Identifying novel therapeutic targets and understanding TNBC's biological mechanisms are critical.

Purpose of the Study:

  • To discover promising therapeutic targets for TNBC.
  • To investigate new insights into the biological mechanisms of TNBC.

Main Methods:

  • Integrated six microarray datasets (463 non-TNBC, 405 TNBC) using meta-analysis.
  • Constructed a protein-protein interaction network to identify 29 hub genes.
  • Utilized machine learning for feature selection, identifying 16 key hub genes (12 upregulated, 4 downregulated).
  • Developed a Naïve Bayes classifier to distinguish TNBC from non-TNBC samples.

Main Results:

  • Identified 1075 differentially expressed genes and 29 hub genes.
  • Selected 16 significant hub genes, including upregulated AURKB, CCNB2, CDC20, and downregulated CCND1, GLI3.
  • Achieved high classification accuracy (ROC 0.93-0.98) for TNBC detection using the 16-gene classifier.
  • Gene Ontology and KEGG pathway analyses revealed enrichment in mitotic and cell cycle processes.

Conclusions:

  • The identified hub genes and cell cycle pathways provide a deeper understanding of TNBC's molecular mechanisms.
  • These findings highlight potential novel therapeutic targets for TNBC treatment.
Keywords:
differentially expressed genesprotein-protein interaction networkreceiver operating curvetriple-negative breast cancer

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