Multidimensional computational study to understand non-coding RNA interactions in breast cancer metastasis

Sohini Chakraborty1, Satarupa Banerjee2

  • 1Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, 632014, Tamil Nadu, India.

Scientific Reports
|September 22, 2023
PubMed

Insights

This study deciphers gene and non-coding RNA interactions in breast cancer metastasis, identifying key networks and transcription factors for potential therapeutic targets. Findings offer insights into complex molecular mechanisms driving cancer progression.

Area of Science:

  • Oncology
  • Molecular Biology
  • Bioinformatics

Background:

  • Metastasis is a critical hallmark of breast cancer, driving disease progression and mortality.
  • Understanding the complex molecular interactions underlying metastasis is crucial for developing effective treatments.

Purpose of the Study:

  • To investigate the intricate interactions among differentially expressed genes, non-coding RNAs (miRNAs, lncRNAs), and drugs associated with breast cancer metastasis.
  • To identify key regulatory networks, hub molecules, and transcription factors involved in breast cancer progression.

Main Methods:

  • Construction of gene co-expression, mRNA-miRNA-lncRNA-drug, and mRNA-miRNA-TF interaction networks.
  • Analysis of topological parameters, significant cliques, transcription factor (TF) analysis, and TCGA expression data.
  • Functional enrichment analysis of differentially expressed genes.

Main Results:

  • Identification of significant cliques and hub RNAs within the constructed networks.
  • Discovery of two significant transcription factors (EST1 and SP1) associated with breast cancer metastasis.
  • TCGA expression, subclass-based, and methylation analyses revealed insights into mRNA and non-coding RNA roles.

Conclusions:

  • The identified significant cliques may serve as targets for novel therapeutic interventions in breast cancer.
  • This research provides a deeper understanding of the molecular intricacies of breast cancer metastasis, potentially revealing new biomarkers.