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

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.