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Updated: Jul 16, 2025

Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material
Published on: August 1, 2018
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.
Abstract:
Metastasis is a major breast cancer hallmark due to which tumor cells tend to relocate to regional or distant organs from their organ of origin. This study is aimed to decipher the interaction among 113 differentially expressed genes, interacting non-coding RNAs and drugs (614 miRNAs, 220 lncRNAs and 3241 interacting drugs) associated with metastasis in breast cancer. For an extensive understanding of genetic interactions in the diseased state, a backbone gene co-expression network was constructed. Further, the mRNA-miRNA-lncRNA-drug interaction network was constructed to identify the top hub RNAs, significant cliques and topological parameters associated with differentially expressed genes. Then, the mRNAs from the top two subnetworks constructed are considered for transcription factor (TF) analysis. 39 interacting miRNAs and 1641 corresponding TFs for the eight mRNAs from the subnetworks are also utilized to construct an mRNA-miRNA-TF interaction network. TF analysis revealed two TFs (EST1 and SP1) from the cliques to be significant. TCGA expression analysis of miRNAs and lncRNAs as well as subclass-based and promoter methylation-based expression, oncoprint and survival analysis of the mRNAs are also done. Finally, functional enrichment of mRNAs is also performed. Significant cliques identified in the study can be utilized for identification of newer therapeutic interventions for breast cancer. This work will also help to gain a deeper insight into the complicated molecular intricacies to reveal the potential biomarkers involved with breast cancer progression in future.
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.
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lncRNA - Long Non-coding RNAs
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