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Updated: Jun 6, 2025
10:36
Systems Biology of Metabolic Regulation by Estrogen Receptor Signaling in Breast Cancer
Published on: March 17, 2016
10.4K
Unveiling epigenetic regulatory elements associated with breast cancer development.
Marta Jardanowska-Kotuniak1,2, Michał Dramiński1, Michał Własnowolski3
1Computational Biology Group, Institute of Computer Science of the Polish Academy of Sciences, Warsaw, Poland.
Biorxiv : the Preprint Server for Biology
|November 28, 2024
Summary
This study reveals key epigenetic changes in breast cancer, identifying potential biomarkers and therapeutic targets by analyzing gene expression and DNA methylation. Findings highlight regulatory dependencies and altered chromatin structure in cancer cells.
Area of Science:
- Genomics and Epigenetics
- Cancer Biology
- Bioinformatics
Background:
- Breast cancer is a leading global health concern, with over 2 million women affected annually.
- While extensively studied, the epigenetic landscape of breast cancer remains incompletely understood.
- Epigenetic alterations play a crucial role in cancer development and progression.
Purpose of the Study:
- To identify epigenetic mechanisms influencing breast cancer-related gene expression.
- To discover novel biomarkers and therapeutic targets for breast cancer.
- To elucidate the role of DNA methylation and microRNA in breast cancer pathogenesis.
Main Methods:
- Utilized The Cancer Genome Atlas (TCGA) database with over 800 samples.
- Integrated multi-omics data including mRNA, microRNA (miRNA), and DNA methylation.
- Applied Monte Carlo Feature Selection and Interdependency Discovery to identify 2701 significant features.
- Confirmed biological impact using statistical analysis, NLP, machine learning, transcription factor analysis, drug interaction, and 3D chromatin structure analysis.
Main Results:
- Achieved high classification accuracy (0.91-0.98) for distinguishing cancer from control samples using selected features.
- Observed generally lower gene expression and increased DNA methylation (β-values) in cancer samples.
- Identified correlations between mRNA expression, miRNA levels, and DNA methylation patterns.
- Detected potential disruption of transcription factor binding (NRF1, MXI1) affecting gene expression (NKAPL, PITX1).
- 3D chromatin models indicated looser chromatin packing in cancer cells.
Conclusions:
- Successfully identified numerous potential regulatory dependencies in breast cancer epigenetics.
- Highlighted specific epigenetic alterations impacting gene expression and transcription factor activity.
- Provided insights into the structural changes of chromatin in breast cancer.
- Established a foundation for developing novel epigenetic biomarkers and therapeutic strategies for breast cancer.
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