Related Experiment Video
Updated: Jan 12, 2026
07:41
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
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Exploring Breast Cancer-Associated Genes: A Comprehensive Analysis and Competitive Endogenous RNA Network
H Charu Meena1, R Sagaya Jansi1, S Aishwarya1
1Department of Bioinformatics, Stella Maris College, Chennai, Tamil Nadu, India.
Archives of Razi Institute
|November 3, 2025
Summary
This study identified 613 differentially expressed genes in breast cancer, including key long non-coding RNAs like LINC00461 and MALAT1, offering potential new therapeutic biomarkers for this common cancer.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Breast cancer is a prevalent malignancy primarily affecting women, with complex etiology involving genetic and environmental factors.
- Non-coding RNAs play a crucial role in the development and progression of various cancers, including breast cancer.
Purpose of the Study:
- To identify differentially expressed genes in breast cancer using RNA-Seq data.
- To explore gene expression patterns and construct competing endogenous RNA (ceRNA) networks.
- To discover potential therapeutic biomarkers for breast cancer.
Main Methods:
- RNA-Seq data analysis from The Cancer Genome Atlas (TCGA) for breast cancer.
- Utilized R programming and the "TCGA Biolinks" package for expression and survival analyses.
- Constructed ceRNA networks to investigate regulatory relationships between RNAs.
Main Results:
- Identified 613 differentially expressed genes (254 upregulated, 359 downregulated) in breast cancer samples.
- Found aberrantly expressed long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs).
- Highlighted LINC00461 and MALAT1 as highly expressed lncRNAs with potential as therapeutic biomarkers.
Conclusions:
- The study successfully identified key differentially expressed genes and constructed ceRNA networks in breast cancer.
- Aberrantly expressed lncRNAs, particularly LINC00461 and MALAT1, show promise as diagnostic and therapeutic targets.
- Findings contribute to understanding breast cancer molecular mechanisms and identifying novel biomarkers.
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