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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
An integrative ENCODE resource for cancer genomics
Jing Zhang1,2, Donghoon Lee1,2, Vineet Dhiman3,4
1Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT, 06520, USA.
This study creates a custom genome annotation using advanced functional genomics data. It reveals regulatory networks and protein interactions crucial for understanding cancer development and identifying therapeutic targets.
Area of Science:
- Genomics
- Cancer Biology
- Systems Biology
Background:
- The Encyclopedia of DNA Elements (ENCODE) provides extensive functional genomics data for universal genome interpretation.
- Customized annotations are beneficial for specific research applications, enhancing genome analysis.
- Understanding complex diseases like cancer requires detailed regulatory network information.
Purpose of the Study:
- To develop a custom genome annotation using advanced functional genomics assays (eCLIP, Hi-C, STARR-seq) in ENCODE cell types.
- To build comprehensive, experimentally derived networks of transcription factors (TFs) and RNA-binding proteins (RBPs).
- To apply this network-based annotation to cancer research, focusing on regulatory hierarchies and network rewiring during oncogenesis.
Main Methods:
- Leveraging eCLIP, Hi-C, and whole-genome STARR-seq assays on ENCODE cell types.
- Constructing experimentally derived networks of TFs and RBPs, including TF-RBP crosstalk.
- Analyzing regulatory network changes during oncogenesis in cancer-associated cell types.
- Developing a workflow for prioritizing key genomic elements, variants, and regulators.
Main Results:
- A custom genome annotation with comprehensive TF and RBP networks was developed.
- SUB1, a novel RBP, was identified to drive aberrant tumor expression and amplify MYC oncogenic activity.
- Oncogenic transformations were mapped to a stem-like state in cell space, with opposing trends for oncogene knockdowns.
- Prioritization workflow successfully identified key elements and variants for cancer research applications.
Conclusions:
- The custom annotation and network resource provide valuable insights into cancer biology and oncogenesis.
- Identification of novel regulators like SUB1 offers potential therapeutic avenues.
- The developed workflow aids in prioritizing targets for further investigation in cancer genomics and therapeutics.
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