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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
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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.

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Summary
This summary is machine-generated.

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.

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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.