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Subpathway-LNCE: Identify dysfunctional subpathways competitively regulated by lncRNAs through integrating

Xinrui Shi1, Yanjun Xu1, Chunlong Zhang1

  • 1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.

Oncotarget
|September 17, 2016
PubMed

Insights

This study introduces Subpathway-LNCE, a novel method to identify long noncoding RNAs (lncRNAs) that regulate disease pathways. This tool helps uncover the roles of lncRNAs in diseases like cancer.

Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • Long noncoding RNAs (lncRNAs) are increasingly recognized as crucial regulators in various diseases, including cancer.
  • lncRNAs can modulate messenger RNA (mRNA) stability and translation by competitively binding to microRNAs (miRNAs).
  • Understanding lncRNA-mediated regulatory networks is vital for deciphering disease mechanisms and identifying therapeutic targets.

Purpose of the Study:

  • To develop and validate an effective computational method, Subpathway-LNCE, for identifying lncRNA-competitively regulated subpathways.
  • To elucidate the functional roles of lncRNAs in disease pathogenesis through pathway analysis.
  • To provide a tool for uncovering disease-associated lncRNAs and their regulatory functions.

Main Methods:

  • Integration of lncRNA-mRNA expression profiles with pathway topology data.
  • Development of the Subpathway-LNCE algorithm to identify dysregulated subpathways driven by lncRNA-miRNA-mRNA interactions.
  • Application and validation of the method using datasets from prostate cancer, lung adenocarcinoma (LUAD), and kidney renal clear cell carcinoma.

Main Results:

  • Subpathway-LNCE successfully identified disease-associated dysfunctional subpathways regulated by lncRNAs in various cancer types.
  • The method demonstrated effectiveness in pinpointing key lncRNAs involved in kidney renal clear cell carcinoma.
  • The Subpathway-LNCE method was confirmed to be reproducible and robust across different datasets.

Conclusions:

  • Subpathway-LNCE offers a flexible and powerful approach to identify lncRNA-regulated signal subpathways in specific disease contexts.
  • The tool aids in understanding the functional significance of lncRNAs in disease progression and provides insights into potential therapeutic strategies.
  • An R package for Subpathway-LNCE is publicly available, facilitating broader research applications.
Keywords:
cancercompetitive regulationlncRNAmRNApathway identification

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