PCB: A pseudotemporal causality-based Bayesian approach to identify EMT-associated regulatory relationships of AS events and RBPs during breast cancer progression

PLoS Comput Biol. 2023 Mar 17;19(3):e1010939. doi: 10.1371/journal.pcbi.1010939. eCollection 2023 Mar.

Abstract

During breast cancer metastasis, the developmental process epithelial-mesenchymal (EM) transition is abnormally activated. Transcriptional regulatory networks controlling EM transition are well-studied; however, alternative RNA splicing also plays a critical regulatory role during this process. Alternative splicing was proved to control the EM transition process, and RNA-binding proteins were determined to regulate alternative splicing. A comprehensive understanding of alternative splicing and the RNA-binding proteins that regulate it during EM transition and their dynamic impact on breast cancer remains largely unknown. To accurately study the dynamic regulatory relationships, time-series data of the EM transition process are essential. However, only cross-sectional data of epithelial and mesenchymal specimens are available. Therefore, we developed a pseudotemporal causality-based Bayesian (PCB) approach to infer the dynamic regulatory relationships between alternative splicing events and RNA-binding proteins. Our study sheds light on facilitating the regulatory network-based approach to identify key RNA-binding proteins or target alternative splicing events for the diagnosis or treatment of cancers. The data and code for PCB are available at: http://hkumath.hku.hk/~wkc/PCB(data+code).zip.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alternative Splicing / genetics
  • Bayes Theorem
  • Breast Neoplasms* / metabolism
  • Cell Line, Tumor
  • Cross-Sectional Studies
  • Epithelial-Mesenchymal Transition / genetics
  • Female
  • Humans
  • Neoplastic Processes
  • RNA-Binding Proteins / genetics
  • RNA-Binding Proteins / metabolism

Substances

  • RNA-Binding Proteins

Grants and funding

YQ was supported by grants from the National Natural Science Foundation of China [grant number 62002234] the Guangdong Basic and Applied Basic Research Foundation [grant number 2019A1515111180]. WC was supported by grants from the HKRGC GRF [grant number 17301519]. PZ was supported by grants from the Fundamental Research Funds for Central Public Welfare Research Institutes of China [grant number N2120003], Special Projects of the Central Government in Guidance of Local Science and Technology Development [grant number 2022JH6/100100025]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.