Emergent dynamics of underlying regulatory network links EMT and androgen receptor-dependent resistance in prostate

Rashi Jindal1,2, Abheepsa Nanda1,2, Maalavika Pillai1,2

  • 1Center for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India.

Insights

Prostate cancer develops resistance to hormone therapy through genetic and non-genetic pathways. This study models regulatory networks, revealing how androgen receptor variants and epithelial-mesenchymal transition drive resistance and suggesting new therapeutic targets.

Area of Science:

  • Oncology
  • Systems Biology
  • Computational Biology

Background:

  • Advanced prostate cancer initially responds to hormone therapies like androgen deprivation therapy (ADT) and second-generation agents (abiraterone, enzalutamide).
  • Hormone therapy resistance is a major clinical challenge, arising from diverse genetic and non-genetic mechanisms, including lineage plasticity.
  • Understanding the regulatory networks governing androgen independence and phenotypic plasticity is crucial for developing effective treatments.

Purpose of the Study:

  • To investigate the dynamics of a regulatory network linking androgen receptor (AR) splice variants and epithelial-mesenchymal transition (EMT).
  • To explore how these networks contribute to phenotypic heterogeneity and plasticity in hormone therapy resistance.
  • To identify potential therapeutic strategies by understanding the systems-level drivers of cancer progression.

Main Methods:

  • Developed a computational model simulating a regulatory network of AR variants and EMT.
  • Analyzed model simulations to predict cancer phenotypes under different regulatory conditions.
  • Validated model predictions using transcriptomic datasets (single-cell and bulk) and in vitro/clinical samples.
  • Incorporated the immune checkpoint molecule PD-L1 into the network model.

Main Results:

  • Model simulations identified four key phenotypes: epithelial-sensitive (ES), epithelial-resistant (ER), mesenchymal-resistant (MR), and mesenchymal-sensitive (MS).
  • Observed that coordinated antagonistic regulator activity enables these phenotypes.
  • Demonstrated spontaneous stochastic switching between ES and MR states.
  • Confirmed interactions between AR, PD-L1, and SNAIL, a mesenchymal marker, through simulations and experiments.

Conclusions:

  • The study provides a systems-level understanding of androgen independence and EMT in prostate cancer.
  • Identified non-genetic transitions and plasticity as key drivers of hormone therapy resistance.
  • Findings may aid in developing novel therapeutic strategies targeting these regulatory networks.

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