Modulation of Network Plasticity Opens Novel Therapeutic Possibilities in Cancer, Diabetes, and Neurodegeneration

Márk Kerestély1, István Narozsny1, Levente Szarka1

  • 1Department of Molecular Biology, Semmelweis University, Budapest, Hungary.

Insights

Cellular plasticity networks offer new therapeutic strategies for cancer and neurodegenerative diseases. Network analysis reveals targets for drug development and regenerative medicine, improving patient outcomes.

Area of Science:

  • Biochemistry
  • Systems Biology
  • Oncology

Background:

  • Cellular plasticity is vital for cancer progression and regenerative medicine in diseases like diabetes, Alzheimer's, and Parkinson's.
  • Network analysis of protein-protein interactions, signaling, and gene regulation describes cellular adaptation in disease.
  • Understanding these networks is key to developing novel therapeutic interventions.

Purpose of the Study:

  • To review how network analysis of cellular plasticity can inform novel therapeutic strategies.
  • To highlight plasticity-related drug targets and regenerative therapies.
  • To identify research gaps and future directions in network-based plasticity research.

Main Methods:

  • Literature review focusing on network analysis of cellular plasticity.
  • Identification and categorization of plasticity-related cancer drug targets.
  • Description of network plasticity-designed therapies for cancer and regenerative medicine.

Main Results:

  • Network analysis provides novel therapeutic options for cancer progression, metastasis, cancer stem cells, and drug resistance.
  • 55 plasticity-related cancer drug targets were identified, with 20 approved drugs and 9 investigational drugs.
  • Network-driven regenerative therapies for pancreatic beta cells and neurons show recent expansion.

Conclusions:

  • Network analysis of cellular plasticity is a promising approach for developing innovative therapies.
  • Further research into plasticity-related signaling pathways, drug resensitization, and computational modeling is warranted.
  • Identifying biomarkers and optimizing sequential therapies through network-based approaches will advance clinical applications.

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