Network-based approaches for anticancer therapy (Review)

Hyunjeong Seo1, Wanyeon Kim, Jihyung Lee

  • 1Department of Biological Sciences, College of Natural Sciences, Pusan National University, Busan 609-735, Republic of Korea.

Insights

Cancer cells develop resistance to therapies by altering signaling networks. Targeting key molecular hubs within these networks offers a promising strategy to improve cancer treatment efficacy and reduce side effects.

Area of Science:

  • Systems Biology
  • Cancer Biology
  • Network Medicine

Background:

  • Cancer involves complex alterations in multiple signaling networks, often exhibiting scale-free properties with critical 'hub' molecules.
  • Hubs are vital network components and potential biomarkers; targeting them could enhance cancer treatment effectiveness.
  • Current therapies like chemotherapy and radiotherapy can paradoxically induce cancer cell resistance by activating alternative pathways.

Purpose of the Study:

  • To review current research on cancer-associated complex networks.
  • To examine how these networks modulate in response to cancer therapy.
  • To explore network-based therapeutic strategies for improving cancer treatment outcomes.

Main Methods:

  • Review of existing literature on cancer signaling networks and therapeutic responses.
  • Analysis of network properties, including scale-free characteristics and hub identification.
  • Discussion of network modulation mechanisms and their role in chemoresistance and radioresistance.

Main Results:

  • Cancer networks are dynamic and can rewire in response to therapy, leading to resistance.
  • Hub molecules play a crucial role in network flexibility and therapy-induced adaptations.
  • Identifying key molecules controlling network modulation is essential for overcoming treatment failure.

Conclusions:

  • Network-based therapies targeting network flexibility and hub molecules show promise for improving cancer treatment.
  • Understanding and manipulating cancer network dynamics can minimize side effects and enhance therapeutic efficacy.
  • Further research into network modulation is critical for developing more effective cancer treatments.

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