Cancer-related networks: A help to understand, predict and change malignant transformation

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Cancer is increasingly described as a systems-level, network phenomenon. Genetic methods, such as next generation sequencing and RNA interference uncovered the complexity tumor-specific mutation-induced effects and the identification of multiple target sets. Network analysis of cancer-specific metabolic and signaling pathways highlighted the structural features of cancer-related proteins and their complexes to develop next-generation protein kinase inhibitors, as well as the modulation of inflammatory and autophagic pathways in anti-cancer therapies. Importantly, malignant transformation can be described as a two-phase process, where an initial increase of system plasticity is followed by a decrease of plasticity at late stages of tumor development. Late-stage tumors should be attacked by an indirect network influence strategy. On the contrary, the attack of early-stage tumors may target central network nodes. Cancer stem cells need special diagnosis and targeting, since they potentially have an extremely high ability to change the rigidity/plasticity of their networks. The early warning signals of the activation of fast growing tumor cell clones are important in personalized diagnosis and therapy. Multi-target attacks are needed to perturb cancer-specific networks to exit from cancer attractors and re-enter a normal attractor. However, the dynamic non-genetic heterogeneity of cancer cell population induces the replenishment of the cancer attractor with surviving, non-responsive cells from neighboring abnormal attractors. The development of drug resistance is further complicated by interactions of tumor clones and their microenvironment. Network analysis of intercellular cooperation using game theory approaches may open new areas of understanding tumor complexity. In conclusion, the above applications of the network approach open up new, and highly promising avenues in anti-cancer drug design.

Original languageEnglish
Pages (from-to)209-212
Number of pages4
JournalSeminars in Cancer Biology
Volume23
Issue number4
DOIs
Publication statusPublished - Aug 2013

Fingerprint

Neoplasms
Clone Cells
Game Theory
Neoplastic Stem Cells
Drug Design
Protein Kinase Inhibitors
RNA Interference
Metabolic Networks and Pathways
Drug Resistance
Mutation
Therapeutics
Population
Proteins

Keywords

  • Anti-cancer therapies
  • Autophagy
  • Cancer attractors
  • Cancer stem cells
  • Game theory
  • Inflammation
  • Interactome
  • Metabolic modeling
  • Networks
  • Protein kinase inhibitors
  • Signaling.

ASJC Scopus subject areas

  • Cancer Research

Cite this

Cancer-related networks : A help to understand, predict and change malignant transformation. / Csermely, P.; Korcsmáros, T.

In: Seminars in Cancer Biology, Vol. 23, No. 4, 08.2013, p. 209-212.

Research output: Contribution to journalArticle

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