Show simple item record Csermely, Péter Korcsmáros, Tamás 2016-06-30T12:41:06Z 2016-06-30T12:41:06Z 2013
dc.identifier 84881109934
dc.identifier.citation pagination=209-212; journalVolume=23; journalIssueNumber=4; journalTitle=SEMINARS IN CANCER BIOLOGY;
dc.identifier.uri doi:10.1016/j.semcancer.2013.06.011
dc.description.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. © 2013 Elsevier Ltd.
dc.relation.ispartof urn:issn:1044-579X
dc.title Cancer-related networks: A help to understand, predict and change malignant transformation
dc.type Journal Article 2015-11-20T10:21:01Z
dc.language.rfc3066 en
dc.identifier.mtmt 2378502
dc.identifier.wos 000323455900001

Files in this item



This item appears in the following Collection(s)

Show simple item record

Search DSpace

Advanced Search


My Account