Literature DB >> 18684067

From oncogene to network addiction: the new frontier of cancer genomics and therapeutics.

Giovanni Tonon1.   

Abstract

Recent advances in genomic analysis have provided a comprehensive view of the genetic and epigenetic changes present in cancer cells. While therapies targeting genes causally linked to carcinogenesis have been successful in a subset of tumor types, the hope for treatments tailored on patient genomic profiles seems, for most cancers, still elusive. Cancer genes belong to two clearly defined groups. The first subset of genes is frequently mutated across samples and tumor types, and includes well-studied oncogenes and tumor suppressor genes, such as members of the RAS, AKT and TP53 families, whose direct targeting has so far been largely disappointing. In the other group, the vast majority of putative cancer genes emerging from sequencing and genomic studies show a low incidence (5% or less). The possibility of finding novel selective drugs against such a high number of gene products seems daunting. However, recent genomic and proteomic findings, as well as novel frameworks arising from systems biology approaches, suggest that this apparent discordance may converge towards a more satisfying model. It seems that genetic lesions in cancer tend to cluster around certain pathways, suggesting that the concept of 'network addiction', rather than 'oncogene addiction', would recapitulate more closely what is happening during tumor development and after exposure to therapeutic agents. This new perspective, arising from genomic and systems biology studies, will likely provide a valuable frame for the design of the cancer drugs of the future.

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Year:  2008        PMID: 18684067     DOI: 10.2217/14796694.4.4.569

Source DB:  PubMed          Journal:  Future Oncol        ISSN: 1479-6694            Impact factor:   3.404


  8 in total

1.  Radiofrequency field-induced thermal cytotoxicity in cancer cells treated with fluorescent nanoparticles.

Authors:  Evan S Glazer; Steven A Curley
Journal:  Cancer       Date:  2010-07-01       Impact factor: 6.860

2.  NID2 and HOXA9 promoter hypermethylation as biomarkers for prevention and early detection in oral cavity squamous cell carcinoma tissues and saliva.

Authors:  R Guerrero-Preston; E Soudry; J Acero; M Orera; L Moreno-López; G Macía-Colón; A Jaffe; M Berdasco; C Ili-Gangas; P Brebi-Mieville; Y Fu; C Engstrom; R A Irizarry; M Esteller; W Westra; W Koch; J Califano; D Sidransky
Journal:  Cancer Prev Res (Phila)       Date:  2011-05-10

3.  XPD DNA nucleotide excision repair gene polymorphisms associated with DNA repair deficiency predict better treatment outcomes in secondary acute myeloid leukemia.

Authors:  Nataliya Kuptsova-Clarkson; Christine B Ambrosone; Joli Weiss; Maria R Baer; Lara E Sucheston; Gary Zirpoli; Kenneth J Kopecky; Laurie Ford; Javier Blanco; Meir Wetzler; Kirsten B Moysich
Journal:  Int J Mol Epidemiol Genet       Date:  2010-08-10

Review 4.  Platelet-derived growth factor receptor alpha in glioma: a bad seed.

Authors:  Kun-Wei Liu; Bo Hu; Shi-Yuan Cheng
Journal:  Chin J Cancer       Date:  2011-09

Review 5.  Oncogene addiction in gliomas: implications for molecular targeted therapy.

Authors:  Wei Yan; Wei Zhang; Tao Jiang
Journal:  J Exp Clin Cancer Res       Date:  2011-05-17

6.  Mechanistic-enriched models: integrating transcription factor networks and metabolic deregulation in cancer.

Authors:  Enrique Hernández-Lemus; J Mario Siqueiros-García
Journal:  Theor Biol Med Model       Date:  2015-09-09       Impact factor: 2.432

Review 7.  A new hope in immunotherapy for malignant gliomas: adoptive T cell transfer therapy.

Authors:  Dong-Sup Chung; Hye-Jin Shin; Yong-Kil Hong
Journal:  J Immunol Res       Date:  2014-06-09       Impact factor: 4.818

8.  The role of master regulators in the metabolic/transcriptional coupling in breast carcinomas.

Authors:  Karol Baca-López; Miguel Mayorga; Alfredo Hidalgo-Miranda; Nora Gutiérrez-Nájera; Enrique Hernández-Lemus
Journal:  PLoS One       Date:  2012-08-27       Impact factor: 3.240

  8 in total

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