Literature DB >> 19010930

Genome-wide functional synergy between amplified and mutated genes in human breast cancer.

Yuri Nikolsky1, Evgeny Sviridov, Jun Yao, Damir Dosymbekov, Vadim Ustyansky, Valery Kaznacheev, Zoltan Dezso, Laura Mulvey, Laura E Macconaill, Wendy Winckler, Tatiana Serebryiskaya, Tatiana Nikolskaya, Kornelia Polyak.   

Abstract

A single cancer cell contains large numbers of genetic alterations that in combination create the malignant phenotype. However, whether amplified and mutated genes form functional and physical interaction networks that could explain the selection for cells with combined alterations is unknown. To investigate this issue, we characterized copy number alterations in 191 breast tumors using dense single nucleotide polymorphism arrays and identified 1,747 genes with copy number gain organized into 30 amplicons. Amplicons were distributed unequally throughout the genome. Each amplicon had distinct enrichment pattern in pathways, networks, and molecular functions, but genes within individual amplicons did not form coherent functional units. Genes in amplicons included all major tumorigenic pathways and were highly enriched in breast cancer-causative genes. In contrast, 1,188 genes with somatic mutations in breast cancer were distributed randomly over the genome, did not represent a functionally cohesive gene set, and were relatively less enriched in breast cancer marker genes. Mutated and gained genes did not show statistically significant overlap but were highly synergistic in populating key tumorigenic pathways including transforming growth factor beta, WNT, fibroblast growth factor, and PIP3 signaling. In general, mutated genes were more frequently upstream of gained genes in transcription regulation signaling than vice versa, suggesting that mutated genes are mainly regulators, whereas gained genes are mostly regulated. ESR1 was the major transcription factor regulating amplified but not mutated genes. Our results support the hypothesis that multiple genetic events, including copy number gains and somatic mutations, are necessary for establishing the malignant cell phenotype.

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Year:  2008        PMID: 19010930     DOI: 10.1158/0008-5472.CAN-08-3082

Source DB:  PubMed          Journal:  Cancer Res        ISSN: 0008-5472            Impact factor:   12.701


  54 in total

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2.  AP-2γ regulates oestrogen receptor-mediated long-range chromatin interaction and gene transcription.

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3.  Interactions between the tumor and the blood systemic response of breast cancer patients.

Authors:  Vanessa Dumeaux; Bjørn Fjukstad; Hans E Fjosne; Jan-Ole Frantzen; Marit Muri Holmen; Enno Rodegerdts; Ellen Schlichting; Anne-Lise Børresen-Dale; Lars Ailo Bongo; Eiliv Lund; Michael Hallett
Journal:  PLoS Comput Biol       Date:  2017-09-28       Impact factor: 4.475

4.  NRMT2 is an N-terminal monomethylase that primes for its homologue NRMT1.

Authors:  Janusz J Petkowski; Lindsay A Bonsignore; John G Tooley; Daniel W Wilkey; Michael L Merchant; Ian G Macara; Christine E Schaner Tooley
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5.  JARID1B is a luminal lineage-driving oncogene in breast cancer.

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Journal:  Cancer Cell       Date:  2014-06-16       Impact factor: 31.743

6.  Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity.

Authors:  Vanessa Almendro; Yu-Kang Cheng; Amanda Randles; Shalev Itzkovitz; Andriy Marusyk; Elisabet Ametller; Xavier Gonzalez-Farre; Montse Muñoz; Hege G Russnes; Aslaug Helland; Inga H Rye; Anne-Lise Borresen-Dale; Reo Maruyama; Alexander van Oudenaarden; Mitchell Dowsett; Robin L Jones; Jorge Reis-Filho; Pere Gascon; Mithat Gönen; Franziska Michor; Kornelia Polyak
Journal:  Cell Rep       Date:  2014-01-23       Impact factor: 9.423

7.  Integrated network analysis of transcriptomic and proteomic data in psoriasis.

Authors:  Eleonora Piruzian; Sergey Bruskin; Alex Ishkin; Rustam Abdeev; Sergey Moshkovskii; Stanislav Melnik; Yuri Nikolsky; Tatiana Nikolskaya
Journal:  BMC Syst Biol       Date:  2010-04-08

8.  Functional analysis of multiple genomic signatures demonstrates that classification algorithms choose phenotype-related genes.

Authors:  W Shi; M Bessarabova; D Dosymbekov; Z Dezso; T Nikolskaya; M Dudoladova; T Serebryiskaya; A Bugrim; A Guryanov; R J Brennan; R Shah; J Dopazo; M Chen; Y Deng; T Shi; G Jurman; C Furlanello; R S Thomas; J C Corton; W Tong; L Shi; Y Nikolsky
Journal:  Pharmacogenomics J       Date:  2010-08       Impact factor: 3.550

9.  PTK6 regulates IGF-1-induced anchorage-independent survival.

Authors:  Hanna Y Irie; Yashaswi Shrestha; Laura M Selfors; Fabianne Frye; Naoko Iida; Zhigang Wang; Lihua Zou; Jun Yao; Yiling Lu; Charles B Epstein; Sridaran Natesan; Andrea L Richardson; Kornelia Polyak; Gordon B Mills; William C Hahn; Joan S Brugge
Journal:  PLoS One       Date:  2010-07-23       Impact factor: 3.240

Review 10.  Key signalling nodes in mammary gland development and cancer: Myc.

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Journal:  Breast Cancer Res       Date:  2009       Impact factor: 6.466

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