Literature DB >> 16550159

Using high-throughput SNP technologies to study cancer.

L J Engle1, C L Simpson, J E Landers.   

Abstract

Identifying genes involved in the development of cancer is crucial to fully understanding cancer biology, for developing novel therapeutics for cancer treatment and for providing methods for cancer prevention and early diagnosis. The use of polymorphic markers, in particular single nucleotide polymorphisms (SNPs), promises to provide a comprehensive tool for analysing the human genome and identifying those genes and genomic regions contributing to the cancer phenotype. This review summarizes the various analytical methodologies in which SNPs are used and presents examples of how each of these methodologies have been used to locate genes and genomic regions of interest for various cancer types. Additionally many of the current SNP-analysing technologies will be reviewed with particular attention paid to the advantages and disadvantages of each and how each technology can be applied to the analysis of the genome for identifying cancer-related genes.

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Year:  2006        PMID: 16550159     DOI: 10.1038/sj.onc.1209368

Source DB:  PubMed          Journal:  Oncogene        ISSN: 0950-9232            Impact factor:   9.867


  30 in total

1.  [Molecular pathology as an necessity: its role in diagnostic and predictive pathology].

Authors:  K W Schmid
Journal:  Pathologe       Date:  2009-03       Impact factor: 1.011

2.  CanProVar: a human cancer proteome variation database.

Authors:  Jing Li; Dexter T Duncan; Bing Zhang
Journal:  Hum Mutat       Date:  2010-03       Impact factor: 4.878

Review 3.  Whole genome scanning as a cytogenetic tool in hematologic malignancies.

Authors:  Jaroslaw P Maciejewski; Ghulam J Mufti
Journal:  Blood       Date:  2008-05-27       Impact factor: 22.113

4.  The regulatory mechanism of the LY6K gene expression in human breast cancer cells.

Authors:  Hyun Kyung Kong; Sukjoon Yoon; Jong Hoon Park
Journal:  J Biol Chem       Date:  2012-09-17       Impact factor: 5.157

5.  Biomarkers of sepsis.

Authors:  John C Marshall
Journal:  Curr Infect Dis Rep       Date:  2006-09       Impact factor: 3.725

6.  Frequent genomic abnormalities in acute myeloid leukemia/myelodysplastic syndrome with normal karyotype.

Authors:  Tadayuki Akagi; Seishi Ogawa; Martin Dugas; Norihiko Kawamata; Go Yamamoto; Yasuhito Nannya; Masashi Sanada; Carl W Miller; Amanda Yung; Susanne Schnittger; Torsten Haferlach; Claudia Haferlach; H Phillip Koeffler
Journal:  Haematologica       Date:  2009-01-14       Impact factor: 9.941

7.  [Molecular pathological identification of predictive biomarkers: a new task for diagnostic pathology].

Authors:  K W Schmid
Journal:  Urologe A       Date:  2008-10       Impact factor: 0.639

Review 8.  A brief review of molecular techniques to assess plant diversity.

Authors:  Ibrahim A Arif; Mohammad A Bakir; Haseeb A Khan; Ahmad H Al Farhan; Ali A Al Homaidan; Ali H Bahkali; Mohammad Al Sadoon; Mohammad Shobrak
Journal:  Int J Mol Sci       Date:  2010-05-10       Impact factor: 5.923

Review 9.  Application of OMICS technologies in occupational and environmental health research; current status and projections.

Authors:  J Vlaanderen; L E Moore; M T Smith; Q Lan; L Zhang; C F Skibola; N Rothman; R Vermeulen
Journal:  Occup Environ Med       Date:  2009-11-20       Impact factor: 4.402

10.  Genome Alteration Print (GAP): a tool to visualize and mine complex cancer genomic profiles obtained by SNP arrays.

Authors:  Tatiana Popova; Elodie Manié; Dominique Stoppa-Lyonnet; Guillem Rigaill; Emmanuel Barillot; Marc Henri Stern
Journal:  Genome Biol       Date:  2009-11-11       Impact factor: 13.583

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