Literature DB >> 19446742

Genes that contribute to cancer fusion genes are large and evolutionarily conserved.

Swetha Narsing1, Zhihong Jelsovsky, Alfred Mbah, George Blanck.   

Abstract

Numerous cancer fusion genes have been identified and studied, and in some cases, therapy or diagnostic techniques have been designed that are specific to the fusion protein encoded by the fusion gene. There has been little progress, however, in understanding the general features of cancer fusion genes in a way that could provide the foundation for an algorithm for predicting the occurrence of a fusion gene once the chromosomal translocation points have been identified by karyotype analyses. In this study, we used publicly available data sets to characterize 59 cancer fusion genes. The results indicate that all but 17% of the genes involved in fusion events are either relatively large, compared to neighboring genes, or are highly conserved in evolution. These results support a basis for designing algorithms that could have a high degree of predictive value in identifying fusion genes once conventional microscopic analyses have identified the chromosomal breakpoints.

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Year:  2009        PMID: 19446742     DOI: 10.1016/j.cancergencyto.2009.02.004

Source DB:  PubMed          Journal:  Cancer Genet Cytogenet        ISSN: 0165-4608


  4 in total

1.  De novo, systemic, deleterious amino acid substitutions are common in large cytoskeleton-related protein coding regions.

Authors:  Rebecca J Stoll; Grace R Thompson; Mohammad D Samy; George Blanck
Journal:  Biomed Rep       Date:  2016-12-08

2.  Flat cells come full sphere: Are mutant cytoskeletal-related proteins oncoprotein-monsters or useful immunogens?

Authors:  Michele L Parry; George Blanck
Journal:  Hum Vaccin Immunother       Date:  2015-07-30       Impact factor: 3.452

3.  Module-based breast cancer classification.

Authors:  Yuji Zhang; Jianhua Xuan; Robert Clarke; Habtom W Ressom
Journal:  Int J Data Min Bioinform       Date:  2013       Impact factor: 0.667

4.  Identification of Sets of Cytoskeletal Related and Adhesion-related Coding Region Mutations in the TCGA Melanoma Dataset that Correlate with a Negative Outcome.

Authors:  John M Yavorski; Rebecca J Stoll; Mohammad D Samy; James A Mauro; George Blanck
Journal:  Curr Genomics       Date:  2017-06       Impact factor: 2.236

  4 in total

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