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    Interchromosomal Translocations as a Means to Map Chromosome Territories in Breast Cancer

    Parl, Fritz F.
    Dupont, William D.
    Crooke, Philip S.
    : https://ir.vanderbilt.edu/xmlui/handle/1803/9896
    : 2019-04-16

    Abstract

    The genome-wide identification of mutated genes is an important advance in our understanding of tumor biology, but several fundamental questions remain open. How do these genes act together to promote cancer development and, a related question, how are they spatially arranged in the nucleus to allow coordinated expression? We examined the nuclear topography of mutated genes in breast cancer and their relation to chromosome territories (CTs). We performed a literature review and analyzed 1 type of mutation, interchromosomal translocations, in 1546 primary breast cancers to infer the spatial arrangement of chromosomes. The cosegregation of all observed fusion genes was used to create a matrix of genome-wide CT contacts and develop a tentative CT map of breast cancer. Regression analysis was performed to determine the association between CTs and all types of mutations. Chromosomes 17, 11, 8, and 1 had the majority of interchromosomal fusions and are presumably clustered in the nuclear center, whereas chromosomes 22, 21. X. and 18 had the lowest number of contacts, likely reflecting a more peripheral position. Regression analysis revealed that there was no significant association between chromosome length indicated by the number of base pairs per chromosome and the number of total (inter- and intrachromosomal) translocations. point mutations, or copy number aberrations (CNAs). The gene density of chromosomes (genes/Mb) was significantly correlated with total translocations (P= .02), but not with point mutations P= .19 and CNAs P= .62. Finally, the association of the 3 genetic alterations with the CT map deduced from the interchromosomal fusions was significant, ie. total translocations P=7 x 10(-11), point mutations P= .01, CNAs P=.002. In conclusion, we developed a tentative CT map and observed a spatial association with genetic alterations in breast cancer.
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