Parl Fritz F, Dupont William D, Crooke Philip S
Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA.
Department of Biostatistics, Vanderbilt University, Nashville, TN, USA.
Cancer Inform. 2019 Apr 16;18:1176935119842573. doi: 10.1177/1176935119842573. eCollection 2019.
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 ( = .02), but not with point mutations = .19 and CNAs = .62. Finally, the association of the 3 genetic alterations with the CT map deduced from the interchromosomal fusions was significant, ie, total translocations = 7 × 10, point mutations = .01, CNAs = .002. In conclusion, we developed a tentative CT map and observed a spatial association with genetic alterations in breast cancer.
全基因组范围内突变基因的鉴定是我们对肿瘤生物学理解的一项重要进展，但仍有几个基本问题悬而未决。这些基因如何共同作用促进癌症发展，以及一个相关问题，它们在细胞核中是如何进行空间排列以实现协同表达的？我们研究了乳腺癌中突变基因的核拓扑结构及其与染色体领地（CTs）的关系。我们进行了文献综述，并分析了1546例原发性乳腺癌中的1种突变类型——染色体间易位，以推断染色体的空间排列。利用所有观察到的融合基因的共分离来创建全基因组CT接触矩阵，并绘制出乳腺癌的初步CT图谱。进行回归分析以确定CTs与所有类型突变之间的关联。17号、11号、8号和1号染色体具有大多数染色体间融合，可能聚集在核中心，而22号、21号、X号和18号染色体的接触数最少，这可能反映了它们处于更外围的位置。回归分析显示，每条染色体的碱基对数量所表示的染色体长度与总（染色体间和染色体内）易位、点突变或拷贝数变异（CNA）的数量之间没有显著关联。染色体的基因密度（基因/Mb）与总易位显著相关（=0.02），但与点突变（=0.19）和CNA（=0.62）无关。最后，这三种基因改变与从染色体间融合推导的CT图谱之间的关联是显著的，即总易位=7×10，点突变=0.01，CNA=0.002。总之，我们绘制了初步的CT图谱，并观察到其与乳腺癌基因改变的空间关联。
