Wide-scale alterations in interchromosomal organization in breast cancer cells: defining a network of interacting chromosomes.
The interchromosomal spatial positionings of a subset of human chromosomes was examined in the human breast cell line MCF10A (10A) and its malignant counterpart MCF10CA1a (CA1a). The nine chromosomes selected (#1, 4, 11, 12, 15, 16, 18, 21 and X) cover a wide range in size and gene density and compose ∼40% of the total human genome. Radial positioning of the chromosome territories (CT) was size dependent with certain of the CT more peripheral in CA1a. Each CT was in close proximity (interaction) with a similar number of other CT except the inactive CTXi. It had lower levels of interchromosomal partners in 10A which increased strikingly in CA1a. Major alterations from 10A to CA1a were detected in the pairwise interaction profiles which were subdivided into five types of altered interaction profiles: overall increase, overall decrease, switching from 1 to ≥2, vice versa or no change. A global data mining program termed the chromatic median calculated the most probable overall association network for the entire subset of CT. This interchromosomal network was drastically altered in CA1a with only 1 of 20 shared connections. We conclude that CT undergo multiple and preferred interactions with other CT in the cell nucleus and form preferred-albeit probabilistic-interchromosomal networks. This network of interactions is highly altered in malignant human breast cells. It is intriguing to consider the relationship of these alterations to the corresponding changes in the gene expression program of these malignant cancer cells.
Department of Biological Sciences and.
Andrew J
AJ
Fritz
Department of Computer Sciences, University at Buffalo, State University of New York, Buffalo, NY 14260, USA.
Branislav
B
Stojkovic
Department of Computer Sciences, University at Buffalo, State University of New York, Buffalo, NY 14260, USA.
Hu
H
Ding
Department of Computer Sciences, University at Buffalo, State University of New York, Buffalo, NY 14260, USA.
Jinhui
J
Xu
Department of Computer Sciences, Fayetteville State University, Fayetteville, NC 28301, USA.
Sambit
S
Bhattacharya
Department of Biostatistics, University at Buffalo, State University of New York, Buffalo, NY 14214, USA.
Daniel
D
Gaile
Department of Biological Sciences and berezney@buffalo.edu.
Ronald
R
Berezney
D001943:Breast Neoplasms / Q000235:genetics*; D045744:Cell Line, Tumor; D002877:Chromosomes, Human; D019295:Computational Biology; D004261:DNA Replication; D004843:Epistasis, Genetic; D005260:Female; D015870:Gene Expression; D053263:Gene Regulatory Networks; D023281:Genomics / Q000379:methods; D006801:Humans; D017404:In Situ Hybridization, Fluorescence; D016571:Neural Networks, Computer