Linksets of tumor chromosome breakpoints related to survival in ovarian adenocarcinoma.

Biological processes are often accompanied by occurrences of multiple events, such as activation of certain cell types, change in prevalence of cell subpopulations (such as T cells), changes in concentration of proteins or peptides, or breaks in chromosomes. Some co-occurrences of these events are by chance, but others may have meaningful relations to the underlying biological process. The methodology of linksets is designed to detect the presence of potentially meaningful co-occurrences. Due to the complex ways in which linksets can determine the observed occurrences of multiple events, some moderately powerful computational methods are necessary for statistical estimation. Here, linkset models are fitted to data on chromosome breakpoints in ovarian adenocarcinomas, in order to answer the question motivating the project that collected them--whether there are nonrandom co-occurrences of breakpoints in particular chromosome regions, and whether these might be of prognostic significance. The results identify breakpoints in 1p1 as associated with early mortality when they occur in linksets of breakpoints in 1p3 and any one of 11q1, 11q2, or 6q2. Conversely, breakpoints in 6p2, 1q3, and 7p1 occur in linksets associated with late mortality. This is, to our knowledge, the first demonstration of a new method for analyzing patterns of event occurrence in biological data.