Detecting Breakage Fusion Bridge cycles in tumor genomes -- an algorithmic approach

TL;DR

This paper introduces efficient algorithms to detect Breakage-Fusion-Bridge cycles in tumor genomes from sequencing data, aiding the interpretation of complex structural variations linked to cancer.

Contribution

It presents the first linear-time algorithm for the BFB count vector problem and combines it with fold-back inversion analysis to improve BFB detection in cancer genomes.

Findings

Validated algorithms on pancreatic tumor data

Confirmed previous BFB findings in tumors

Identified new BFB-rearranged chromosomal region

Abstract

Breakage-Fusion-Bridge (BFB) is a mechanism of genomic instability characterized by the joining and subsequent tearing apart of sister chromatids. When this process is repeated during multiple rounds of cell division, it leads to patterns of copy number increases of chromosomal segments as well as fold-back inversions where duplicated segments are arranged head-to-head. These structural variations can then drive tumorigenesis. BFB can be observed in progress using cytogenetic techniques, but generally BFB must be inferred from data like microarrays or sequencing collected after BFB has ceased. Making correct inferences from this data is not straightforward, particularly given the complexity of some cancer genomes and BFB's ability to generate a wide range of rearrangement patterns. Here we present algorithms to aid the interpretation of evidence for BFB. We first pose the BFB count vector problem: given a chromosome segmentation and segment copy numbers, decide whether BFB can yield a chromosome with the given segment counts. We present the first linear-time algorithm for the problem, improving a previous exponential-time algorithm. We then combine this algorithm with fold-back inversions to develop tests for BFB. We show that, contingent on assumptions about cancer genome evolution, count vectors and fold-back inversions are sufficient evidence for detecting BFB. We apply the presented techniques to paired-end sequencing data from pancreatic tumors and confirm a previous finding of BFB as well as identify a new chromosomal region likely rearranged by BFB cycles, demonstrating the practicality of our approach.