Background: Whole-genome doubling (WGD) is a common mutation in cancer. Various studies have suggested that WGD is associated with a poor prognosis in cancer. However, the detailed association between WGD occurrence and prognosis remains unclear. In this study, we aimed to elucidate the mechanism by which WGD affects prognosis using sequencing data from the Pan-Cancer Analysis of Whole Genomes (PCAWG) and The Cancer Genome Atlas.
Methods: Whole-genome sequencing data of 23 cancer types were downloaded from PCAWG project. We defined the WGD event in each sample using the WGD status annotated using PCAWG. We used MutationTimeR to predict the relative timings of mutations and loss of heterozygosity (LOH) in WGD, thus evaluating their association with WGD. We also analyzed the association between WGD-associated factors and patient prognosis.
Results: WGD was associated with several factors, e.g., length of LOH regions. Survival analysis using WGD-associated factors revealed that longer LOH regions and LOH in chr17 were associated with poor prognosis in samples with WGD (WGD samples) and samples without WGD (nWGD samples). In addition to these two factors, nWGD samples showed that the number of mutations in tumor suppressor genes was associated with prognosis. Moreover, we explored the genes associated with prognosis in both samples separately.
Conclusion: The prognosis-related factors in WGD samples differed significantly compared with those in nWGD samples. This study emphasizes the need for different treatment strategies for WGD and nWGD samples.
Keywords: Computational biology; Genes; Genetics; Genomics; Mutation; PCAWG; TCGA.
© 2023. The Author(s).