An in silico model of LINE-1-mediated neoplastic evolution.
Bioinformatics
; 36(14): 4144-4153, 2020 08 15.
Article
em En
| MEDLINE
| ID: mdl-32365170
ABSTRACT
MOTIVATION Recent research has uncovered roles for transposable elements (TEs) in multiple evolutionary processes, ranging from somatic evolution in cancer to putatively adaptive germline evolution across species. Most models of TE population dynamics, however, have not incorporated actual genome sequence data. The effect of site integration preferences of specific TEs on evolutionary outcomes and the effects of different selection regimes on TE dynamics in a specific genome are unknown. We present a stochastic model of LINE-1 (L1) transposition in human cancer. This system was chosen because the transposition of L1 elements is well understood, the population dynamics of cancer tumors has been modeled extensively, and the role of L1 elements in cancer progression has garnered interest in recent years. RESULTS:
Our model predicts that L1 retrotransposition (RT) can play either advantageous or deleterious roles in tumor progression, depending on the initial lesion size, L1 insertion rate and tumor driver genes. Small changes in the RT rate or set of driver tumor-suppressor genes (TSGs) were observed to alter the dynamics of tumorigenesis. We found high variation in the density of L1 target sites across human protein-coding genes. We also present an analysis, across three cancer types, of the frequency of homozygous TSG disruption in wild-type hosts compared to those with an inherited driver allele. AVAILABILITY AND IMPLEMENTATION Source code is available at https//github.com/atallah-lab/neoplastic-evolution. CONTACT jlebien@uno.edu. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Elementos de DNA Transponíveis
/
Elementos Nucleotídeos Longos e Dispersos
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Bioinformatics
Assunto da revista:
INFORMATICA MEDICA
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Estados Unidos