4.3 Article

NELL1, whose high expression correlates with negative outcomes, has different methylation patterns in alveolar and embryonal rhabdomyosarcoma

Journal

ONCOTARGET
Volume 8, Issue 20, Pages 33086-33099

Publisher

IMPACT JOURNALS LLC
DOI: 10.18632/oncotarget.16526

Keywords

DNA methylation; RRBS; sequencing; rhabdomyosarcoma; NELL1

Funding

  1. Fondazione Citta della Speranza (the City of Hope Foundation)
  2. Associazione Italiana per la Ricerca sul Cancro (The Italian Association for Cancer Research) [13576/2012]

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Rhabdomyosarcoma (RMS), which represents the most frequent soft tissue sarcoma in pediatric populations, is classified into two major subtypes: embryonal RMS (ERMS) and alveolar RMS (ARMS). ARMS subtype, which shows greater aggressiveness and proneness to metastasis with respect to ERMS, are characterized, in about 75% of cases, by specific chromosomal translocations that involve PAX and FOXO1 genes. Many findings have demonstrated that PAX/FOXO1-positive ARMS have a worse prognosis than PAX/FOXO1-negative ones and that distinct molecular features characterize RMS with different gene fusion statuses. DNA methylation, which presently represents a challenging research area, is involved in the modulation of gene expression. We performed a genome-wide DNA methylation analysis using reduced-representation bisulfite sequencing (RRBS) in RMS samples and we found that fusion-positive alveolar and embryonal subgroups have different DNA methylation signatures and that ARMS fusion-positive subtypes are characterized by overall hypomethylation levels. While NELL1 was found to be hypomethylated and transcriptionally enhanced in RMS alveolar subtypes, high NELL1 expression levels, which proved to be correlated with negative RMS prognostic factors such as fusion status and histology (P < 0.0001), were found to discriminate between RMS patients with different outcomes (P < 0.05). In conclusion, our results demonstrated that different DNA methylation patterns distinguish between different RMS subgroups and they suggest that epigenetic signatures could be useful for risk stratification of patients.

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