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Genomic Signatures Predict Poor Outcome in Undifferentiated Pleomorphic Sarcomas and Leiomyosarcomas

Authors
Journal
PLoS ONE
1932-6203
Publisher
Public Library of Science
Publication Date
Volume
8
Issue
6
Identifiers
DOI: 10.1371/journal.pone.0067643
Keywords
  • Research Article
  • Biology
  • Genetics
  • Human Genetics
  • Genetic Association Studies
  • Cancer Genetics
  • Genomics
  • Genome Analysis Tools
  • Genetic Screens
  • Medicine
  • Clinical Genetics
  • Genetic Testing
  • Diagnostic Medicine
  • Pathology
  • Clinical Pathology
  • Molecular Genetics
  • General Pathology
  • Biomarkers
  • Oncology
  • Cancers And Neoplasms
  • Bone And Soft Tissue Sarcomas
Disciplines
  • Biology

Abstract

Undifferentiated high-grade pleomorphic sarcomas (UPSs) display aggressive clinical behavior and frequently develop local recurrence and distant metastasis. Because these sarcomas often share similar morphological patterns with other tumors, particularly leiomyosarcomas (LMSs), classification by exclusion is frequently used. In this study, array-based comparative genomic hybridization (array CGH) was used to analyze 20 UPS and 17 LMS samples from untreated patients. The LMS samples presented a lower frequency of genomic alterations compared with the UPS samples. The most frequently altered UPS regions involved gains at 20q13.33 and 7q22.1 and losses at 3p26.3. Gains at 8q24.3 and 19q13.12 and losses at 9p21.3 were frequently detected in the LMS samples. Of these regions, gains at 1q21.3, 11q12.2-q12.3, 16p11.2, and 19q13.12 were significantly associated with reduced overall survival times in LMS patients. A multivariate analysis revealed that gains at 1q21.3 were an independent prognostic marker of shorter survival times in LMS patients (HR = 13.76; P = 0.019). Although the copy number profiles of the UPS and LMS samples could not be distinguished using unsupervised hierarchical clustering analysis, one of the three clusters presented cases associated with poor prognostic outcome (P = 0.022). A relative copy number analysis for the ARNT, SLC27A3, and PBXIP1 genes was performed using quantitative real-time PCR in 11 LMS and 16 UPS samples. Gains at 1q21-q22 were observed in both tumor types, particularly in the UPS samples. These findings provide strong evidence for the existence of a genomic signature to predict poor outcome in a subset of UPS and LMS patients.

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