On the reproducibility of TCGA ovarian cancer microRNA profiles

PLoS One. 2014 Jan 29;9(1):e87782. doi: 10.1371/journal.pone.0087782. eCollection 2014.

Abstract

Dysregulated microRNA (miRNA) expression is a well-established feature of human cancer. However, the role of specific miRNAs in determining cancer outcomes remains unclear. Using Level 3 expression data from the Cancer Genome Atlas (TCGA), we identified 61 miRNAs that are associated with overall survival in 469 ovarian cancers profiled by microarray (p<0.01). We also identified 12 miRNAs that are associated with survival when miRNAs were profiled in the same specimens using Next Generation Sequencing (miRNA-Seq) (p<0.01). Surprisingly, only 1 miRNA transcript is associated with ovarian cancer survival in both datasets. Our analyses indicate that this discrepancy is due to the fact that miRNA levels reported by the two platforms correlate poorly, even after correcting for potential issues inherent to signal detection algorithms. Corrections for false discovery and microRNA abundance had minimal impact on this discrepancy. Further investigation is warranted.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Female
  • Humans
  • MicroRNAs / genetics
  • MicroRNAs / metabolism*
  • Oligonucleotide Array Sequence Analysis*
  • Ovarian Neoplasms / genetics*
  • Ovarian Neoplasms / metabolism
  • Ovarian Neoplasms / mortality*
  • Proportional Hazards Models
  • Reproducibility of Results
  • Transcriptome

Substances

  • MicroRNAs

Grants and funding

This work is supported in part through the Collaborative Advances in Biomedical Computing Seed Funding Program at the Ken Kennedy Institute for Information Technology at Rice University supported by the John and Ann Doerr Fund for Computational Biomedicine and through the Center for Computational and Integrative Biomedical Research Seed Funding Program at Baylor College of Medicine. GA is also partially supported by NSF DMS-1209017. ZD is supported by the Houston Bioinformatics Endowment and NSF DMS-1263932. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.