Integrated analyses of microRNAs demonstrate their widespread influence on gene expression in high-grade serous ovarian carcinoma Journal Article


Authors: Creighton, C. J.; Hernandez-Herrera, A.; Jacobsen, A.; Levine, D. A.; Mankoo, P.; Schultz, N.; Du, Y.; Zhang, Y.; Larsson, E.; Sheridan, R.; Xiao, W.; Spellman, P. T.; Getz, G.; Wheeler, D. A.; Perou, C. M.; Gibbs, R. A.; Sander, C.; Hayes, D. N.; Gunaratne, P. H.
Article Title: Integrated analyses of microRNAs demonstrate their widespread influence on gene expression in high-grade serous ovarian carcinoma
Abstract: Background: The Cancer Genome Atlas (TCGA) Network recently comprehensively catalogued the molecular aberrations in 487 high-grade serous ovarian cancers, with much remaining to be elucidated regarding the microRNAs (miRNAs). Here, using TCGA ovarian data, we surveyed the miRNAs, in the context of their predicted gene targets. Methods and Results: Integration of miRNA and gene patterns yielded evidence that proximal pairs of miRNAs are processed from polycistronic primary transcripts, and that intronic miRNAs and their host gene mRNAs derive from common transcripts. Patterns of miRNA expression revealed multiple tumor subtypes and a set of 34 miRNAs predictive of overall patient survival. In a global analysis, miRNA:mRNA pairs anti-correlated in expression across tumors showed a higher frequency of in silico predicted target sites in the mRNA 3′-untranslated region (with less frequency observed for coding sequence and 5′-untranslated regions). The miR-29 family and predicted target genes were among the most strongly anti-correlated miRNA:mRNA pairs; over-expression of miR-29a in vitro repressed several anti-correlated genes (including DNMT3A and DNMT3B) and substantially decreased ovarian cancer cell viability. Conclusions: This study establishes miRNAs as having a widespread impact on gene expression programs in ovarian cancer, further strengthening our understanding of miRNA biology as it applies to human cancer. As with gene transcripts, miRNAs exhibit high diversity reflecting the genomic heterogeneity within a clinically homogeneous disease population. Putative miRNA:mRNA interactions, as identified using integrative analysis, can be validated. TCGA data are a valuable resource for the identification of novel tumor suppressive miRNAs in ovarian as well as other cancers. © 2012 Creighton et al.
Keywords: controlled study; human tissue; human cell; overall survival; genetics; cancer grading; neoplasm; cell proliferation; ovarian neoplasms; metabolism; cell viability; gene overexpression; microrna; gene expression profiling; breast; genetic transcription; in vitro study; pathology; cell line, tumor; gene expression regulation; oncogene; gene expression regulation, neoplastic; 5' untranslated region; ovary tumor; tumor cell line; ovary carcinoma; hemizygosity; 3' untranslated region; micrornas; serosa; genetic heterogeneity; 3' untranslated regions; genetic database; genetic algorithm; dna copy number variations; copy number variation; rna methylation; neoplasms, cystic, mucinous, and serous; dnmt3a gene; dnmt3b gene; mirn29 microrna, human
Journal Title: PLoS ONE
Volume: 7
Issue: 3
ISSN: 1932-6203
Publisher: Public Library of Science  
Date Published: 2012-01-01
Start Page: e34546
Language: English
DOI: 10.1371/journal.pone.0034546
PROVIDER: scopus
PMCID: PMC3315571
PUBMED: 22479643
DOI/URL:
Notes: --- - "Export Date: 1 May 2012" - "Source: Scopus"
Altmetric
Citation Impact
BMJ Impact Analytics
MSK Authors
  1. Douglas A Levine
    380 Levine
  2. Parminder Kaur Mankoo
    3 Mankoo
  3. Erik Larsson
    11 Larsson
  4. Chris Sander
    210 Sander
  5. Nikolaus D Schultz
    487 Schultz