Key nodes of a microRNA network associated with the integrated mesenchymal subtype of high-grade serous ovarian cancer

Yan Sun, Fei Guo, Marina Bagnoli, Feng Xia Xue, Bao Cun Sun, Ilya Shmulevich, Delia Mezzanzanica, Ke Xin Chen, Anil K. Sood, Da Yang, Wei Zhang

Research output: Contribution to journalArticle

16 Citations (Scopus)

Abstract

Metastasis is the main cause of cancer mortality. One of the initiating events of cancer metastasis of epithelial tumors is epithelial-to-mesenchymal transition (EMT), during which cells dedifferentiate from a relatively rigid cell structure/morphology to a flexible and changeable structure/morphology often associated with mesenchymal cells. The presence of EMT in human epithelial tumors is reflected by the increased expression of genes and levels of proteins that are preferentially present in mesenchymal cells. The combined presence of these genes forms the basis of mesenchymal gene signatures, which are the foundation for classifying a mesenchymal subtype of tumors. Indeed, tumor classification schemes that use clustering analysis of large genomic characterizations, like The Cancer Genome Atlas (TCGA), have defined mesenchymal subtype in a number of cancer types, such as high-grade serous ovarian cancer and glioblastoma. However, recent analyses have shown that gene expression-based classifications of mesenchymal subtypes often do not associate with poor survival. This “paradox” can be ameliorated using integrated analysis that combines multiple data types. We recently found that integrating mRNA and microRNA (miRNA) data revealed an integrated mesenchymal subtype that is consistently associated with poor survival in multiple cohorts of patients with serous ovarian cancer. This network consists of 8 major miRNAs and 214 mRNAs. Among the 8 miRNAs, 4 are known to be regulators of EMT. This review provides a summary of these 8 miRNAs, which were associated with the integrated mesenchymal subtype of serous ovarian cancer.

Original languageEnglish
Pages (from-to)28-40
Number of pages13
JournalChinese Journal of Cancer
Volume34
Issue number1
DOIs
Publication statusPublished - 2015

Fingerprint

MicroRNAs
Ovarian Neoplasms
Epithelial-Mesenchymal Transition
Neoplasms
Neoplasm Metastasis
Messenger RNA
Survival
Atlases
Glioblastoma
Genes
Cluster Analysis
Genome
Gene Expression
Mortality
Proteins

Keywords

  • Cancer
  • Epithelial-to-mesenchymal transition (EMT)
  • MicroRNA (miRNA)
  • miR-101
  • miR-506
  • Ovary

ASJC Scopus subject areas

  • Oncology

Cite this

Key nodes of a microRNA network associated with the integrated mesenchymal subtype of high-grade serous ovarian cancer. / Sun, Yan; Guo, Fei; Bagnoli, Marina; Xue, Feng Xia; Sun, Bao Cun; Shmulevich, Ilya; Mezzanzanica, Delia; Chen, Ke Xin; Sood, Anil K.; Yang, Da; Zhang, Wei.

In: Chinese Journal of Cancer, Vol. 34, No. 1, 2015, p. 28-40.

Research output: Contribution to journalArticle

Sun, Yan ; Guo, Fei ; Bagnoli, Marina ; Xue, Feng Xia ; Sun, Bao Cun ; Shmulevich, Ilya ; Mezzanzanica, Delia ; Chen, Ke Xin ; Sood, Anil K. ; Yang, Da ; Zhang, Wei. / Key nodes of a microRNA network associated with the integrated mesenchymal subtype of high-grade serous ovarian cancer. In: Chinese Journal of Cancer. 2015 ; Vol. 34, No. 1. pp. 28-40.
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