Differential expression profiling of microRNAs and their potential involvement in esophageal squamous cell carcinoma

Tumour Biol. 2014 Apr;35(4):3295-304. doi: 10.1007/s13277-013-1432-5. Epub 2013 Nov 22.

Abstract

MicroRNAs are small, noncoding RNAs approximately 18-24 nucleotides in length that negatively regulate gene expression at the posttranscriptional and/or translational level by binding to complimentary sequences in the 3'-untranslated regions of target mRNAs. Growing evidence has indicated the important roles for different miRNA species in the development of different cancers. Therefore, miRNAs have the potential to become new biological markers for esophageal squamous cell carcinoma (ESCC) and to be applied in the diagnosis, prognosis, and targeted treatment of ESCC. In this study, we performed a miRNA microarray to analyze the miRNA expression profile in ESCC compared to normal tissues. Then, we made a preliminary analysis of the biological function for the most differentially expressed miRNAs and their potentially target genes regulated. Some microarray results were validated by performing quantitative RT-PCR. The study provided evidence that linked the biological role of miRNAs to ESCC and showed that miRNAs could undertake a variety of mechanisms. Additionally, we also found that altered miR-429 and miR-451 expression levels were associated with the occurrence of lymph node metastases and the differentiation status and TNM stage in ESCC. The study of miRNAs may lead to finding novel methods to diagnose, treat, and prevent ESCC.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Base Sequence
  • Carcinoma, Squamous Cell / genetics*
  • Carcinoma, Squamous Cell / pathology
  • Esophageal Neoplasms / genetics*
  • Esophageal Neoplasms / pathology
  • Esophageal Squamous Cell Carcinoma
  • Female
  • Gene Expression Profiling*
  • Gene Expression Regulation, Neoplastic*
  • Gene Regulatory Networks
  • Humans
  • Lymphatic Metastasis
  • Male
  • MicroRNAs / analysis*
  • Middle Aged
  • Molecular Sequence Data

Substances

  • MicroRNAs