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MicroRNAs MiR-218, MiR-125b, and Let-7g Predict Prognosis in Patients with Oral Cavity Squamous Cell Carcinoma

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  • Shih-Chi Peng
  • Chun-Ta Liao
  • Chien-Hua Peng
  • Ann-Joy Cheng
  • Shu-Jen Chen
  • Chung-Guei Huang
  • Wen-Ping Hsieh
  • Tzu-Chen Yen

Abstract

MicroRNAs (miRNAs) have a major impact on regulatory networks in human carcinogenesis. In this study, we sought to investigate the prognostic significance of miRNAs in patients with oral cavity squamous cell carcinoma (OSCC). In a discovery phase, RNA was extracted from 58 OSCC tumor samples and paired normal tissues. MiRNAs expression was evaluated with TaqMan Array Card and TaqMan MicroRNA assays. The prognostic significance of the miRNA signature identified in the discovery phase was validated by qRT-PCR in a replication set consisting of 141 formalin-fixed, paraffin-embedded (FFPE) samples. We identified a miRNA regulatory network centered on the three hub genes (SP1, MYC, and TP53) that predicted distinct clinical endpoints. Three miRNAs (miR-218, miR-125b, and let-7g) and their downstream response genes had a concordant prognostic significance on disease-free survival and disease-specific survival rates. In addition, patients with a reduced expression of miR-218, miR-125b, and let-7g have a higher risk of poor outcomes in presence of specific risk factors (p-stage III-IV, pT3-4, or pN+). Our findings indicate that specific miRNAs have prognostic significance in OSCC patients and may improve prognostic stratification over traditional risk factors.

Suggested Citation

  • Shih-Chi Peng & Chun-Ta Liao & Chien-Hua Peng & Ann-Joy Cheng & Shu-Jen Chen & Chung-Guei Huang & Wen-Ping Hsieh & Tzu-Chen Yen, 2014. "MicroRNAs MiR-218, MiR-125b, and Let-7g Predict Prognosis in Patients with Oral Cavity Squamous Cell Carcinoma," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-9, July.
    • Handle: RePEc:plo:pone00:0102403
    DOI: 10.1371/journal.pone.0102403
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    1. Hyonho Chun & Sündüz Keleş, 2010. "Sparse partial least squares regression for simultaneous dimension reduction and variable selection," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(1), pages 3-25, January.
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