Pathway-based serum microRNA profiling and survival in patients with advanced stage non-small cell lung cancer

Yan Wang, Jian Gu, Jack A. Roth, Michelle A T Hildebrandt, Scott M. Lippman, Yuanqing Ye, John D. Minna, Xifeng Wu

Research output: Contribution to journalArticlepeer-review

73 Scopus citations


This study was designed to identify TGF-b signaling pathway-related serum microRNAs (miRNA) as predictors of survival in advanced non-small cell lung cancer (NSCLC). Serum samples from 391 patients with advanced NSCLC were collected before treatment. Global miRNA microarray expression profiling based on sera from four patients with good survival (>24 months) and four patients with poor survival (<6 months) was used to identify 140 highly expressed serum miRNAs, among which 35 miRNAs had binding sites within the 30-untranslated regions of a panel of 11 genes in the TGF-b signaling pathway and were assayed by quantitative RT-PCR for their associations with survival in a training (n = 192) and testing set (n = 191). Out of the 35 miRNAs, survival analysis using Cox regression model identified 17 miRNAs significantly associated with 2-year patient survival. MiR-16 exhibited the most statistically significant association: high expression of miR-16 was associated with a significantly better survival [adjusted hazard ratio (HR) = 0.4, 95% confidence interval (CI): 0.3-0.5]. A combined 17-miRNA risk score was created that was able to identify patients at the highest risk of death. Those with a high-risk score had a 2.5-fold increased risk of death compared with those with a low risk score (95% CI: 1.8-3.4; P = 1.1 × 10-7). This increase in risk of death was corresponding to a 7.8-month decrease in median survival time (P = 9.5 × 10-14). Our results suggest that serum miRNAs could serve as predictors of survival for advanced NSCLC.

Original languageEnglish (US)
Pages (from-to)4801-4809
Number of pages9
JournalCancer research
Issue number15
StatePublished - Aug 1 2013

ASJC Scopus subject areas

  • Oncology
  • Cancer Research


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