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P. Stanton



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    P1.06 - Poster Session 1 - Prognostic and Predictive Biomarkers (ID 161)

    • Event: WCLC 2013
    • Type: Poster Session
    • Track: Biology
    • Presentations: 1
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      P1.06-045 - Serum microRNA as a predictive marker for radiation pneumonitis in patients with inoperable/unresectablenon-small cell lung cancer (NSCLC) (ID 2795)

      09:30 - 09:30  |  Author(s): P. Stanton

      • Abstract

      Background
      Radiation pneumonitis (RP) is a major dose-limiting toxicity after thoracic radiotherapy (RT), with no good models available to accurately predict the individual risk.MicroRNAs (miRNAs) are found to be stable in serum and other body fluids,with exciting potential as novel non-invasive biomarkers. This study is to investigate serum microRNAs associated with RP grade ≥ 2 in inoperable/unresectable NSCLC patients treated with definitive RT.

      Methods
      134 patients with inoperable/unresectable NSCLC treated with definitive RT (18-month minimum follow-up) were eligible. Serum samples were collected prospectively before treatment. 100 patients who had enough serum and reliable miRNA profile quality were included in this study. MiRNA profiling was performed using real-time PCR-based array, containing a panel of 84 miRNAs detectable in human bodily fluids. Spiked-in cel-miR-39 was used for normalization. The primary endpoint was symptomatic RP (grade 2 and higher). 2-sample mean comparisons were used between the RP and non-RP subgroups.Stepwise Logistic regression model building was used to build a miRNA signature. Receiver operator characteristic (ROC) analysis was used to assess the predictive ability of single-marker and signature of RP.

      Results
      Of 100 patients enrolled, 17 (17.0%) patients developed symptomatic RP. Patients received a median of 70 Gy (34-85.6Gy) of RT with a mean lung dose (MLD) of 16.9 Gy (2.1-25.5 Gy). Serum miRNA profiling identified pre-treatment expressions of 9miRNAs were significantly associated with risk of RP (p<0.05). Significant correlations were not found for any clinical or dosimetric parameters including age, gender, stage, MLD (p>0.05). Stepwise regression modeling identified only has-miR-191 as significant predictors of symptomatic RP (HR=4.94, 95%CI:1.46-16.66, p=0.01). Using ROC curves, we found has-miR-191 was independent predictors of symptomatic RP (p=0.01). A model of combining has-miR-191 and MLD had AUC of 0.72 (p=0.004) comparing to 0.64 of MLD alone (p=0.08).

      Conclusion
      In our preliminary analysis, baseline serum has-miR-191 may help predictingsymptomaticRP. However, analysis on larger and independent datasets will be required to verify our findings.

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    P3.06 - Poster Session 3 - Prognostic and Predictive Biomarkers (ID 178)

    • Event: WCLC 2013
    • Type: Poster Session
    • Track: Biology
    • Presentations: 1
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      P3.06-041 - Serum miRNA signature predicts survival in patients with unresectable/inoperable non-small cell lung cancer treated with definitive radiation therapy (ID 2785)

      09:30 - 09:30  |  Author(s): P. Stanton

      • Abstract

      Background
      The expression profiles of serum micro RNAs (miRNAs) are known to predict overall survival (OS) of metastatic and operable non-small cell lung cancer (NSCLC). We hypothesized that circulating miRNAs is also correlated with survival in unresectable/inoperable NSCLC treated with radiation therapy (RT).

      Methods
      134 patients with inoperable/unresectable NSCLC treated with definitive RT (18-month minimum follow-up) were eligible. Serum samples were collected prospectively before RT commencement. 100 patients with enough serum and reliable miRNA profile quality were randomly divided into training and validation sets (50 patients each). MiRNA profiling was performed using real-time PCR-based array, containing a panel of 84 miRNAs detectable in human bodily fluids. Spiked-in cel-miR-39 was used for normalization. Stepwise regression Cox model building was used to build a miRNA signature on the training set, which was then assessed on the validation set both alone and with clinical factors.

      Results
      The median age was 67 years; 76% were stages III and 79% received chemoradiation; the median physical dose was 70 Gy. Stepwise regression modeling identified five miRNAs as jointly significant predictors. Using coefficients from Cox model fit, the miRNA signature was 0.53*log(hsa-miR-15b)+0.21*log(hsa-miR-34a)-0.27*log(hsa-miR-221)-0.27*log(hsa-miR-224) -0.07*log(hsa-miR-130b). This signature was a significant predictor of OS in the validation set (p=0.011). It retained statistical significance in a model also containing terms for GTV Volume and KPS, the only two significant clinical factors in univariate analysis in the validation set (p=0.012). Using computational methods (TargetScan6.2) for miRNA target prediction, the putative targets of these five miRNAs are known to modulate apoptosis, cell cycle control, DNA damage response and repair process (including nucleotide excision repair and DNA translesion synthesis), angiogenesis and epithelial-mesenchymal transition.

      Conclusion
      In this study, we developed a prognostic miRNA signature consisting of five miRNAs and validated in an independent dataset for unresectable/inoperable NSCLC treated with RT. This circulating miRNA signature may be used as a non-invasive biomarker, which may have prognostic or therapeutic implications for the future management of locally advance NSCLC patients. Larger sample size studies are needed to further validate our findings.