Virtual Library

Start Your Search

A. Chrząstek



Author of

  • +

    P2.01 - Poster Session with Presenters Present (ID 461)

    • Event: WCLC 2016
    • Type: Poster Presenters Present
    • Track: Biology/Pathology
    • Presentations: 1
    • +

      P2.01-016 - Analysis of 5 Differential miRNA Expression in NSCLC Patients (ID 5140)

      14:30 - 14:30  |  Author(s): A. Chrząstek

      • Abstract

      Background:
      There are two main types of lung cancer: non small cell lung cancer (NSCLC) which represents 80-85% cases of lung cancer and small cell lung cancer (SCLC) which is about 10-15% cases of lung cancer. The 5-year survival rate for patients with lung cancer vary depending on the stage of the cancer when it is diagnosed. Unfortunately, most of patients with lung cancer are diagnosed on later stage of disease (stage III and IV). In our research we try to find marker among miRNA that can predict occurring of lung cancer on the earlier stage.

      Methods:
      Isolation of miRNA from plasma was performed by miRCURY RNA Isolation Kit – Biofluids (Exiqon) from NSCLC patients and controls. Synthesis of cDNA and qPCR were carried out using miRCURY LNA[TM] Universal RT microRNA PCR with LNA[TM] enhanced PCR Primers (Exiqon). Statistical calculations were executed on 11 samples as a Pre-eliminary data.

      Results:
      Results are shown in the following table.Figure 1



      Conclusion:
      We assed level of 5 different miRNAs circulating in the blood of NSCLC patients using qPCR. Our initial results show that different miRNA can be used to stratify patients and miRNA. Expression of hsa-miR-451a is decreasing in NSCLC versus negative control. Interestingly up-regulated hsa-miR-660-5p was recently described as a prognostic marker in breast cancer but our result preliminary results showed constant decrease in hsa-miR-660-5p expression in all patients’ groups vs controls. The examination on the bigger cohort of patients is necessary to receive a more statistically significant and conclusive data.