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Y.J. Jung
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P1.05 - Poster Session with Presenters Present (ID 457)
- Event: WCLC 2016
- Type: Poster Presenters Present
- Track: Early Stage NSCLC
- Presentations: 1
- Moderators:
- Coordinates: 12/05/2016, 14:30 - 15:45, Hall B (Poster Area)
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P1.05-007 - Analysis of RNA Sequencing Data along with PET SUV-max Can Discover Novel Gene Sets Which Can Predict Surgical Outcome of NSCLC (ID 5404)
14:30 - 14:30 | Author(s): Y.J. Jung
- Abstract
Background:
Recent development of NGS technology provides a better understanding on the molecular mechanism of the cancer. A comprehensive analysis algorism of NGS data along with various clinical phenotypes and clinical outcome may lead discovery of novel molecular mechanism of cancer biology. It has been suggested that the preoperative SUV of the PET-CT is related to the aggressiveness of the cancer. We hypothesized that the identification of genes that were related to the PET SUV-max would lead a discovery of novel genes which could predict long-term outcomes of patients of non-small cell lung cancer.
Methods:
We set a 51 adenocarcinoma and a 101 squamous cell carcinoma patients cohort, whose cancer and normal tissue whole transcriptome sequencing data were available. The RNA sequencing fastq files were aligned on the reference genome (http://grch37.ensembl.org/) and the differential expressions were analyzed using tuxedo protocol (TopHat 2.0, Cufflinks 2.2.1). Visualizations of differential expressions were presented with CummeRbund R-package.
Results:
Based on the preoperative PET-CT SUV-max, patients were classified as "Low" (SUV≤3), "Intermediate" (SUV 3-10), and "High" (SUV>10) groups. Using the tuxedo RNA analysis tools, we selected 31 genes which showed significantly different expression of RNAs between "Low" and "High" groups in adenocarcinoma and between “Intermediate” and “High” groups in squamous cell carcinoma. By comparing expression levels of those 31 genes according to the development of recurrence, we could identify two sets of genes (COL2A1, BPIFB2, RYR2, F7, HPX, AC022596.6 and H19 for adenocarcinoma; BPIFB2, AC022596.6, ANKRD18B, GCLC, HHIPL2, COL2A1 and DPP10 for squamous cell carcinoma) which were related to the development of recurrence. Figure 1
Conclusion:
Our results suggest that it is necessary to set a comprehensive analysis algorithm of the NGS data along with various clinical phenotypes of the patients, for the discovery of clinically meaningful molecular mechanisms of the cancer.
