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A.D. Pamungkas
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P1.03 - Poster Session with Presenters Present (ID 455)
- Event: WCLC 2016
- Type: Poster Presenters Present
- Track: Radiology/Staging/Screening
- Presentations: 1
- Moderators:
- Coordinates: 12/05/2016, 14:30 - 15:45, Hall B (Poster Area)
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P1.03-005 - High Resolution Metabolomics in Discovering Plasma Biomarkers of Lung Cancer Patients with EGFR Common Mutations (Exon 19 or 21) (ID 4978)
14:30 - 14:30 | Author(s): A.D. Pamungkas
- Abstract
Background:
The epidermal growth factor receptor (EGFR) is a key target in the treatment of advanced non-small cell lung cancer (NSCLC). The presence of EGFR mutations predicts the sensitivity to EGFR tyrosine kinase inhibitors (TKIs) of NSCLC patients. For this reason, EGFR mutation test is required to provide personalized treatment options. Currently available DNA sources are mainly small biopsies and cytological samples, providing limited and low-quality material. So, there is the need of new biomarker discovery. Recently, metabolomics, which is the comprehensive study of low molecular weight metabolites, has also been developed. Integration of transcriptomic and metabolomic data has enabled deeper analysis of chemosensitive pathways. In this regard, this study aims to apply high resolution metabolomics (HRM) to detect significant compounds that might contribute in inducing EGFR mutations.
Methods:
Plasma samples from 2 healthy volunteers and 15 lung cancer patients were analyzed to detect biomarkers which can predict EGFR mutations. The comparison was made between healthy control and lung cancer groups for metabolic differences. Ten patients had EGFR mutations and five patients had wild type EGFR (n=5) in tumor tissue. The EGFR mutation group was divided into exon 21 deletion group (n=6), and exon 19 deletion group (n=4). Differences in metabolic profiles of EGFR mutation lung cancer populations and EGFR wild type lung cancer patients were examined. Metabolites were separated using Agilent 1200 High Performance Liquid Chromatography and Agilent 6530 quadrupole time-of-flight LC/MS.
Results:
From 216 metabolites, 112 metabolites were found to be significantly different. Relative concentration of L-valine, linoleate, tetradecanoyl carnitine, 5-MTHF, and N-succinyl-L-Glutamate-5 semialdehyde showed significant difference (p<0.05). Linoleic acid was elevated in mutation group while tetradecanoyl carnitine was found to be lowered in mutation group. These two compounds are related to the alteration of mitochondrial energy metabolism (carnitine shuttle). Compounds related to amino acid metabolism, L-valine and N-succinyl-L-Glutamate-5 semi aldehyde were increased in mutation group.
Conclusion:
Our results show that HRM with the combination of pathway analysis from significant metabolites was able to discriminate an EGFR mutation positive patients (exon 19 or exon 21) from wild type advanced NSCLC patients. Therefore, high resolution metabolomics can be the potential non-invasive tool to utilize clinically to detect the EGFR mutations in NSCLC patients.
