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M. Mori
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P3.06 - Poster Session/ Screening and Early Detection (ID 220)
- Event: WCLC 2015
- Type: Poster
- Track: Screening and Early Detection
- Presentations: 1
- Moderators:
- Coordinates: 9/09/2015, 09:30 - 17:00, Exhibit Hall (Hall B+C)
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P3.06-010 - The Performance of a Novel Amino Acid Multivariate Index for Detecting Lung Cancer: A Case Control Study in Korea (ID 755)
09:30 - 09:30 | Author(s): M. Mori
- Abstract
Background:
Previous studies have shown that plasma free amino acid (PFAA) profiles are altered in cancer patients compared with healthy controls. A multivariate index based on PFAAs was generated from a Japanese dataset and has been previously demonstrated to be clinically valuable for discriminating patients in the early stages of lung cancer. However, it remains unclear whether similar PFAA profile changes occur in cancer patients from other populations. Therefore, this study aimed to validate the performance of this index in discriminating lung cancer patients from controls in the Korean population.
Methods:
Samples were collected from a total of 142 Korean subjects (72 lung cancer/70 controls) for this study. PFAAs were quantified by high-performance liquid chromatography-electrospray ionization-mass spectrometry, and the clinical performance characteristics of the amino acid multivariate index were evaluated across cancer stages and histological types.
Results:
The concentrations of several PFAAs were significantly decreased in the Korean lung cancer patients compared with the controls. Significant decreases in threonine, citrulline, histidine and tryptophan and increases in proline, isoleucine, phenylalanine and ornithine were observed, which are similar to the PFAA changes reported by a previous Japanese study. The area under the receiver-operator characteristic curve (AUC of the ROC) for the index was 0.80, and similar performances were demonstrated for the different histological types.
Conclusion:
These results suggest that the amino acid multivariate index previously developed from a Japanese dataset has the potential to aid in the early detection of lung cancers of different histological types in Korean patients.
