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laor Chailurkit
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P2.11 - Screening and Early Detection (ID 178)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Screening and Early Detection
- Presentations: 1
- Moderators:
- Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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P2.11-25 - Pre- and Post-Surgery Metabolomic Profiles in Early-Stage NSCLC Patients (ID 2476)
10:15 - 18:15 | Author(s): laor Chailurkit
- Abstract
Background
Finding biomarkers to detect cancer at its early stage is of importance. Since metabolic reprogramming is a hallmark of cancer, oncometabolite is thus a promising target.Progress in cancer metabolomics opens the door for large scale screening of cancer-specific metabolites that could be future applied for subclinical stage detection and novel therapeutic targets.
Method
Seventy paired pre- and postoperative plasma samples of early-stage NSCLC patients who had completed curative surgery during 2015-2018 with ≥ 3 months disease free were retrieved. Demographic and Clinical data were collected. All samples were subjected to targeted metabolomics analysis using AbsoluteIDQ® p180 Kit on ESI 5500 LC-MS/MS System equipped with 1260 Series HPLC, according to the manufacturer's instruction.Multivariate analysis including PCA and OPLS-DA were used to identify the difference between pre- vs post-operative sample set. T-test was used to confirmed if the metabolites significantly different among groups at the univariate level (p < 0.05).
Result
Of the 70 patients, 31 (44.3%) were male and 39 (55.7%) were female. Median age was 63 years old (23 - 85). Majority of them were never-smokers (64.3%). Adenocarcinoma was the most common histology (91.4%). EGFR mutation was tested in 34 (48.6%) patients, of which, 22(64.7%) of them were positive. Metabolomic analysis revealed tryptophan as the most statistically significant change, together with other amino acids, carnitines, biogenic amines, and lipids (Table1). Besides glutamate, all metabolites increased postoperatively.Metabolites with VIP scores (Variable Importance in Projection) ≥ 1.5, including tryptophan, lysophosphatidylcholine-acyl C16:0, lysophosphatidylcholine-acyl C18:0, and carnitine, were assembled together for a predictive model which will be presented at the congress.
Table 1: Metabolites with significant difference between pre- and post-surgery in early-stage NSCLC patients
ConclusionMetabolite (ng/ml)
Pre operation (N=70)
Post operative (N=70)
Fold change
p-value
VIP score
Mean
SD
Mean
SD
Amino acid
Glutamate
17,449.31
7,808.80
10,192.53
5,294.28
-0.374
<0.001
1.21
Glutamine
87,406.56
22,839.10
104,994.00
26,276.52
0.324
<0.001
0.77
Arginine
10,869.44
5,082.21
16,101.94
8,220.61
0.481
<0.001
0.79
Asparagine
5,023.79
1,294.80
7,630.93
2,343.85
0.663
<0.001
1.34
Tryptophan
6,921.41
1,579.37
13,189.77
4,105.45
0.992
<0.001
1.70
Acrylcarnitine
carnitine (C0)
4,680.23
1,292.54
7,263.51
2,136.29
0.657
<0.001
1.50
Biogenic amine
Creatinine
7,262.43
2,410.21
10,529.83
4,070.33
0.536
<0.001
1.14
Kynurenine
363.42
126.06
571.91
232.05
0.723
<0.001
0.82
Sphingolipid
SM C16:1
8,837.49
2,290.28
10,875.53
2,970.15
0.290
<0.001
1.33
SM C20:2
178.18
60.77
205.47
66.55
0.304
0.005
0.43
Phosphatidylcholine
lysoPC a C16:0
26,863.83
6,420.81
45,877.36
13,732.55
0.774
<0.001
1.67
lysoPC a C16:1
740.24
287.44
1,256.99
588.67
0.842
<0.001
1.33
lysoPC a C17:0
303.24
90.78
521.36
200.39
0.853
<0.001
1.45
lysoPC a C18:0
8,449.64
2,593.82
14,854.50
5,047.03
0.885
<0.001
1.60
lysoPC a C18:2
6,818.04
2,466.61
11,990.73
4,760.87
0.965
<0.001
1.37
We identified a distinct cluster of significant metabolic biomarkers associated with early-stage NSCLC. Tryptophan is the most significant one that associated with cancer metabolome. These would be potential biomarker profile for early-stage NSCLC detection.Larger cohort is needed to be validated.