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Songporn Oranratnachai
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EP1.14 - Targeted Therapy (ID 204)
- Event: WCLC 2019
- Type: E-Poster Viewing in the Exhibit Hall
- Track: Targeted Therapy
- Presentations: 1
- Now Available
- Moderators:
- Coordinates: 9/08/2019, 08:00 - 18:00, Exhibit Hall
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EP1.14-09 - Characterization of Actionable BRAF<sup>V600E</sup> and Co-Mutations in Non-Small Cell Lung Cancer (NSCLC) Patients (Now Available) (ID 1056)
08:00 - 18:00 | Author(s): Songporn Oranratnachai
- Abstract
Background
Targeting activated-mutations in NSCLC offers unique benefit that outperforms other cancers. Multiplex Next Generation Sequencing (NGS) platform provides opportunity for detection of low-frequency actionable-mutations such as BRAF V600E, which was previously reported in 1-2% of NSCLC and correlated with poorer response to chemotherapy. In this study, we used the NGS platform to determine the prevalence and characteristics of BRAF V600E-mutated NSCLC.
Method
Tissue archive of stage I-IV NSCLC from Ramathibodi and Phramongkutklao Hospitals during 2012-2015 was retrieved for DNA extraction. Samples were analyzed by NGS with Lung Cancer Panel 45 Genes on Ion Torrent system. Variants from NGS with coverage of higher than 1000X and ≥3% alternate variant frequency were considered as positive. The cutoff-point was validated by Real- time PCR. Clinical data correlation was analyzed.
Result
Of the 159 FFPE-samples, 16 samples (10.1%) with BRAFV600E mutation were identified. The median age was 66.6 years old. Majority of the patients were female (81.3%) and never-smoker (75%). Seven patients had early stage and 9 patients had stage III-IV disease. Co-mutations with BRAFV600E were found in 13 patients. EGFR mutation was the most common co-mutation (62.5%) follow by co-mutation with KRAS (37.5%), MET exon14 splice-site (18.8%), and PIK3CA (6.3%) (Table1). Advanced-stage patients with KRAS and MET exon14 splice-site co-mutations with BRAFV600E had worse survival (10.4, 10.4 months) compared to patients with EGFR co-mutation (41.1 months). Survival of patients with single BRAFV600E is better than patients with other co-mutations (not reach vs 60.5 months) in all stages.
Table 1: Baseline characteristics of 16 patients with BRAFV600E mutation and their co-mutated gene including palliative treatment in stage IV patients
ConclusionPatient ID
Gender
Age
Smoking
status
Staging
Co-mutation
First line treatment
Second line treatment
Current status
OS
(mo)
EGFR
KRAS
MET
PIK3CA
1
Female
62
Never
IA
L858R
Alive
2
Female
73
Never
IA
Del19, L858R
G12D
Alive
3
Female
50
Never
IA
Del19
G12C, G12D, Q61R
Alive
4
Female
67
Never
IA
G719S
G12D
Alive
5
Female
62
Never
IB
G12S
Alive
6
Female
67
Never
IB
G719A, del19
Alive
7
Female
75
Never
IIA
Alive
8
Female
80
Ex-smoke
IIIA
G12D, G13S
C2888-1G>A*
Death
10.4
9
Male
63
Ex-smoke
IIIA
Alive
10
Female
75
Never
IV
C3028G>T*
Gemcitabine
-
Death
7.9
11
Female
60
Never
IV
Del19
Carbo/Pac
Bevacizumab
Death
12.6
12
Female
59
Never
IV
L858R
C3028G>A*
Carbo/Pem
Erlotinib
Death
48.9
13
Female
89
Never
IV
L858R
Erlotinib
Osimertinib
Death
60.5
14
Male
74
Ex-smoke
IV
Del19
G12D, Q61L
H1047R
Carbo/Pac
Gemcitabine
Death
27.1
15
Female
58
Never
IV
Carbo/Gem
Carbo/Gem
Death
34.9
16
Male
71
Current smoke
IV
L858R
Gefitinib
Carbo/Gem
Death
41.1
Our data demonstrated high prevalence of BRAF V600E and coexisting-actionable mutations. BRAFV600E-mutated NSCLC are common in female and never-smoker. Co-mutations with other actionable-mutations patients showed worse survival compared to single BRAFV600E patients. Integrating the sensitive multiplex NGS method into the clinical practice will help broaden the opportunity for superior treatment efficacy in the future.
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P2.04 - Immuno-oncology (ID 167)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Immuno-oncology
- Presentations: 1
- Moderators:
- Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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P2.04-78 - PD-L1 Expression as a Prognostic Marker for Non-Small Cell Lung Cancer in Distinct Mutational Status (ID 2927)
10:15 - 18:15 | Author(s): Songporn Oranratnachai
- Abstract
Background
Programmed death-ligand 1 (PD-L1) expression is widely used as the predictive biomarker for immunotherapy treatment in NSCLC whereas their role as a prognostic marker is limited.
Method
Seventy-nine FFPE tissues (stage I-IV) during 2012-2017 were retrieved for Next Generation Sequencing (NGS) and immunohistochemistry (IHC) staining. PD-L1 expression was performed using 22C3 Ab. Positive-PD-L1 was defined by tumor proportion score (TPS) >1%. Targeted mutations and fusion genes were analyzed by Lung Cancer Panel 45 Genes and Targeted RNAscan Panel on NGS, respectively. Variants from NGS with coverage of higher than 1000X, cutoff ≥3% alternate variant frequency were considered positive. The cutoff was validated by Real-time PCR. Clinical data correlation was analyzed.
Result
Thirty-one patients (39%) had stage I-II and 48 patients (61%) had stage III-IV disease. Mean age was 62.5 years old. Fifty-one patients (65%) were female and 55 patients (70%) were never-smoker. A majority of the patients (83.6%) were negative-PD-L1. All of the 13 PD-L1 positive patients were in stage III-IV, suggesting the increased likelihood of PD-L1 expression in advanced disease (p = 0.014). No difference in age, sex, smoking status, histological subtypes, and mutational status were seen between PD-L1 positive and negative group.However, PD-L1 negative was associated with a trend toward better survival (Table1). Subgroup analysis in stage IV patients with common EGFR mutations revealed PD-L1 positive status as a significant negative prognostic factor with HR of 3.00 (95% CI: 1.17, 7.73; P-value=0.023), whereas positive-PD-L1 patients with the other mutations showed a trend of worse survival outcome.
Table 1: Cox regression analysis of prognostic factors associated with overall survival of NSCLC patients
ConclusionPrognostic factors
Follow up time
(100 person-month)
Death
Median survival
(mo)
Univariate analysis
Multivariate analysis
No.
Rate (95% CI)
HR (95% CI)
p-value
Adjusted HR (95% CI)
p-value
Age
1.00 (0.98, 1.03)
0.893
-
Sex
0.250
Male
8.71
18
2.07 (1.30, 3.28)
22.8
1.43 (0.79, 2.59)
0.243
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Female
21.14
28
1.32 (0.91, 1.92)
53.9
1
-
PDL1
0.002
Negative (<1%)
28.05
35
1.25 (0.90, 1.74)
53.9
1
1
Positive (≥1%)
1.80
11
6.09 (3.38, 11.00)
7.1
3.52 (1.73, 7.16)
0.001
1.88 (0.83, 4.22)
0.128
Stage
<0.001
I-II
19.20
6
0.31 (0.14, 0.70)
NR
1
1
III-IV
10.65
40
3.76 (2.75, 5.12)
20.1
11.09 (4.26, 28.87)
<0.001
10.03 (3.67, 27.41)
<0.001
Smoking status
0.011
Never smoker
24.04
28
1.16 (0.80, 1.69)
76.2
1
1
Ex-smoker
4.55
10
2.20 (1.18, 4.09)
20.1
1.70 (0.82, 3.52)
0.154
1.02 (0.47, 2.23)
0.962
Current smoker
1.26
8
6.33 (3.17, 12.66)
8.7
3.76 (1.68, 8.41)
0.001
1.70 (0.74, 3.88)
0.208
EGFR
0.825
Mutation
22.99
35
1.52 (1.09, 2.12)
31.9
0.93 (0.47, 1.83)
0.824
-
No mutation
6.87
11
1.60 (0.89, 2.89)
33.5
1
-
ALK
0.869
Positive
2.28
3
1.32 (0.43, 4.09)
NR
1.11 (0.33, 3.78)
0.867
-
Negative
16.50
19
1.15 (0.73, 1.81)
76.2
1
-
KRAS
0.051
Mutation
13.12
12
0.91 (0.52, 1.61)
NR
0.53 (0.27, 1.03)
0.062
-
No mutation
16.73
34
2.03 (1.45, 2.84)
31.1
1
-
Number of co-MT
0.045
< 1000
11.84
27
2.28 (1.56, 3.33)
22.8
1
1
≥ 1000
18.02
19
1.05 (0.67, 1.65)
57.6
0.55 (0.30, 0.99)
0.047
1.22 (0.61, 2.41)
0.574
Positive-PD-L1 is significantly associated with advanced disease and a trend toward unfavorable prognosis. The detrimental effect of PD-L1 is significant in stage IV patients with common EGFR mutations. A confirmatory study with a larger sample size would better identify the prognostic benefit of PD-L1 status in vast subsets.
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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): Songporn Oranratnachai
- 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.
