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Narumol Trachu



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    P2.01 - Advanced NSCLC (Not CME Accredited Session) (ID 950)

    • Event: WCLC 2018
    • Type: Poster Viewing in the Exhibit Hall
    • Track:
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/25/2018, 16:45 - 18:00, Exhibit Hall
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      P2.01-90 - PD-L1 Expression as a Predictive Biomarker in Advanced Non-Small Cell Lung Cancer Patients with or without EGFR Mutation (ID 13528)

      16:45 - 18:00  |  Author(s): Narumol Trachu

      • Abstract
      • Slides

      Background

      The prognostic value of PD-L1 expression and its clinical relevance of NSCLC is controversy. The impact of PD-L1 expression as the predictive biomarker for EGFR-TKIs treatment is needed to explore.

      a9ded1e5ce5d75814730bb4caaf49419 Method

      Medical records of metastatic NSCLC during September 2015-2016 had been reviewed. PD-L1 immunohistochemistry (IHC) staining with Antibody clone 22C3 was used. The PD-L1 positive was defined by tumor proportion score (TPS) > 1%.

      4c3880bb027f159e801041b1021e88e8 Result

      204 patients were included. Patients with positive PD-L1 expression had significantly increased numbers of metastatic sites (P=0.009) and lung metastasis (P=0.045) compared to PD-L1 negative patients. Overall survival (OS) was longer in PD-L1 negative patients (22.7 months) compared to PD-L1 positive groups (13.6 months) (HR=1.48; P=0.03). Median OS were significantly different with the number of 7.2, 11.1, 25.7, 42.6 months in EGFR-/PD-L1+, EGFR-/PD-L1-, EGFR+/PD-L1+ and EGFR+/PD-L1- , respectively (P<0.001). Among EGFR positive patients, mOS of T790M-/PD-L1+, T790M-/PD-L1-, T790M+/PD-L1-, and T790M+/PD-L1+ were 22.1, 28, 42.6 and 48.4 months, respectively (P=0.03).

      Patient characteristics categorized by PD-L1 expression (N = 204)
      Characteristics

      PD-L1 Negative

      N=134 (65.69%)

      PD-L1 Positive

      N=70 (34.31%)

      P value

      Age

      - Median age (range)

      - < 65 years

      - > 65 years

      65 (36-85)

      64 (47.76)

      70 (52.24)

      65 (35-86)

      33 (47.14

      37 (52.86)

      0.933

      Sex

      - Male

      - Female

      62 (46.27)

      72 )53.73)

      37 (52.86)

      33 (47.14)

      0.371

      ECOG PS

      - 0-1

      - > 2

      116 (86.57)

      18 (13.43)

      57 (82.61

      12 (17.39)

      0.452

      Smoking status

      - Never

      - Ex-smoker

      - Current smoker

      82 (61.65)

      36 (27.07)

      15 (11.28)

      36 (52.17)

      18 (26.09)

      15 (21.74)

      0.131
      Mean smoking pack-year (range) 29.72 (2-100) 25.68 (2-40) 0.873

      Initial staging

      - Recurrent

      - Denovo metastasis

      32 (23.88)

      102 (76.12)

      14 (20)

      56 (80)

      0.529

      Histology

      - Adenocarcinoma

      - Squamous cell carcinoma

      - Adenosquamous carcinoma

      - Others

      117 (87.31)

      1 (0.75)

      2 (1.49)

      14 (10.45)

      58 (84.06)

      3 (4.35)

      2 (2.9)

      6 (8.7)

      0.288

      EGFR mutation

      - Negative

      - Positive

      47 (35.07)

      87 (64.93)

      32 (45.71)

      38 (54.29)

      0.092

      Exon 19 deletion

      - No

      - Yes

      87 (64.93)

      47 (35.07)

      50 (71.43)

      20 (28.57)

      0.348

      L858R

      - No

      - Yes

      100 (74.63)

      34 (25.37)

      53 (75.71)

      17 (24.29)

      0.865

      ALK results

      - Negative

      - Positive

      79 (92.94)

      6 (7.06)

      47 (97.92)

      1 (2.08)

      0.421

      Number of site of metastasis

      - 0-1

      - > 2

      88 (65.67)

      46 (34.33)

      37 (52.86)

      33 (47.14)

      0.009

      Lung metastasis

      - No

      - Yes

      92 (69.17)

      41 (30.83)

      38 (54.29)

      32 (45.71)

      0.045

      Bone metastasis

      - No

      - Yes

      101 (75.37)

      33 (24.63)

      53 (75.71)

      17 (24.29)

      0.957

      Liver metastasis

      - No

      - Yes

      122 (91.04)

      12 (8.96)

      62 (88.57)

      8 (11.43)

      0.573

      Pleural metastasis

      - No

      - Yes

      91 (67.91)

      43 (32.09)

      62 (88.57)

      20 (28.57)

      0.606

      Brain metastasis

      - No

      - Yes

      117 (87.31)

      17 (12.69)

      58 (82.86)

      12 (17.14)

      0.387

      Adrenal metastasis

      - No

      - Yes

      122 (91.04)

      12 (8.96)

      62 (88.57)

      8 (11.43)

      0.573

      figure pd-l1.jpg

      8eea62084ca7e541d918e823422bd82e Conclusion

      PD-L1 expression was associated with poorer survival outcomes among advanced NSCLC patients regardless of EGFR mutation status. PD-L1 expression is also the potential of predictive biomarker for EGFR TKIs treatment. The larger studies are needed to identify the prognostic and predictive values in T790M mutation population.

      6f8b794f3246b0c1e1780bb4d4d5dc53

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    P3.09 - Pathology (Not CME Accredited Session) (ID 975)

    • Event: WCLC 2018
    • Type: Poster Viewing in the Exhibit Hall
    • Track:
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/26/2018, 12:00 - 13:30, Exhibit Hall
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      P3.09-10 - Circulating Cell-Free DNA (cfDNA) Molecular Profile of Thai NSCLC Patients Using Difference Variant Frequency of NGS (ID 13744)

      12:00 - 13:30  |  Author(s): Narumol Trachu

      • Abstract
      • Slides

      Background

      Detecting cfDNA in the liquid biopsy has become a promising method to explore the genetic landscape of tumor heterogeneity. We developed a pilot-study to find the suitable cutoff of variant frequencies detected from liquid biopsy by NGS to track tumor-associated mutations in NSCLC patients.

      a9ded1e5ce5d75814730bb4caaf49419 Method

      Ninety-four samples (24 early-stage NSCLC, 70 late-stage NSCLC) were collected from Ramathibodi Hospital, Thailand. Profiling cfDNA using Ion Proton NGS platform. Overall average base coverage depth from NGS was 10,000x, all variants selected have read depths >10x in order to reach 0.1% sensitivity. Each of selected variants has threshold variant quality (QUAL) >20. Droplet digital PCR (ddPCR) was performed for EGFR-mutation testing to determine the appropriated cutoff variant frequency from NGS.

      4c3880bb027f159e801041b1021e88e8 Result

      In early-stage NSCLC, a minimum-threshold variant frequencies at 0.1% could detect EGFR exon19 deletion in all samples (24,100%), with BRAF (12,50%), KRAS (21,87.5%) and other mutations in AKT1, MET, PIK3CA, PTEN, ROS1 (14,58%). None of these mutations identified when using conventional level cutoff at 3% (Table1). ddPCR observed EGFR-mutations in 2 early-stage cases only (8.3%). In late-stage NSCLC, 64 (91.4%) cases were observed multiple mutations, suggesting tumor heterogeneity. At 0.1% cutoff in NGS, Thirty-six (52.9%) cases of EGFR-mutations in NGS and ddPCR were identical. Thirteen (18.6%) samples shown partial discrepancies in the mutations. Interestingly, NGS found EGFR-mutations in 20 (28.6%) samples which ddPCR failed to detect, 12 of them contained T790M. Only one sample (1.4%) using 0.1% cutoff was unable to detect EGFR-mutation. Higher variant allele frequencies were found in EGFR-positive detected by ddPCR compared to not-detected by ddPCR.

      Table1
      Mutations detected variant allele frequencies detected from liquid biopsy by NGS at minimum threshold cut-off 0.1% variant allele frequencies detected from liquid biopsy by NGS at minimum threshold cut-off 0.1% variant allele frequencies detected from liquid biopsy by NGS at conventional level detection of somatic variants cut-off 3% variant allele frequencies detected from liquid biopsy by NGS at conventional level detection of somatic variants cut-off 3% variant allele frequencies detected from liquid biopsy by ddPCR (EGFR only) variant allele frequencies detected from liquid biopsy by ddPCR (EGFR only)
      N (%) median (range) N (%) median (range) N (%) median (range)
      BRAF (V600E) early stage total N=24 12 (50%) 0.8 (0.3-2.5) 0 (0%) 0 NA NA
      BRAF (V600E) late stage total N=70 11 (15.7%) 0.6 (0.1-1.1) 0 (0%) 0 NA NA
      KRAS early stage 21 (87.5%) 0.1 (0.1-0.5) 0 (0%) 0 NA NA
      KRAS late stage 50 (71.4%)

      0.2

      (0.1-13.6)

      3 (4.3%) 11.1 (5.8-14.3) NA NA
      AKT1 (E17K) early stage 7 (29.2%) 0.1 (0.1-0.7) 0 (0%) 0 NA NA
      AKT1 (E17K) late stage 12 (17.1%) 0.1 (0.1-0.7) 0 (0%) 0 NA NA
      MET exon 14 splicing early stage

      4 (16.7%)

      0.1 (0.1-0.1) 0 (0%) 0 NA NA
      MET exon 14 splicing late stage 3 (4.3%) 0.2 (0.2-0.2) 0 (0%) 0 NA NA
      PIK3CA early stage 9 (37.5%) 0.2 (0.1-0.8) 0 (0%) 0 NA NA
      PIK3CA late stage 19 (27.1%) 0.3 (0.1-0.7) 0 (0%) 0 NA NA
      PTEN (R233*) early stage 6 (25.0%) 0.1 (0.1-0.4) 0 (0%) 0 NA NA
      PTEN (R233*) late stage 11 (15.7%) 0.1 (0.1-0.2) 0 (0%) 0 NA NA

      ROS1

      early stage 0 (0%) 0 0 (0%) 0 NA NA

      ROS1

      late stage 4 (5.7%)

      0.55

      (0.1-0.7)

      0 (0%) 0 NA NA

      EGFR

      Exon 19 Deletion

      early stage 24 (100%)

      0.35

      (0.1-2.1)

      0 (0%) 0 1 (4.2%) 0.5 (0.5-0.5)

      EGFR

      Exon 19 Deletion

      late stage 25 (35.7%)

      0.6

      (0.1-49.0)

      6 (8.6%) 9.4 (4.5-49.5) 20 (28.6%) 0.65 (0-49.0)
      EGFR L858R early stage 5 (20.8%) 0.2 (0.1-0.5) 0 (0%) 0 0 (0%) 0
      EGFR L858R late stage 21 (30%) 1.4 (0.1-9.7) 4 (5.7%) 4.6 (4.4-6.4) 14 (20%) 1.8 (0.3-9.7)
      EGFR T790M early stage 8 (33.3%) 0.1 (0.1-0.2) 0 (0%) 0 0 (0%) 0
      EGFR T790M late stage 30 (42.9%) 0.1 (0.1-4.6) 2 (2.9%) 7.5 (5.3-9.7) 16 (22.9%) 0.15 (0-4.1)
      EGFR Exon18 (G719X) early stage 6 (25%) 0.2 (0.1-0.4) 0 (0%) 0 1 (4.2%) 0.4 (0.4-0.4)
      EGFR Exon18 (G719X) late stage 4 (5.7%)

      4.5

      (0.1-49.2)

      2 (2.9%)

      27.9

      (6.7-49.2)

      2 (2.9%) 25.6 (2-49.2)
      EGFR Exon 20 Insertion early stage 0 (0%) 0 0 (0%) 0 0 (0%) 0
      EGFR Exon 20 Insertion late stage 1 (1.4%)

      73.8

      (73.8-73.8)

      1 (1.4%)

      91.7

      (91.7-91.7)

      0 (0%) 0

      8eea62084ca7e541d918e823422bd82e Conclusion

      Detecting variant frequencies at 0.1% could reveal more hidden tumor-associated mutations compared to variant frequency cutoff at 3%. With a careful validation, profiling cfDNA using NGS can be a crucial method to accurately select treatment for NSCLC patients in the future.

      6f8b794f3246b0c1e1780bb4d4d5dc53

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