Virtual Library
Start Your Search
Z. Yuan
Author of
-
+
P1.07 - Immunology and Immunotherapy (ID 693)
- Event: WCLC 2017
- Type: Poster Session with Presenters Present
- Track: Immunology and Immunotherapy
- Presentations: 1
- Moderators:
- Coordinates: 10/16/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)
-
+
P1.07-013 - Detection of Genomic Alterations in Plasma Circulating Tumor DNA in Patients with Metabolically Active Lung Cancers (ID 8853)
09:30 - 09:30 | Author(s): Z. Yuan
- Abstract
Background:
Targeted exome sequencing (TES) using plasma ctDNA has been used in complementing tissue-based genomic assay for matching targeted molecular therapy for individuals with advanced solid tumors. However, concordance varies significantly in reported studies. Unlike tissue-based genomic assays, plasma ctDNA assays are more dependent on viable tumors producing sufficient ctDNA. The objective of this study was to explore successful detection of genomic alterations (GAs) and tumor metabolic activity by FDG PET/CT scan.
Method:
Plasma ctDNA samples extracted from frozen plasma (Group A) or fresh whole blood (Group B) samples were subjected to a 62-gene panel TES assay (FoundationACT™). The fraction of ctDNA in the blood was estimated using the maximum somatic allele frequency (MSAF) for each sample. Tumor load, assessed by RECIST V1.1, and tumor metabolic activity, assessed by SUVmax, were correlated with ctDNA GAs detected by FoundationACT™.
Result:
Patient characteristics are summarized in Table. MSAF was significantly higher in fresh blood than frozen plasma specimens. GAs (≥1) were detected in 50 cases (77%). Various tumor features contributing to undetectable GAs include low tumor burden, indolent growth, and tumor regression. Tumor metabolic activity (i.e., viable tumor burden) measured by SUVmax on FDG-PET scan correlated better with the detection of GAs in plasma ctDNA than tumor radiographic burden measured by RECIST V1.1 on CT scan (Table).
*Other tumor types include lung small cell carcinoma (n=2); Lung large cell neuroendocrine (n=1). *P-values in abstract are calculated using unpaired t-test.FoundationACT Group A (N=14) Group B (N=51) Total (N=65) Specimen Type Frozen plasma Fresh whole blood All samples Volume (mL) ~3.0 8.5 (6.0-11.0) - Age: median (range) 66 (44-74) 68 (50-93) 67 (44-93) Gender: Female (N, %) 7 (50%) 32 (63%) 39 (60%) Race/Ethnicity (N, %) Hispanic 2 (14%) 6 (12%) 8 (12%) Caucasian 10 (71%) 33(65%) 43 (66%) Asian 2 (14%) 10 (20%) 12(18%) African American 0 2(3%) 2 (4%) Histology: Lung adenocarcinoma 3 (21%) 40 (78%) 43 (66%) Lung squamous cell carcinoma 11 (79%) 8 (16%) 19 (29%) Others* 0 3 (6%) 63(5%) GA ≥1 10 (71%) 40 (78%) 50 (77%) MSAF (mean± SD); (GA ≥1 vs GA = 0) 0.122 ±0.250 vs 0.008±0.009 (P=0.185) 0.163±0.256 vs 0.002±0.004 (P=0.0003) 0.155±0.253 vs 0.004±0.006 (P=0.0001) Tumor burden by RECIST V1.1 (GA ≥1 vs GA = 0) (mean ± SD) 7.1±6.2 vs 12.8±7.4 (P=0.182) 10.0±6.2 vs 6.9±3.6 (P=0.145) 9.4±6.2 vs 8.6±5.4 (P=0.682) Tumor metabolic activity by SUVmax (GA ≥1 vs GA = 0) (mean ± SD) 47.6±30.9 vs 39.0±23.2 (P=0. 637) 48.3±30.9 vs 20.2±12.5 (P=0.003) 48.1±30.5 vs 25.6±17.6 (P=0.002)
Conclusion:
Our study supports the clinical utility of plasma ctDNA genomic profiling in patients with metabolically active tumors that are measurable by SUVmax on PET/CT scan. Further study is needed to understand the biology of plasma ctDNA and to optimize imaging tools for quantifying tumor metabolism and guiding clinical use of plasma ctDNA assay.
