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V.K. De Sa
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OA 07 - Biomarker for Lung Cancer (ID 659)
- Event: WCLC 2017
- Type: Oral
- Track: Biology/Pathology
- Presentations: 1
- Moderators:Philip Christopher Mack, Shinichi Toyooka
- Coordinates: 10/16/2017, 15:45 - 17:30, Room 503
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OA 07.08 - Clinical Potential of Sputum in Detecting Driver Mutations in Patients with Non-Small Cell Lung Cancer: A Preliminary Study (ID 7540)
17:10 - 17:20 | Author(s): V.K. De Sa
- Abstract
- Presentation
Background:
The incidence of lung cancer has significantly increased over the last century and remains the most common cause of cancer deaths worldwide. Our better understanding of the tumor microenvironment and the systemic actions of tumors, combined with the recent advent of the liquid biopsy, may allow molecular diagnostics to be done with non-invasive method for detection and monitoring of patient tumors. Sputum has been the target for the discovery of non-invasive biomarkers for lung cancer because it contains airway epithelial cells, and molecular alterations identified in sputum are most likely to reflect tumor-associated changes. Since January of 2017, sputum samples have been prospectively collected at the time of diagnosis for future evaluation of actionable mutations in EGFR, KRAS, BRAF and NRAS in patients with non-small cell lung cancer in our center. Currently, from 20 sputum samples already collected, 5 are confirmed for driver mutations (one in KRAS and 4 in EGFR) in tissue biopsy, with 2 of the samples being positive for T790M in circulating tumor DNA (ctDNA) isolated from plasma. Our aim is to evaluate whether sputum may be representative in the detection of these mutations.
Method:
DNA was extracted from sputum using QIAamp DNA midi kit (Qiagen). Tumor somatic mutations were investigated by target-sequencing using a custom Ion Ampliseq™ Panel (ThermoFisher Scientific), containing hotspot regions of 14 genes frequently mutated in solid tumors (including EGFR). Multiplex amplification was performed with 10 ng of DNA using Multiplex PCR Master Mix (Qiagen) and high-throughput sequencing was performed using Ion Proton platform. Somatic mutations were considered if the variant allele was present in more than 0.5% of the reads, considering a minimum coverage depth of 20,000X. A medium coverage of 172,524X was obtained in the five samples.
Result:
We detected mutations in 3 out of 5 sputum samples of patients with previously known driver mutations (two exon 19 deletions and one exon 18 G719A in EGFR). The highest frequency was detected in the only patient with spontaneous sputum collection (23%).The other two mutations were detected in low frequencies (0.5 and 0.6%) in samples derived from sputum induction. We found T790M in one patient positive for T790M in ctDNA isolated from plasma.
Conclusion:
These preliminary findings indicate that driver mutations can be identified in sputum routinely obtained from sputum samples. Thus, the ability to examine sputum might provide a convenient source of sampling and may be adapted for future large-scale screening.
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P3.02 - Biology/Pathology (ID 620)
- Event: WCLC 2017
- Type: Poster Session with Presenters Present
- Track: Biology/Pathology
- Presentations: 1
- Moderators:
- Coordinates: 10/18/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)
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P3.02-060 - EGFR Mutation Status by Three Sequencing Platforms in 704 Non-Small Cell Lung Cancer (NSCLC) Brazilian Patients (ID 10371)
09:30 - 09:30 | Author(s): V.K. De Sa
- Abstract
Background:
EGFR status has utmost importance in treatment of NSCLC with the emergence of highly effective anti-EGFR tyrosine-kinase inhibitors (TKI). Current technologies for EGFR evaluation are based on sequencing platforms, such as Sanger, Pyrosequencing (Pyro) and Next Generation Sequencing (NGS), used in different timeframes during the last 6 years of our local practice. Indirect evidence demonstrates that Latin American patients have higher frequency of EGFR mutations. We aimed to describe EGFR mutation frequency in a Brazilian population and concordance of findings and differences between available sequencing techniques.
Method:
Between August/2010-July/2016 we performed a retrospective analysis of the reports of formalin-fixed paraffin-embedded 704 consecutive biopsy samples from TKI-naïve patients tested for EGFR at A.C.Camargo Cancer Center, São Paulo, Brazil. EGFR exons 18 to 21 were analyzed by Sanger, Pyro or NGS. All tests were performed locally.
Result:
EGFR mutation aggregated rate was 26.7% for the overall population. Table 1 shows patient’s characteristics (when medical records were available) including differences between mutated and non-mutated patients. Table 2 demonstrates differences between mutation findings for each sequencing platform.Table 1. Patient Characteristics. WT: Wild Type. Mut: Mutant.
WT EGFR Mut EGFR P value GENDER Male 223/516 (43.2%) 63/188 (33.5%) Female 293/516 (56.8%) 125/188 (66.5%) <0.001 MEDIAN AGE AT DIAGNOSIS (YEARS) 64 64.8 0.72 HISTOLOGY Adenocarcinoma 367/418 (87.8%) 156/161 (96.9%) Non-Adenocarcinoma NSCLC 51/418 (12.2%) 5/161 (3.1%) 0.01 SMOKING STATUS Nonsmoker 81/308 (26.3%) 52/128 (40.6%) Smoker/Former Smoker 227/308 (73.7%) 76/128 (59.4%) < 0.001 MEDIAN SMOKING LOAD (PACK-YEARS) 40 17.5 < 0.001 METASTASIS AT DIAGNOSIS Yes 238/333 (71.5%) 105/137 (76.6%) No 95/333 (28.5%) 32/137 (23.4%) 0.25 Table 2 – Numbers and types of mutations detected according to the test methodology.
Sanger Pyro NGS Aggregated EGFR Mutant Patients 82/352 (23.3%) 27/101 (26.7%) 79/251 (31.5%) 188/704 (26.7%) Total Number of EGFR Variants Detected* 93 28 84 205 Patients with Multiple EGFR Variants 8/82 (9.8%) 1/27 (3.7%) 5/79 (6.3%) 14/188 (7.4%) Sensitivity Variants 69/93 (74.5%) 26/28 (92.9%) 71/84 (84.5%) 166/205 (81%) Resistance Variants 3/93 (3.2%) 0 6/84 (7.1%) 9/205 (4.4%) Variants of Uncertain Significance 21/93 (22.6%) 2/28 (7.1%) 7/84 (8.3%) 30/205 (14.6%) Inconclusive test 60/352 (17%) 4/101 (4%) 5/251 (2%) 69/704 (9.8%)
Conclusion:
Our findings demonstrate higher than expected EGFR mutation rate among for caucasian patients in a Brazilian population and a numerically higher and broader EGFR mutation detection rate with NGS.
