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Detection of epidermal growth factor receptor mutations in exhaled breath condensate using droplet digital polymerase chain reaction.

ABSTRACT: The detection of certain oncogenic driver mutations, including those of epidermal growth factor receptor (EGFR), is essential for determining treatment strategies for advanced non-small cell lung cancer (NSCLC). The current study assessed the feasibility of testing exhaled breath condensate (EBC) for EGFR mutations by droplet digital PCR (ddPCR). Samples were collected from 12 patients with NSCLC harboring EGFR mutations that were admitted to Okayama University Hospital between June 1, 2014 and December 31, 2017. A total of 21 EBC samples were collected using the RTube™ method and EGFR mutations (L858R, exon 19 deletions or T790M) were assessed through ddPCR analysis (EBC-ddPCR). A total of 3 healthy volunteer samples were also tested to determine a threshold value for each mutation. Various patient characteristics were determined, including sex (3 males and 9 females), age (range 54-81 years; median, 66 years), smoking history (10 had never smoked; 2 were former smokers), histology (12 patients exhibited adenocarcinoma), clinical stage (9 patients were stage IV; 3 exhibited post-operative recurrence) and EGFR mutation type (4 had L858R; 8 had exon 19 deletions; 8 had T790M). EBC-ddPCR demonstrated positive droplets in 8 of the 12 patients. The sensitivity and specificity of each mutation was as follows: 27.3 and 80.0% for EGFR L858R, 30.0 and 90.9% for EGFR Ex19del, and 22.2 and 100% for EGFR T790M. EBC-ddPCR analysis of EGFR mutations exhibited modest sensitivity and acceptable specificity. EBC-ddPCR is a minimally invasive and replicable procedure and may be a complementary method for EGFR testing in patients where blood or tissue sampling proves difficult.

SUBMITTER: Nishii K

PROVIDER: S-EPMC7656106 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Detection of epidermal growth factor receptor mutations in exhaled breath condensate using droplet digital polymerase chain reaction.

Nishii Kazuya K Ohashi Kadoaki K Tamura Tomoki T Ninomiya Kiichiro K Matsubara Takehiro T Senoo Satoru S Kano Hirohisa H Watanabe Hiromi H Oda Naohiro N Makimoto Go G Higo Hisao H Kato Yuka Y Ninomiya Takashi T Kubo Toshio T Yamamoto Hiromasa H Tomida Shuta S Hotta Katsuyuki K Tabata Masahiro M Toyooka Shinichi S Maeda Yoshinobu Y Kiura Katsuyuki K

Oncology letters 20201029 6

The detection of certain oncogenic driver mutations, including those of epidermal growth factor receptor (<i>EGFR</i>), is essential for determining treatment strategies for advanced non-small cell lung cancer (NSCLC). The current study assessed the feasibility of testing exhaled breath condensate (EBC) for <i>EGFR</i> mutations by droplet digital PCR (ddPCR). Samples were collected from 12 patients with NSCLC harboring EGFR mutations that were admitted to Okayama University Hospital between Jun ...[more]

PMID: 33193853

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Project description:The lung microbiota is commonly sampled using relatively invasive bronchoscopic procedures. Exhaled breath condensate (EBC) collection potentially offers a less invasive alternative for lung microbiota sampling. We compared lung microbiota samples retrieved by protected specimen brushings (PSB) and exhaled breath condensate collection. We also sought to assess whether aerosolized antibiotic treatment would influence the lung microbiota and whether this change could be detected in EBC. EBC was collected from 6 conscious sheep and then from the same anesthetized sheep during mechanical ventilation. Following the latter EBC collection, PSB samples were collected from separate sites within each sheep lung. On the subsequent day, each sheep was then treated with nebulized colistimethate sodium. Two days after nebulization, EBC and PSB samples were again collected. Bacterial DNA was quantified using 16S rRNA gene quantitative PCR. The V2-V3 region of the 16S rRNA gene was amplified by PCR and sequenced using Illumina MiSeq. Quality control and operational taxonomic unit (OTU) clustering were performed with mothur. The EBC samples contained significantly less bacterial DNA than the PSB samples. The EBC samples from anesthetized animals clustered separately by their bacterial community compositions in comparison to the PSB samples, and 37 bacterial OTUs were identified as differentially abundant between the two sample types. Despite only low concentrations of colistin being detected in bronchoalveolar lavage fluid, PSB samples were found to differ by their bacterial compositions before and after colistimethate sodium treatment. Our findings indicate that microbiota in EBC samples and PSB samples are not equivalent.IMPORTANCE Sampling of the lung microbiota usually necessitates performing bronchoscopic procedures that involve a hospital visit for human participants and the use of trained staff. The inconvenience and perceived discomfort of participating in this kind of research may deter healthy volunteers and may not be a safe option for patients with advanced lung disease. This study set out to evaluate a less invasive method for collecting lung microbiota samples by comparing samples taken via protected specimen brushings (PSB) to those taken via exhaled breath condensate (EBC) collection. We found that there was less bacterial DNA in EBC samples compared with that in PSB samples and that there were differences between the bacterial communities in the two sample types. We conclude that while EBC and PSB samples do not produce equivalent microbiota samples, the study of the EBC microbiota may still be of interest.

Project description:Digital PCR in droplets (ddPCR) is an emerging method for more and more applications in DNA (and RNA) analysis. Special requirements when establishing ddPCR for analysis of genetically modified organisms (GMO) in a laboratory include the choice between validated official qPCR methods and the optimization of these assays for a ddPCR format. Differentiation between droplets with positive reaction and negative droplets, that is setting of an appropriate threshold, can be crucial for a correct measurement. This holds true in particular when independent transgene and plant-specific reference gene copy numbers have to be combined to determine the content of GM material in a sample. Droplets which show fluorescent units ranging between those of explicit positive and negative droplets are called 'rain'. Signals of such droplets can hinder analysis and the correct setting of a threshold. In this manuscript, a computer-based algorithm has been carefully designed to evaluate assay performance and facilitate objective criteria for assay optimization. Optimized assays in return minimize the impact of rain on ddPCR analysis. We developed an Excel based 'experience matrix' that reflects the assay parameters of GMO ddPCR tests performed in our laboratory. Parameters considered include singleplex/duplex ddPCR, assay volume, thermal cycler, probe manufacturer, oligonucleotide concentration, annealing/elongation temperature, and a droplet separation evaluation. We additionally propose an objective droplet separation value which is based on both absolute fluorescence signal distance of positive and negative droplet populations and the variation within these droplet populations. The proposed performance classification in the experience matrix can be used for a rating of different assays for the same GMO target, thus enabling employment of the best suited assay parameters. Main optimization parameters include annealing/extension temperature and oligonucleotide concentrations. The droplet separation value allows for easy and reproducible assay performance evaluation. The combination of separation value with the experience matrix simplifies the choice of adequate assay parameters for a given GMO event.

Dataset Information

Detection of epidermal growth factor receptor mutations in exhaled breath condensate using droplet digital polymerase chain reaction.

Publications

Detection of epidermal growth factor receptor mutations in exhaled breath condensate using droplet digital polymerase chain reaction.

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