Epidermal Growth Factor Receptor Genotyping Research Articles

Rapid and reliable testing for clinically actionable EGFR mutations in non-small cell lung cancer using the IdyllaTM platform: a real-world two-center experience in Greece

ABSTRACT Background Limited information exists on epidermal growth factor receptor (EGFR) molecular epidemiology in Greece. Next-generation sequencing (NGS) is the recommended method for EGFR genotyping in NSCLC. The Idylla Biocartis platform is a fully automated system for actionable EGFR mutation detection. Research design and methods We describe the prevalence of EGFR mutations in NSCLC patients in two high-volume clinical centers in Greece and compare key methods used for their determination. Eight hundred and fifty-seven FFPE samples from NSCLC patients were tested for EGFR mutations at University of Crete (UoC; n = 324) and at Evangelismos Hospital, Athens (Evangelismos; n = 503). Results The prevalence of EGFR mutations was 11.1% in the whole cohort (11.5% in non-squamous). The detection rate was 11.0% by NGS, 9.8% by Sanger and 11.3% by Idylla for the whole cohort (12.0% in non-squamous). The agreement between Idylla and Sanger was 93.2%. A targetable EGFR mutation was detected in 10.0% using tissue NGS alone, and in 16.0% using concurrent Idylla ctEGFR testing. Conclusion The frequency of EGFR mutations was as expected for a Caucasian population. The Idylla EGFR test performance is comparable to reference methods and with a shorter TAT. Adding a concurrent plasma Idylla test to tissue NGS testing increases the detection rate of EGFR mutations in NSCLC.

End-to-end Prediction of EGFR Mutation Status with Denseformer.

Accurate genotyping of the epidermal growth factor receptor (EGFR) is critical for the treatment planning of lung adenocarcinoma. Currently, clinical identification of EGFR genotyping highly relies on biopsy and sequence testing which is invasive and complicated. Recent advancements in the integration of computed tomography (CT) imagery with deep learning techniques have yielded a non-invasive and straightforward way for identifying EGFR profiles. However, there are still many limitations for further exploration: 1) most of these methods still require physicians to annotate tumor boundaries, which are time-consuming and prone to subjective errors; 2) most of the existing methods are simply borrowed from computer vision field which does not sufficiently exploit the multi-level features for final prediction. To solve these problems, we propose a Denseformer framework to identify EGFR mutation status in a real end-to-end fashion directly from 3D lung CT images. Specifically, we take the 3D whole-lung CT images as the input of the neural network model without manually labeling the lung nodules. This is inspired by the medical report that the mutational status of EGFR is associated not only with the local tumor nodules but also with the microenvironment surrounded by the whole lung. Besides, we design a novel Denseformer network to fully explore the distinctive information across the different level features. The Denseformer is a novel network architecture that combines the advantages of both convolutional neural network (CNN) and Transformer. Denseformer directly learns from the 3D whole-lung CT images, which preserves the spatial location information in the CT images. To further improve the model performance, we designed a combined Transformer module. This module employs the Transformer Encoder to globally integrate the information of different levels and layers and use them as the basis for the final prediction. The proposed model has been tested on a lung adenocarcinoma dataset collected at the Affiliated Hospital of Zunyi Medical University. Extensive experiments demonstrated the proposed method can effectively extract meaningful features from 3D CT images to make accurate predictions. Compared with other state-of-the-art methods, Denseformer achieves the best performance among current methods using deep learning to predict EGFR mutation status based on a single modality of CT images.

A multi-task deep learning model for EGFR genotyping prediction and GTV segmentation of brain metastasis

BackgroundThe precise prediction of epidermal growth factor receptor (EGFR) mutation status and gross tumor volume (GTV) segmentation are crucial goals in computer-aided lung adenocarcinoma brain metastasis diagnosis. However, these two tasks present continuous difficulties due to the nonuniform intensity distributions, ambiguous boundaries, and variable shapes of brain metastasis (BM) in MR images.The existing approaches for tackling these challenges mainly rely on single-task algorithms, which overlook the interdependence between these two tasks.MethodsTo comprehensively address these challenges, we propose a multi-task deep learning model that simultaneously enables GTV segmentation and EGFR subtype classification. Specifically, a multi-scale self-attention encoder that consists of a convolutional self-attention module is designed to extract the shared spatial and global information for a GTV segmentation decoder and an EGFR genotype classifier. Then, a hybrid CNN-Transformer classifier consisting of a convolutional block and a Transformer block is designed to combine the global and local information. Furthermore, the task correlation and heterogeneity issues are solved with a multi-task loss function, aiming to balance the above two tasks by incorporating segmentation and classification loss functions with learnable weights.ResultsThe experimental results demonstrate that our proposed model achieves excellent performance, surpassing that of single-task learning approaches. Our proposed model achieves a mean Dice score of 0.89 for GTV segmentation and an EGFR genotyping accuracy of 0.88 on an internal testing set, and attains an accuracy of 0.81 in the EGFR genotype prediction task and an average Dice score of 0.85 in the GTV segmentation task on the external testing set. This shows that our proposed method has outstanding performance and generalization.ConclusionWith the introduction of an efficient feature extraction module, a hybrid CNN-Transformer classifier, and a multi-task loss function, the proposed multi-task deep learning network significantly enhances the performance achieved in both GTV segmentation and EGFR genotyping tasks. Thus, the model can serve as a noninvasive tool for facilitating clinical treatment.

A prospective phase 2 study of expeditious EGFR genotyping and immediate therapeutic initiation through extracellular vesicles (EV)-based bronchoalveolar lavage fluid (BALF) liquid biopsy in advanced NSCLC patients.

In our previous study, epidermal growth factor receptor (EGFR) genotyping using extracellular vesicles (EV)-derived DNA isolated from bronchoalveolar lavage fluid (BALF) was proven to be highly concordant with conventional tissue-based genotyping and its turn-around-time (TAT) was only 1-2 days. On this background, we prospectively validated the performance of EV-based BALF liquid biopsy for EGFR genotyping in the real practice of advanced non-small cell lung cancer (NSCLC) patients. After screening 120 newly diagnosed stage III-IV NSCLC patients, 51 cases were detected as EGFR-mutated by EV-based BALF EGFR genotyping and 40 patients were enrolled for gefitinib treatment. BALF EV were isolated by ultracentrifuge method and EGFR genotyping was performed with PCR-based PNA-clamping assisted fluorescence melting curve analysis. The objective response rate, progression-free survival (PFS), TAT, time to treatment initiation (TTI), and concordance rate were analyzed with clinical parameters. There was only one false positive case among the 120 screened patients and the overall concordance rate between tissue biopsy and EV-based BALF liquid biopsy was 99.2% including the subtype of EGFR mutations. TAT for EV-based BALF EGFR genotyping was 1.9±1.1 days, while tissue-based TAT was 12.1±7.2 days (P<0.001). EGFR genotyping was determined even before obtaining histopathologic report in most cases. TTI in BALF EGFR genotyping was faster than tissue genotyping (7.8±6.5 vs. 13.8±12.9 days). Therapeutic outcomes of response rate and PFS were almost similar to tissue-based results. We demonstrated, for the first time, that EV-based BALF liquid biopsy should be an excellent platform for expeditious EGFR genotyping and rapid therapeutic intervention even before obtaining the result of histopathology in advanced NSCLC patients.

Clinical Validation of the Unparalleled Sensitivity of the Novel Allele-Discriminating Priming System Technology-Based EGFR Mutation Assay in Patients with Operable Non-Small Cell Lung Cancer.

Recently, we developed allele-discriminating priming system (ADPS) technology. This method increases the sensitivity of conventional quantitative polymerase chain reaction up to 100 folds, with limit of detection, 0.01%, with reinforced specificity. This prospective study aimed to develop and validate the accuracy of ADPS epidermal growth factor receptor (EGFR) Mutation Test Kit using clinical specimens. In total 189 formalin-fixed paraffin-embedded tumor tissues resected from patients with non-small cell lung cancer were used to perform a comparative evaluation of the ADPS EGFR Mutation Test Kit versus the cobas EGFR Mutation Test v2, which is the current gold standard. When the two methods had inconsistent results, next-generation sequencing-based CancerSCAN was utilized as a referee. The overall agreement of the two methods was 97.4% (93.9%-99.1%); the positive percent agreement, 95.0% (88.7%-98.4%); and the negative percent agreement, 100.0% (95.9%-100.0%). EGFR mutations were detected at a frequency of 50.3% using the ADPS EGFR Mutation Test Kit and 52.9% using the cobas EGFR Mutation Test v2. There were 10 discrepant mutation calls between the two methods. CancerSCAN reproduced eight ADPS results. In two cases, mutant allele fraction was ultra-low at 0.02% and 0.06%, which are significantly below the limit of detection of the cobas assay and CancerSCAN. Based on the EGFR genotyping by ADPS, the treatment options could be switched in five patients. The highly sensitive and specific ADPS EGFR Mutation Test Kit would be useful in detecting the patients who have lung cancer with EGFR mutation, and can benefit from the EGFR targeted therapy.

59P Clinical utility of plasma cell-free DNA EGFR mutation analysis in treatment-naïve stage IV non-small cell lung cancer patients

Plasma cell-free DNA epidermal growth factor receptor (EGFR) mutation tests are widely used at initial diagnosis and at progression in stage IV non-small cell lung cancer (NSCLC). We analyzed the factors associated with plasma EGFR mutation detection and the effect of plasma EGFR genotyping on the clinical outcomes of the patients with treatment-naïve stage IV NSCLC. In this retrospective cohort study, we included subjects with treatment-naïve stage IV NSCLC who underwent plasma EGFR genotyping between 2018 and 2020. The presence of plasma EGFR mutation was determined by real-time polymeric chain reaction. The prevalence of EGFR mutation in this cohort was 52.7% (164/311). Among 164 EGFR mutant subjects, 34 (20.7%) were positive for the plasma EGFR mutation assay only. The diagnostic sensitivity of the plasma EGFR mutation assay (80.5%) was similar to that of the tissue EGFR mutation assay (79.3%, p = 0.787). In multivariable analysis, the detection of plasma EGFR mutation was significantly related to higher serum carcinoembryonic antigen levels, never-smoker status, N3 stage, and brain or intrathoracic metastasis. The time to treatment initiation (TTI) of the plasma EGFR mutation-positive group (14 days) was shorter than that of the plasma EGFR mutation-negative group (21 days, p < 0.001). More patients received the 1st line EGFR-TKI in the plasma positive group compared with the tissue positive group. Smoking status and the factors reflecting tumor burden were associated with detection of plasma EGFR mutation. The plasma EGFR mutation assay can shorten the TTI, and facilitate the 1st line EGFR-TKI therapy for patients with treatment-naïve stage IV NSCLC, especially in the region of high-prevalence of EGFR mutation.

Clinical Utility of Plasma Cell-Free DNA EGFR Mutation Analysis in Treatment-Naïve Stage IV Non-Small Cell Lung Cancer Patients.

Background: Plasma cell-free Deoxyribo nucleic acid epidermal growth factor receptor (EGFR) mutation tests are widely used at initial diagnosis and at progression in stage IV non-small cell lung cancer (NSCLC). We analyzed the factors associated with plasma EGFR mutation detection and the effect of plasma EGFR genotyping on the clinical outcomes of the patients with treatment-naïve stage IV NSCLC. Methods: In this retrospective cohort study, we included subjects with treatment-naïve stage IV NSCLC who underwent plasma EGFR genotyping between 2018 and 2020. The presence of plasma EGFR mutation was determined by real-time polymeric chain reaction. Results: The prevalence of EGFR mutation in this cohort was 52.7% (164/311). Among 164 EGFR mutant subjects, 34 (20.7%) were positive for the plasma EGFR mutation assay only. In multivariable analysis, the detection of plasma EGFR mutation was significantly related to higher serum carcinoembryonic antigen levels, never-smoker status, N3 stage, and brain or intrathoracic metastasis. The time to treatment initiation (TTI) of the plasma EGFR mutation-positive group (14 days) was shorter than that of the plasma EGFR mutation-negative group (21 days, p < 0.001). More patients received the 1st line EGFR-TKI in the plasma positive group compared with the tissue positive group. Conclusion: Smoking status and the factors reflecting tumor burden were associated with the detection of plasma EGFR mutation. The plasma EGFR mutation assay can shorten the TTI, and facilitate the 1st line EGFR-TKI therapy for patients with treatment-naïve stage IV NSCLC, especially in the region of high-prevalence of EGFR mutation.

Contribution of the IdyllaTM System to Improving the Therapeutic Care of Patients with NSCLC through Early Screening of EGFR Mutations.

Epidermal growth factor receptor (EGFR) genotyping, a critical examen for the treatment decisions of patients with non-small cell lung cancer (NSCLC), is commonly assayed by next-generation sequencing (NGS), but this global approach takes time. To determine whether rapid EGFR genotyping tests by the IdyllaTM system guides earlier therapy decisions, EGFR mutations were assayed by both the IdyllaTM system and NGS in 223 patients with NSCLC in a bicentric prospective study. IdyllaTM demonstrated agreement with the NGS method in 187/194 cases (96.4%) and recovered 20 of the 26 (77%) EGFR mutations detected using NGS. Regarding the seven missed EGFR mutations, five were not detected by the IdyllaTM system, one was assayed in a sample with insufficient tumoral cells, and the last was in a sample not validated by the IdyllaTM system (a bone metastasis). IdyllaTM did not detect any false positives. The average time between EGFR genotyping results from IdyllaTM and the NGS method was 9.2 ± 2.2 working days (wd) (12.6 ± 4.0 calendar days (cd)). Subsequently, based on the IdyllaTM method, the timeframe from tumor sampling to the initiation of EGFR-TKI was 7.7 ± 1.2 wd (11.4 ± 3.1 cd), while it was 20.3 ± 6.7 wd (27.2 ± 8.3 cd) with the NGS method (p < 0.001). We thus demonstrated here that the IdyllaTM system contributes to improving the therapeutic care of patients with NSCLC by the early screening of EGFR mutations.

Mutation Spectrum of EGFR From 21,324 Chinese Patients With Non-Small Cell Lung Cancer (NSCLC) Successfully Tested by Multiple Methods in a CAP-Accredited Laboratory.

Genotyping epidermal growth factor receptor (EGFR) gene in patients with advanced non-small cell lung cancers (NSCLC) is essential for identifying those patients who may benefit from targeted therapies. Systemically evaluating EGFR mutation detection rates of different methods currently used in clinical setting will provide valuable information to clinicians and laboratory scientists who take care of NSCLC patients. This study retrospectively reviewed the EGFR data obtained in our laboratory in last 10 years. A total of 21,324 NSCLC cases successfully underwent EGFR genotyping for clinical therapeutic purpose, including 5,244 cases tested by Sanger sequencing, 13,329 cases tested by real-time PCR, and 2,751 tested by next-generation sequencing (NGS). The average EGFR mutation rate was 45.1%, with 40.3% identified by Sanger sequencing, 46.5% by real-time PCR and 47.5% by NGS. Of these cases with EGFR mutations identified, 93.3% of them harbored a single EGFR mutation (92.1% with 19del or L858R, and 7.9% with uncommon mutations) and 6.7% harbored complex EGFR mutations. Of the 72 distinct EGFR variants identified in this study, 15 of them (single or complex EGFR mutations) were newly identified in NSCLC. For these cases with EGFR mutations tested by NGS, 65.3% of them also carried tumor-related variants in some non-EGFR genes and about one third of them were considered candidates of targeted drugs. NGS method showed advantages over Sanger sequencing and real-time PCR not only by providing the highest mutation detection rate of EGFR but also by identifying actionable non-EGFR mutations with targeted drugs in clinical setting.

Mutation spectrum of EGFR in 21,324 patients with non-small cell lung cancer successfully tested by multiple platforms in a CAP-accredited laboratory.

e13637 Background: Genotyping epidermal growth factor receptor ( EGFR) gene in patients with advanced non-small cell lung cancers (NSCLC) is essential to identify those patients who may benefit from targeted treatments. However, the testing methodology is still a puzzle for many clinicians. This study retrospectively reviewed the EGFR data from testing patients with NSCLC in our laboratory in 10 years. Methods: A total of 21,324 NSCLC cases successfully underwent EGFR genotyping in our laboratory for clinical therapeutic purpose, including 5,244 cases tested by Sanger sequencing, 13,329 cases tested by real-time PCR, and 2,751 tested by next generation sequencing-NGS. Results: 54.6%, 20% and 2.3% samples were recorded with tumor cell content (TCC) of &lt; 40%, &lt; 20% and 1% respectively. The average EGFR mutation rate was 45.1%, with 40.3% identified by Sanger sequencing, 46.5% by real-time PCR and 47.5% by NGS. Comparable EGFR mutation rates were observed in cases with 1%-20% TCC from real-time PCR and NGS platforms. In these cases with EGFR mutations, 93.3% of them carried a single EGFR mutation (92.1% with a classical mutation as 19del or L858R, and 7.9% with an uncommon mutation) and 6.7% harbored complex EGFR mutations. 65.3% of the cases carrying EGFR mutations identified by NGS also have tumor related variants in other genes. 26.5% more cases were found to have oncogenic driver mutations with therapeutic significance beyond EGFR by NGS. Conclusions: NGS may be the most optimal methodology to detect EGFR mutations in patients with NSCLC compared with Sanger sequencing and real-time PCR platforms from accuracy and comprehensiveness aspects, but some other issues, such as Turn Around Time (TAT), still should be considered in clinical practice.

A tetrahedral DNA nanostructure-decorated electrochemical platform for simple and ultrasensitive EGFR genotyping of plasma ctDNA.

Genotyping of the epidermal growth factor receptor (EGFR) mutation status is of great importance in the screening of appropriate patients with advanced non-small cell lung carcinoma (NSCLC) to receive superior tyrosine kinase inhibitor (TKIs) therapy. Yet conventional assays are generally costly with a relatively long turnaround time for obtaining results, which can lead to a bottleneck for immediately starting TKI therapy in late-staged patients. In this study, we propose an on-site electrochemical platform for sensitive simultaneous genotyping of the two major EGFR mutations (19del and L858R) through plasma ctDNA based on tetrahedral DNA nanostructure decorated screen-printed electrodes (SPE). Linear-after-the-exponential (LATE)-PCR combined with the amplification refractory mutation system (ARMS) was adopted to produce abundant biotin-labeled single-stranded DNA with high amplification efficiency and specificity. Disposable SPE decorated with self-assembled tetrahedral nanostructured DNA probes that showed ordered orientation and good target accessibility enabled the highly efficient hybridization of the specific amplicons through a sandwich-type and quantitatively translated the interfacial hybridization event into electrochemical signals via enzymatic amplification. Taking advantage of the ARMS-based LATE-PCR and the tetrahedral nanostructure-decorated SPE platform, we achieved the accurate detection of around 30 pg DNA of 19del or L858R, or as low as 0.1% of them in the presence of wild-type DNA. Moreover, the EGFR mutation profiles of 13 NSCLC patients we enlisted were accurately genotyped by our electrochemical platform, the results of which were in good agreement with those of commercial genetic detection methods.

Extracellular vesicle-based EGFR genotyping in bronchoalveolar lavage fluid from treatment-naive non-small cell lung cancer patients.

Extracellular vesicles (EV) have been proven to contain double-stranded DNA reflecting the mutational status of the parental tumor cells in non-small cell lung cancer (NSCLC), which can be translated into clinically useful EV-based liquid biopsy for Epidermal growth factor receptor (EGFR) genotyping using bronchoalveolar lavage fluid (BALF) obtained from tumor site. Patients subjected for an initial lung cancer work-up underwent bronchoscopy and BALF was obtained from tumor site. After isolating EVs from BALF by ultracentrifugation, EV-derived DNA (EV DNA) was extracted for subsequent EGFR genotyping performed through peptide nucleic acid (PNA)-mediated Real-Time PCR. The sensitivity, specificity, and concordance rate of BALF EV-based EGFR genotyping were calculated in comparison to tissue genotyping. The average sensitivity and specificity of BALF EV-based EGFR genotyping were 76% and 87%, respectively, while the sensitivity significantly increased as the stage progressed. Especially, in stage IV, BALF EV-based EGFR typing identified all tissue-proven EGFR mutant cases (n=31) and detected 6 additional mutant cases. The concordance rate was 79% in stage I, 100% in stage II, 74% in stage III, and 92% in stage IV. As TNM stage advanced, especially in the presence of metastasis, concordance rate significantly increased (P<0.05). The use of BALF for the collection of EV DNA in lung cancer patients resulted in a highly accurate diagnosis. The establishment of a fast and reliable method to identify target genes using EV DNA illustrated that it can overcome the problems of low sensitivity and instability in using cell-free DNA (cfDNA).

A comprehensive review of uncommon EGFR mutations in patients with non-small cell lung cancer

IntroductionPatients with non-small cell lung cancer (NSCLC) harboring uncommon epidermal growth factor receptor (EGFR) mutations are a heterogeneous group exhibiting differential responses to EGFR inhibitors. This retrospective study reviews the prevalence of uncommon EGFR mutations in a Chinese NSCLC cohort and the clinical characteristics and efficacy of EGFR tyrosine kinase inhibitors (TKIs) associated with these patients. Materials andMethodsA total of 5363 lung cancer patients were screened and underwent EGFR genotyping at the Guangdong Lung Cancer Institute. Of those with uncommon EGFR mutations, the clinical characteristics and responses to EGFR-TKIs were reviewed retrospectively. ResultsUncommon EGFR mutations were observed in 218 patients, comprising 11.9% of all patients with documented EGFR mutations. More smokers (30.7% vs. 24.3%, P=0.039) and males (54.1% vs. 44.4%, P=0.007) were among the patients with uncommon mutations compared with common mutations. The most frequent uncommon mutations were exon 20 insertions (30.7%, n=67), followed by G719X mutations (21.1%, n=46) and compound L858R mutations (17.0%, n=37). Favorable efficacy was observed in patients harboring compound L858R or G719X mutations, with a median progression-free survival (PFS) of 15.2 (95% CI: 8.7–21.7) or 11.6 (95% CI: 3.6–19.6) months, respectively. The median PFS of those with the T790M mutation or an exon 20 insertion was 1.0 (95% CI: 0.0–2.2) and 3.0 (95% CI: 1.3–4.7) months, respectively. ConclusionThis study reviewed the prevalence of uncommon EGFR mutations and their sensitivity to EGFR-TKIs. Favorable responses were observed in patients with G719X and compound L858R mutations, indicating that they may benefit from EGFR-TKIs as a first-line therapy.

The predictive value of uncommon EGFR mutation in patients with non-small-cell lung cancer.

9028 Background: Non-small-cell lung cancers with uncommon epidermal growth factor receptor ( EGFR) mutations are regarded as a heterogeneous group with variable responses to EGFR-targeted drugs. Here we designed this retrospective study to describe the epidemiology and clinical outcomes of uncommon EGFR mutations in a Chinese cohort of lung cancer patients. Methods: Between June 2007 and June 2014, 5363 lung cancer patients whose EGFR genotyping was performed successfully at Guangdong Lung Cancer Institute (GLCI, Guangzhou, China) were screened. 1837 patients were included in the epidemiological analysis. The clinical outcome was analyzed in 97 advanced-stage patients harboring uncommon EGFR mutations with follow-up data. Results: 218 patients harbored uncommon EGFR mutations, making up 11.9% of all cancers with documented EGFR mutations. Compared with common mutants, those with uncommon mutations were more commonly found in smokers and male patients. The most frequently detected uncommon mutations were exon 20 insertions, G719X mutations and L858R complex mutations, occurring in 30.7%, 21.1% and 17.0% of all EGFR-uncommon-mutation cases. G719X and L858R complex mutations were associated with similar benefit from EGFR-TKI; median PFS was 15.2 (95% CI 8.7-21.7) and 11.6 (95% CI 3.6-19.6) months, respectively. T790M or 20INS was associated with a poorer EGFR-TKI response; median PFS was 1.0 (95% CI 0.0-2.2) and 3.0 (95% CI 1.3-4.7) months, respectively. Of note, two patients with 23% and 65% tumor shrinkages had N771_P772insN and H773_V774insQ, with PFS of 5.7 and 6.1 months respectively. Conclusions: Favorable responses were observed in specific subtypes including complex L858R and G719X, and our results suggested first-line EGFR-TKI should be preferable in such patients.

The role of metabolic tumor volume (MTV) measured by [18F] FDG PET/CT in predicting EGFR gene mutation status in non-small cell lung cancer.

Many noninvasive methods have been explored to determine the mutation status of the epidermal growth factor receptor (EGFR) gene, which is important for individualized treatment of non-small cell lung cancer (NSCLC). We evaluated whether metabolic tumor volume (MTV), a parameter measured by [18F] fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) might help predict EGFR mutation status in NSCLC. Overall, 87 patients who underwent EGFR genotyping and pretreatment PET/CT between January 2013 and September 2016 were reviewed. Clinicopathologic characteristics and metabolic parameters including MTV were evaluated. Univariate and multivariate analyses were used to assess the independent variables that predict mutation status to create prediction models. Forty-one patients (41/87) were identified as having EGFR mutations. The multivariate analysis showed that patients with lower MTV (MTV≤11.0 cm3, p=0.001) who were non-smokers (p=0.037) and had a peripheral tumor location (p=0.033) were more likely to have EGFR mutations. Prediction models using these criteria for EGFR mutation yielded a high AUC (0.805, 95% CI 0.712–0.899), which suggests that the analysis had good discrimination. In conclusion, NSCLC patients with EGFR mutations showed significantly lower MTV than patients with wild-type EGFR. Prediction models based on MTV and clinicopathologic characteristics could provide more information for the identification of EGFR mutations.

Genotyping of EGFR Mutations from Bronchial Cytological Specimens in Slovakian Lung Cancer Patients.

Non-small cell lung cancer (NSCLC) is a histologically and molecularly heterogeneous disease predominating in Slovakia among newly diagnosed oncological disorders and leading in the number of associated deaths. NSCLC diagnostics has advanced especially in molecular typing of epidermal growth factor receptor (EGFR) and subsequent targeted molecular therapy using tyrosine-kinase inhibitor(s) (TKI). The selection of patients for targeted therapy, we describe in this study, is mostly guided through bronchial smears rather than more invasive biopsies. We identified 32 adenocarcinomas, 40 squamous-cell carcinomas, 12 large-cell carcinomas, along with two unspecified carcinomas, in the NSCLC group who had bronchial smears taken. The assessment of tumor cell number, and genomic DNA allowed for screening of clinically relevant somatic EGFR mutations in 86 patients. Using quantitative PCR, 12 patients (14 %) were recommended for EGFR-TKI therapy. The most prevalent EGFR HIT-a in the somatosome, terms introduced and defined in this study, were exon 19 deletions, which were found in combination with the TKI-resistant p.T790M mutation in exon 20 in one patient. The study describes a method that is minimally invasive, reliable, and meets all criteria of routine molecular diagnostics. A multidisciplinary approach of EGFR genotyping from bronchial smears implemented in the study allows expanding targeted molecular therapy in NSCLC patients.

Adequacy of endobronchial ultrasound-guided transbronchial needle aspiration samples processed as histopathological samples for genetic mutation analysis in lung adenocarcinoma.

Phenotyping non-small-cell lung cancer is becoming increasingly important with the advent of molecular testing. Tumours harbouring somatic mutations in the gene that encodes for the tyrosine kinase domain of the epidermal growth factor receptor (EGFR) have been found to increase responsiveness to tyrosine kinase inhibitors. Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is a minimally invasive technique for mediastinal node sampling. The available prospective data on EBUS-TBNA sample suitability for molecular profiling are currently limited. The aim of this prospective study was to evaluate the adequacy of EBUS-TBNA samples for EGFR and anaplastic lymphoma kinase (ALK) genetic mutation analysis in confirmed primary lung adenocarcinomas. We conducted a prospective analysis of 410 consecutive patients referred for EBUS-TBNA between 2010 and 2014. Rapid on-site cytological evaluation was not used. The samples were obtained using 21-gauge (21G) or 22G needles and were prepared as histopathological samples. A total of 91 samples were confirmed as lung adenocarcinomas and 80 of these samples were sent for EGFR mutation analysis. EBUS-TBNA had a diagnostic accuracy of 98.3% for malignancy. EGFR mutation testing was possible in 79/80 cases (98.75%). EGFR mutations were detected in 5/80 (6.3%) samples. ALK gene analysis, which became available during the study period, was requested and successfully performed in 21/21 samples (100%). The total combined genotyping success rate was 100/101 (99.0%). This UK study confirmed the high clinical utility of EBUS-TBNA samples processed as histopathological specimens for EGFR and ALK genotyping in primary lung adenocarcinoma. The needle gauge did not affect genotyping efficacy.

Intratumoral distribution of EGFR mutations and copy number in metastatic lung cancer, what impact on the initial molecular diagnosis?

BackgroundActivating epidermal growth factor receptor (EGFR) mutations characterize a subgroup of non-small-cell lung cancer that benefit from first line EGFR tyrosine kinase inhibitors (EGFR-TKI). However, the existence of polyclonal cell populations may hinder personalized-medicine strategies as patients’ screening often depends upon a single tumor-biopsy sample. The purpose of this study is to clarify and to validate in clinical testing conditions the accuracy of EGFR genotyping using different tumor sites and various types of samples (transthoracic, surgical or endoscopic biopsies and cytology specimens).MethodsWe conducted a retrospective review of 357 consecutive patients addressed for EGFR mutation screening in accordance with the directive of the European Medicines Agency (stage IV NSCLC). Fifty-seven samples were EGFR mutated and 40 had adequate tumor specimens for analysis on multiple spatially separated sites. Ten wild type samples were also analyzed. A total of 153 and 39 tumor fragments, from mutated and non-mutated cases respectively, were generated to analyze tumor heterogeneity or primary-metastatic discordances. After histological review of all fragments, EGFR genotyping was assessed using the routine diagnostic tools: fragment analysis for insertions and deletions and allele specific TaqMan probes for point mutations. EGFR copy number (CN) was evaluated by qPCR using TaqMan probes.ResultsThe identification of EGFR mutations was independent of localization within primary tumor, of specimen type and consistent between primary and metastases. At the opposite, for half of the samples, tumor loci showed different EGFR copy number that may affect mutation detection cut-off.ConclusionsThis is the largest series reporting multiple EGFR testing in Caucasians. It validates the accuracy of EGFR mutation screening from single tumor-biopsy samples before first line EGFR-TKI. The unpredictable variability in EGFR CN and therefore in EGFR wild type/mutant allelic ratio justifies the implementation of sensitive methods to identify patients with EGFR mutated tumors.

A Multicenter Blinded Study Evaluating EGFR and KRAS Mutation Testing Methods in the Clinical Non–Small Cell Lung Cancer Setting—IFCT/ERMETIC2 Project Part 1: Comparison of Testing Methods in 20 French Molecular Genetic National Cancer Institute Platforms

Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors have limited use as first-line treatment for mutated EGFR metastatic non-small cell lung cancer. The French National Cancer Institute has installed molecular genetics platforms implementing EGFR and KRAS testing. However, there is considerable uncertainty as to which detection methods should be applied for routine diagnosis. This study aimed to compare the EGFR and KRAS genotyping methods developed by the IFCT/ERMETIC2 network platforms in two blind panels: 25 samples of serial dilutions of cell line DNA (20 centers) and 74 FFPE lung tumor samples (10 centers). The best threshold of mutation detection on cell lines was obtained using allele-specific amplification-based technologies. Nonamplifiable tissue samples were significantly less common when using alternative testing versus direct sequencing [15%; 95% confidence interval (CI), 14%-16% versus 40%; 95% CI, 39%-42%; P < 0.001]. Mutated cases increased from 42% (95% CI, 31%-54%) to 53% (95% CI, 41%-64%), with three supplementary EGFR mutations (p.G179A at exon 18 and p.L858R and p.L861Q at exon 21) and five supplementary KRAS mutations, when using alternative testing instead of direct sequencing. False-positive results were observed when using a PCR-based sizing assay, high-resolution melting, or pyrosequencing. Concordance analysis returned good kappa test scores for EGFR exon 19 and KRAS analysis when comparing sequencing with alternative methods and revealed no difference between alternative techniques themselves.

Preparation of DNA from cytological material

Personalized oncology requires molecular analysis of tumor cells. Several studies have demonstrated that cytological material is suitable for DNA analysis, but to the authors' knowledge there are no systematic studies comparing how the yield and quality of extracted DNA is affected by the various techniques used for the preparation of cytological material. DNA yield and quality were compared using cultured human lung cancer cells subjected to different preparation techniques used in routine cytology, including fixation, mounting medium, and staining. The results were compared with the outcome of epidermal growth factor receptor (EGFR) genotyping of 66 clinical cytological samples using the same DNA preparation protocol. All tested protocol combinations resulted in fragment lengths of at least 388 base pairs. The mounting agent EcoMount resulted in higher yields than traditional xylene-based medium. Spray and ethanol fixation resulted in both a higher yield and better DNA quality than air drying. In liquid-based cytology (LBC) methods, CytoLyt solution resulted in a 5-fold higher yield than CytoRich Red. Papanicolaou staining provided twice the yield of hematoxylin and eosin staining in both liquid-based preparations. Genotyping outcome and quality control values from the clinical EGFR genotyping demonstrated a sufficient amount and amplifiability of DNA in both spray-fixed and air-dried cytological samples. Reliable clinical genotyping can be performed using all tested methods. However, in the cell line experiments, spray- or ethanol-fixed, Papanicolaou-stained slides provided the best results in terms of yield and fragment length. In LBC, the DNA recovery efficiency of the preserving medium may differ considerably, which should be taken into consideration when introducing LBC. Cancer (Cancer Cytopathol) 2013;121:344-353. © 2013 American Cancer Society.