Bronchial Genomic Classifier Research Articles

Comparing modalities for risk assessment in patients with pulmonary lesions and nondiagnostic bronchoscopy for suspected lung cancer

BackgroundBronchoscopy is commonly utilized for non-surgical sampling of indeterminant pulmonary lesions, but nondiagnostic procedures are common. Accurate assessment of the risk of malignancy is essential for decision making in these patients, yet we lack tools that perform well across this heterogeneous group of patients. We sought to evaluate the accuracy of three previously validated risk models and physician-assessed risk (PAR) in patients with a newly identified lung lesion undergoing bronchoscopy for suspected lung cancer where the result is nondiagnostic.MethodsWe performed an analysis of prospective data collected for the Percepta Bronchial Genomic Classifier Multicenter Registry. PAR and three previously validated risk models (Mayo Clinic, Veteran’s Affairs, and Brock) were used to determine the probability of lung cancer (low, intermediate, or high) in 375 patients with pulmonary lesions who underwent bronchoscopy for possible lung cancer with nondiagnostic pathology. Results were compared to the actual adjudicated prevalence of malignancy in each pre-test risk group, determined with a minimum of 12 months follow up after bronchoscopy.ResultsPAR and the risk models performed poorly overall in the assessment of risk in this patient population. PAR most closely matched the observed prevalence of malignancy in patients at 12 months after bronchoscopy, but all modalities had a low area under the curve, and in all clinical models more than half of all the lesions labeled as high risk were truly or likely benign. The studied risk model calculators overestimate the risk of malignancy compared to PAR, particularly in the subset in older patients, irregularly bordered nodules, and masses > 3 cm. Overall, the risk models perform only slightly better when confined to lung nodules < 3 cm in this population.ConclusionThe currently available tools for the assessment of risk of malignancy perform suboptimally in patients with nondiagnostic findings following a bronchoscopic evaluation for lung cancer. More accurate and objective tools for risk assessment are needed.Trial registration:not applicable.

ROLE OF NEXT GENERATION SEQUENCING WITH PERCEPTA BRUSHING IN RECLAFFYING LUNG NODULE RISK AFTER A NON-DIAGNSOTIC BRONCHOSCOPY

TOPIC: Lung Cancer TYPE: Original Investigations PURPOSE: Lung cancer is most common cancer in the world and the most common cause of death from cancer in the United States. With the recent expansion of eligibility for lung cancer screening and expanded acceptance of screening, we are likely to see a growing number of patients with pulmonary nodules. Current ACCP Guidelines recommend non-surgical biopsy for nodule with a risk of malignancy between 5% and 65%, however up to 60% of lung cancer bronchoscopy results are inconclusive. Percepta Genomic Sequencing Classifier (GSC) is an RNA-seq based genomic classifier using cells from a bronchial brushing of benign mucosa to assess risk of lung cancer in a lung nodule in a patient with a history of smoking when the bronchoscopy is inconclusive. The test can reclassify risk. From a pre-bronch intermediate risk, GSC can up-classify to high risk with a 65% PPV or down-classify to low risk with a 91% NPV. We sought to identify the frequency with which Percepta GSC helps to reclassify malignancy risk in intermediate risk nodules to guide further decision-making. METHODS: This was a retrospective review of all inconclusive bronchoscopies in ever smokers with a lung nodule from January 2019 to October 2020 . All nodules were intermediate risk determined by physician-assessed risk (PAR). Right mainstem bronchial brushings for Percepta GSC had been performed in all cases, with the genomic classifier analysis initiated at the time of the non-diagnostic result. The frequency of up and down classification was analyzed. RESULTS: Out of 30 patients classified as intermediate per PAR, 13 (43.3%) patients had an Intermediate GSC result. 8 (26.6%) patients were re-classified with a High GSC result. 9 (30.0%) patients were re-classified with a Low GSC result. In total, in 17 of 30 (56.6%) of patients with a non-diagnostic bronchoscopy, the classifier provided new information to guide further decision-making. For the patients with a Low GSC result, we observed a significant reduction in additional invasive procedures compared to the pre-test management plan. It is interesting to note that out of 9 patient that got reclassified in low category, 1 patient lost to follow up. Seven patients had at least 12 months follow up on their ct chest with nodule size remaining stable. Interestingly one patient on biopsy showed granulomas with culture growing aspergillus and patient treated with voriconazole which resulted in resolution of nodule. CONCLUSIONS: Within this group of patients with a PAR of Intermediate, Percepta GSC provided additional information in the majority of cases where bronchoscopy was non-diagnostic and has helped our lung nodule work up algorithm. Down classification allowed for consideration of deferring CT-guided fine needle aspiration or surgical lung biopsy and pursuing a plan of CT surveillance, helping to avoid unnecessary procedures. Patients with Intermediate results proceeded on the standard diagnostic pathway, and patients re-classified as high risk were considered for more aggressive evaluation to avoid missing a false negative bronchoscopy result. CLINICAL IMPLICATIONS: Bronchoscopy is frequently used for evaluation of pulmonary lesions, but its sensitivity for detecting lung cancer can be limited. Use of the Percepta GSC bronchial genomic classifier can provide additional information when bronchoscopy is inconclusive, with a high NPV for a Low result and a high PPV for a High result, helping to guide decision making. DISCLOSURES: No relevant relationships by Sonya Bracone, source=Web Response No relevant relationships by Abhijit Raval, source=Web Response No relevant relationships by Ashka Raval, source=Web Response

Improving lung cancer risk stratification leveraging whole transcriptome RNA sequencing and machine learning across multiple cohorts

BackgroundBronchoscopy for suspected lung cancer has low diagnostic sensitivity, rendering many inconclusive results. The Bronchial Genomic Classifier (BGC) was developed to help with patient management by identifying those with low risk of lung cancer when bronchoscopy is inconclusive. The BGC was trained and validated on patients in the Airway Epithelial Gene Expression in the Diagnosis of Lung Cancer (AEGIS) trials. A modern patient cohort, the BGC Registry, showed differences in key clinical factors from the AEGIS cohorts, with less smoking history, smaller nodules and older age. Additionally, we discovered interfering factors (inhaled medication and sample collection timing) that impacted gene expressions and potentially disguised genomic cancer signals.MethodsIn this study, we leveraged multiple cohorts and next generation sequencing technology to develop a robust Genomic Sequencing Classifier (GSC). To address demographic composition shift and interfering factors, we synergized three algorithmic strategies: 1) ensemble of clinical dominant and genomic dominant models; 2) development of hierarchical regression models where the main effects from clinical variables were regressed out prior to the genomic impact being fitted in the model; and 3) targeted placement of genomic and clinical interaction terms to stabilize the effect of interfering factors. The final GSC model uses 1232 genes and four clinical covariates – age, pack-years, inhaled medication use, and specimen collection timing.ResultsIn the validation set (N = 412), the GSC down-classified low and intermediate pre-test risk subjects to very low and low post-test risk with a specificity of 45% (95% CI 37–53%) and a sensitivity of 91% (95%CI 81–97%), resulting in a negative predictive value of 95% (95% CI 89–98%). Twelve percent of intermediate pre-test risk subjects were up-classified to high post-test risk with a positive predictive value of 65% (95%CI 44–82%), and 27% of high pre-test risk subjects were up-classified to very high post-test risk with a positive predictive value of 91% (95% CI 78–97%).ConclusionsThe GSC overcame the impact of interfering factors and achieved consistent performance across multiple cohorts. It demonstrated diagnostic accuracy in both down- and up-classification of cancer risk, providing physicians actionable information for many patients with inconclusive bronchoscopy.

IMPROVING INDETERMINANT PULMONARY NODULE MANAGEMENT WITH THE PERCEPTA GENOMIC SEQUENCING CLASSIFIER

SESSION TITLE: Late Breaking Abstracts SESSION TYPE: Original Investigations PRESENTED ON: 10/23/2019 10:45 AM - 11:45 AM PURPOSE: Guidelines recommend patients with intermediate-risk nodules undergo bronchoscopic workup, yet the diagnostic yield is only around 50%, underscoring the need for additional tools to inform patient management. We previously established the clinical accuracy of Percepta Bronchial Genomic Classifier, a molecular test that utilizes a brushing of bronchial epithelium to improve nodule management in smokers. We have since developed the second-generation Percepta Genomic Sequencing Classifier (GSC), which utilizes 1232 gene transcripts from whole-transcriptome RNA sequencing, as well as clinical factors, to achieve improved performance. Here we report the clinical validation and demonstrate improvement for nodule diagnosis. METHODS: We utilized over 1600 patient samples to train the new Percepta GSC, which is an ensemble of four machine-learning models that incorporate genomic and clinical features as well as their interactions. We established diagnostic accuracy on an independent validation set consisting of 412 patient samples from three cohorts: AEGIS I and II (246 patients) and the Percepta Registry (166 patients)—all with nondiagnostic lung nodules from bronchoscopy. We measured positive predictive value (PPV) and negative predictive value (NPV) of Percepta GSC results in physician-reported pre-test risk categories of low, intermediate or high risk. In AEGIS I/II cohorts, where patients with diagnostic bronchoscopy results are available, we calculated the sensitivities of bronchoscopy and Percepta GSC alone, as well as in combination. RESULTS: In the validation set, 80 patients (19%) had a low pre-test risk (cancer prevalence 5.0%), 188 (35%) had an intermediate pre-test risk (cancer prevalence 28.2%), and 144 (46%) had a high pre-test risk (cancer prevalence 73.6%). Percepta GSC down-classified patients with low pre-test risk with >99% NPV and intermediate pre-test risk with a 91.0% NPV. In addition, the classifier up-classified patients with intermediate pre-test risk with a 65.4% PPV and high pre-test risk with a 91.5% PPV. In total, 41.6% of intermediate pre-test risk patients were either down- or up-classified by the test. In the AEGIS cohorts, the sensitivity among low and intermediate pre-test risk patients was: 40.9% (bronchoscopy alone), 92.3% (Percepta GSC alone), and 95.5% (combined). CONCLUSIONS: Percepta GSC is clinically validated to accurately up-classify and down-classify the probability of malignancy for a substantial portion of lung nodule patients with nondiagnostic bronchoscopy. Percepta GSC significantly improves the sensitivity of bronchoscopy overall and demonstrates a combined 95%+ sensitivity for low/intermediate pre-test risk groups. CLINICAL IMPLICATIONS: Percepta GSC compliments bronchoscopy and when used together can enable improved management of pulmonary nodules. DISCLOSURES: No relevant relationships by Christina Bellinger, source=Web Response No relevant relationships by Michael Bernstein, source=Web Response Employee relationship with Veracyte, Inc Please note: >$100000 Added 06/22/2019 by Sangeeta Bhorade, source=Web Response, value=Salary Employee relationship with Veracyte Inc Please note: >$100000 Added 03/21/2019 by Yoonha Choi, source=Web Response, value=Salary Removed 03/21/2019 by Yoonha Choi, source=Web Response Employee relationship with Veracyte Inc Please note: >$100000 Added 03/21/2019 by Yoonha Choi, source=Web Response, value=Salary No relevant relationships by Travis Dotson, source=Web Response Consultant relationship with AstraZeneca Please note: $5001 - $20000 Added 11/29/2018 by David Feller-Kopman, source=Web Response, value=Consulting fee Consultant relationship with Veracyte Please note: $5001 - $20000 Added 11/29/2018 by David Feller-Kopman, source=Web Response, value=Consulting fee Consultant relationship with Veran Medical Please note: $5001 - $20000 Added 11/29/2018 by David Feller-Kopman, source=Web Response, value=Consulting fee Employee relationship with Veracyte Inc Please note: >$100000 Added 03/15/2019 by Jing Huang, source=Web Response, value=Salary no disclosure on file for Giulia Kennedy; Consultant relationship with Veracyte Please note: $5001 - $20000 Added 03/18/2019 by Hans Lee, source=Web Response, value=Consulting fee Consultant relationship with Veran medical Please note: $5001 - $20000 Added 03/18/2019 by Hans Lee, source=Web Response, value=Consulting fee Employee relationship with Veracyte Please note: >$100000 Added 03/15/2019 by Lori Lofaro, source=Web Response, value=Salary Advisory Committee Member relationship with Grail Please note: $1-$1000 Added 06/22/2019 by Peter Mazzone, source=Web Response, value=Consulting fee Consultant relationship with SEER Please note: $1-$1000 Added 06/22/2019 by Peter Mazzone, source=Web Response, value=Consulting fee Research support to my institution relationship with Veracyte Please note: $5001 - $20000 Added 06/22/2019 by Peter Mazzone, source=Web Response, value=Grant/Research Support Research support to my institution relationship with Oncocyte Please note: $5001 - $20000 Added 06/22/2019 by Peter Mazzone, source=Web Response, value=Grant/Research Support Research support to my institution relationship with Exact Sciences Please note: $1001 - $5000 Added 06/22/2019 by Peter Mazzone, source=Web Response, value=Grant/Research Support Employee relationship with Veracyte Please note: >$100000 Added 03/18/2019 by Daniel Pankratz, source=Web Response, value=Salary No relevant relationships by Momen Wahidi, source=Web Response Employee relationship with Veracyte Please note: >$100000 Added 03/18/2019 by Patric Walsh, source=Web Response, value=Salary

OUTCOMES OF ATYPICAL CELLS ON BRONCHOSCOPY FOR MALIGNANCY

SESSION TITLE: Wednesday Electronic Posters 3 SESSION TYPE: Original Inv Poster Discussion PRESENTED ON: 10/23/2019 09:45 AM - 10:45 AM PURPOSE: Inconclusive bronchoscopy results occur approximately 40-60% for the evaluation of pulmonary nodules. Very little has been reported on the outcomes of inconclusive bronchoscopy and even less on atypical cell results leaving clinicians in a potential clinical dilemma. It is unclear what the risk of malignancy with atypical cell results is after bronchoscopy. METHODS: A retrospective review of cases with atypical cells from an inconclusive bronchoscopy was examined from the Percepta bronchial genomic classifier multi-center registry. The registry examined inconclusive bronchoscopy results for the evaluation of pulmonary nodules. We collected data on demographics, radiographic characteristics, and pre-test risk assessment for malignancy. All patients had a minimum of 12 month follow-up and adjudication of pathology and imaging. RESULTS: 520 patients enrolled in the PERCEPTA registry with an inconclusive bronchoscopy. 58 (11%) cases were identified with atypical cells on cytology across 18 different medical centers. Of the 58 cases, 17 patients were removed due to lack of follow-up or ineligible for adjudication. Overall, there was a 76% rate of malignancy (OR 5.6, CI 1.19-26.58). In the high risk group (n=18), 94% were eventually found to have malignancy (OR 10.9, CI 1.23-97.04). 62% in the intermediate group (n=35) had malignancy. The low risk group (n=2), 50% had malignancy. CONCLUSIONS: Atypical cells on bronchoscopy may increase the post-test risk of malignancy especially in the high risk group. CLINICAL IMPLICATIONS: Atypical cells on bronchoscopy has not been examined in the United States to our knowledge. Our cohort reports 11% prevalence in a multi-center registry. The findings of atypical cells increases the risk of malignancy especially in the high risk group where it is 94%, consideration should be made to forego additional diagnostic testing if surgery or curative radiation is a potential option. DISCLOSURES: No relevant relationships by Alexa Barriere, source=Web Response Consultant relationship with AstraZeneca Please note: $5001 - $20000 Added 11/29/2018 by David Feller-Kopman, source=Web Response, value=Consulting fee Consultant relationship with Veracyte Please note: $5001 - $20000 Added 11/29/2018 by David Feller-Kopman, source=Web Response, value=Consulting fee Consultant relationship with Veran Medical Please note: $5001 - $20000 Added 11/29/2018 by David Feller-Kopman, source=Web Response, value=Consulting fee Employee relationship with Veracyte, Inc. Please note: $20001 - $100000 Added 03/15/2019 by Bailey Griscom, source=Web Response, value=Salary Consultant relationship with Veracyte Please note: $5001 - $20000 Added 03/18/2019 by Hans Lee, source=Web Response, value=Consulting fee Consultant relationship with Veran medical Please note: $5001 - $20000 Added 03/18/2019 by Hans Lee, source=Web Response, value=Consulting fee Employee relationship with Veracyte Please note: >$100000 Added 03/15/2019 by Lori Lofaro, source=Web Response, value=Salary No relevant relationships by Christopher Mallow, source=Web Response No relevant relationships by Majid Shafiq, source=Web Response No relevant relationships by Jeffrey Thiboutot, source=Web Response Consultant relationship with Veran Please note: >$100000 Added 11/29/2018 by Lonny Yarmus, source=Web Response, value=Grant/Research Support Research relationship with Rocket Medical Please note: $20001 - $100000 Added 06/20/2019 by Lonny Yarmus, source=Web Response, value=Grant/Research

Prospective Utility of a Bronchial Genomic Classifier for Lung Cancer Detection: Interim Results From a Multicenter Prospective Registry

SESSION TITLE: Advances in Lung Cancer SESSION TYPE: Original Investigation Slide PRESENTED ON: Wednesday, November 1, 2017 at 08:45 AM - 10:00 AM PURPOSE: The Bronchial Genomic Classifier (BGC) improves the sensitivity and negative predictive value (NPV) of bronchoscopy for lung cancer detection. The BGC identifies patients who, with a pre-test intermediate (10-60%) risk of malignancy, and an inconclusive diagnostic bronchoscopy result, are at low risk of malignancy (<10%) and may be considered for radiographic monitoring instead of an additional invasive procedure. We report a planned interim utility analysis from a prospective, multi-center registry study of the BGC, designed to observe patient selection, classifier performance, clinical utility and safety across varied clinical settings. METHODS: The BGC Registry enrolls patients at 43 medical centers who have had an inconclusive diagnostic bronchoscopy for suspected lung cancer, and for whom the BGC was ordered. The BGC sample is obtained by brushing the normal appearing mucosa of the central airway during bronchoscopy. The BGC is measured in those samples after cytology on biospecimens collected at bronchoscopy are confirmed inconclusive. Pre- and post- BGC clinical management recommendations are recorded and follow-up clinical and imaging data are collected at regular time points up to 36 months. RESULTS: 665 eligible patients underwent a diagnostic bronchoscopy for evaluation of lung cancer. A diagnosis was made in 259 (39%) patients at index bronchoscopy: 182 (27%) with lung cancer and 77 (12%) with a benign condition. The BGC was not ordered in 39 (6%) patients and 13 (2%) were not consented, leaving 354 patients meeting enrollment criteria. Of these, 315 patients are evaluable with exclusions of 17 (2%) patients with a BGC ‘no-result’, and 22 patients with insufficient data. Demographics showed 60% ≥ 65 y/o; 50% female, with a median 40 pack-year smoking history. This interim analysis focuses on 209 (66%) patients with an intermediate pre-test risk of malignancy where CT scans showed 76% of index lesions were ≤ 30 mm, 69% were peripherally located, 60% were solid and 50% were in the upper lobe. Advanced bronchoscopic technologies were used in 68% of cases. The BGC test results reclassified 74 (35%) pre-test intermediate risk patients to post-test low risk. At 10-months median follow-up, the reclassified low risk group showed a 17% absolute (40% to 23%), or 40% relative reduction in the use of invasive procedures compared to their pre-test diagnostic management plan. Patients who remained intermediate post-test risk showed no increase in invasive procedures. Five (2%) reclassified low risk patients have, at a median of 10-months follow-up, been diagnosed with lung cancer, well within the NPV of the test (91%). Four of five patients have undergone successful resection without evidence of a stage shift. CONCLUSIONS: This interim analysis from this prospective registry confirms the performance of the BGC reported in the AEGIS I and II studies.The emerging safety of reclassified low risk patients is encouraging. Additional follow-up is required to evaluate the full impact of clinical utility. CLINICAL IMPLICATIONS: The BGC improves the sensitivity of diagnostic bronchoscopy for patients undergoing evaluation for lung cancer and can reduce the number of unnecessary invasive procedures that are performed following an inconclusive procedure. DISCLOSURE: Douglas Hogarth: Grant monies (from industry related sources): Industry funded research, Consultant fee, speaker bureau, advisory committee, etc.: Advisor Board Joshiah Gordon: Other: Paid for time it takes to enroll patients Kate Smith: Employee: I receive a salary and hold stock options from Veracyte. Pauline Bianchi: Employee: Employed by Veracyte Marc Lenburg: Consultant fee, speaker bureau, advisory committee, etc.: Veracyte, Grant monies (from sources other than industry): NIH Avrum Spira: Consultant fee, speaker bureau, advisory committee, etc.: Advisor The following authors have nothing to disclose: Hans Lee, Patrick Whitten, Krish Bhadra, Travis Dotson, Sadia Benzaquen, Michael Pritchett, Ajay Bedekar, Mark Esterle No Product/Research Disclosure Information

Abstract 2423: Bronchial airway gene expression signatures in mouse lung squamous cell carcinoma and their modulation by cancer chemopreventive agents

Abstract Due to exposure to environmental toxicants, a “field cancerization” effect occurs in the lung resulting in the development of a field of initiated but morphologically normal appearing cells in the damaged epithelium of bronchial airways with dysregulated gene expression patterns. Using a mouse model of lung squamous cell carcinoma (SCC), we performed transcriptome sequencing (RNA-Seq) to profile bronchial airway gene expression and found activation of the PI3k and Myc signaling networks in cytologically normal bronchial airway epithelial cells of mice with preneopastic lung SCC lesions, which was reversed by treatment with the PI3K Inhibitor XL-147 and pioglitazone, respectively. Activated MYC signaling was also present in premalignant and tumor tissues from human lung SCC patients. In addition, we identified a key microRNA, mmu-miR-449c-5p, whose suppression significantly up-regulated Myc expression in the normal bronchial airway epithelial cells of mice with early stage SCC lesions. We developed a novel bronchial genomic classifier in mice and validated it in humans. In the classifier, Ppbp (pro-platelet basic protein) was overexpressed 115 fold in the bronchial airways of mice with preneoplastic lung SCC lesions. This is the first report that demonstrates Ppbp as a novel biomarker in the bronchial airway for lung cancer diagnosis. Citation Format: Donghai Xiong, Jing Pan, Qi Zhang, Eva Szabo, Mark S. Miller, Ronald A. Lubet, Ming You, Yian Wang. Bronchial airway gene expression signatures in mouse lung squamous cell carcinoma and their modulation by cancer chemopreventive agents [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2423. doi:10.1158/1538-7445.AM2017-2423

Cost-Effectiveness of a Bronchial Genomic Classifier for the Diagnostic Evaluation of Lung Cancer

IntroductionThe use of a bronchial genomic classifier has been shown to improve the diagnostic accuracy of bronchoscopy for suspected lung cancer by identifying patients who may be more suitable for radiographic surveillance as opposed to invasive procedures. Our objective was to assess the cost-effectiveness of bronchoscopy plus a genomic classifier versus bronchoscopy alone in the diagnostic work-up of patients at intermediate risk for lung cancer. MethodsA decision-analytic Markov model was developed to project the costs and effects of two competing strategies by using test performance from the Airway Epithelial Gene Expression in the Diagnosis of Lung Cancer–1 and Airway Epithelial Gene Expression in the Diagnosis of Lung Cancer–2 studies. The diagnostic accuracy of noninvasive and invasive follow-up, as well as associated adverse event rates, were derived from published literature. Procedure costs were based on claims data and 2016 inpatient and outpatient reimbursement amounts. The model projected the number of invasive follow-up procedures, 2-year costs and quality-adjusted life-years (QALYs) by strategy, and resulting incremental cost-effectiveness ratio discounted at 3% per annum. ResultsUse of the genomic classifier reduced invasive procedures by 28% at 1 month and 18% at 2 years, respectively. Total costs and QALY gain were similar with classifier use ($27,221 versus $27,183 and 1.512 versus 1.509, respectively), resulting in an incremental cost-effectiveness ratio of $15,052 per QALY. ConclusionsOur analysis suggests that the use of a genomic classifier is associated with meaningful reductions in invasive procedures at about equal costs and is therefore a high-value strategy in the diagnostic work-up of patients at intermediate risk of lung cancer.

SC18.01 Field Cancerization in the Airways and its Application to Lung Cancer Early Detection

SC18.01 Field Cancerization in the Airways and its Application to Lung Cancer Early Detection

Bronchial airway gene expression signatures in mouse lung squamous cell carcinoma and their modulation by cancer chemopreventive agents.

Due to exposure to environmental toxicants, a “field cancerization” effect occurs in the lung resulting in the development of a field of initiated but morphologically normal appearing cells in the damaged epithelium of bronchial airways with dysregulated gene expression patterns. Using a mouse model of lung squamous cell carcinoma (SCC), we performed transcriptome sequencing (RNA-Seq) to profile bronchial airway gene expression and found activation of the PI3K and Myc signaling networks in cytologically normal bronchial airway epithelial cells of mice with preneopastic lung SCC lesions, which was reversed by treatment with the PI3K Inhibitor XL-147 and pioglitazone, respectively. Activated MYC signaling was also present in premalignant and tumor tissues from human lung SCC patients. In addition, we identified a key microRNA, mmu-miR-449c-5p, whose suppression significantly up-regulated Myc expression in the normal bronchial airway epithelial cells of mice with early stage SCC lesions. We developed a novel bronchial genomic classifier in mice and validated it in humans. In the classifier, Ppbp (pro-platelet basic protein) was overexpressed 115 fold in the bronchial airways of mice with preneoplastic lung SCC lesions. This is the first report that demonstrates Ppbp as a novel biomarker in the bronchial airway for lung cancer diagnosis.

Can the Use of a Genomic Classifier Reduce the Need for Invasive Procedures to Diagnose Lung Cancer?

Synopsis: This study evaluates the potential for a novel genetic classifier in patients with pulmonary nodules to increase the sensitivity and specificity of lung cancer screening and thereby reduce the number of patients being exposed to the harms of invasive diagnostic testing. Source: Vachani A, Whitney D, Parsons E, et al. Clinical utility of a bronchial genomic classifier in patients with suspected lung cancer. Chest. 2016;150(1):210–218.

Impact of a Bronchial Genomic Classifier for Lung Cancer on Reducing Invasive Procedure Recommendations Across Variations in Pulmonology Practices

Impact of a Bronchial Genomic Classifier for Lung Cancer on Reducing Invasive Procedure Recommendations Across Variations in Pulmonology Practices

Impact of a bronchial genomic classifier on clinical decision making in patients undergoing diagnostic evaluation for lung cancer.

BackgroundBronchoscopy is frequently used for the evaluation of suspicious pulmonary lesions found on computed tomography, but its sensitivity for detecting lung cancer is limited. Recently, a bronchial genomic classifier was validated to improve the sensitivity of bronchoscopy for lung cancer detection, demonstrating a high sensitivity and negative predictive value among patients at intermediate risk (10–60 %) for lung cancer with an inconclusive bronchoscopy. Our objective for this study was to determine if a negative genomic classifier result that down-classifies a patient from intermediate risk to low risk (<10 %) for lung cancer would reduce the rate that physicians recommend more invasive testing among patients with an inconclusive bronchoscopy.MethodsWe conducted a randomized, prospective, decision impact survey study assessing pulmonologist recommendations in patients undergoing workup for lung cancer who had an inconclusive bronchoscopy. Cases with an intermediate pretest risk for lung cancer were selected from the AEGIS trials and presented in a randomized fashion to pulmonologists either with or without the patient’s bronchial genomic classifier result to determine how the classifier results impacted physician decisions.ResultsTwo hundred two physicians provided 1523 case evaluations on 36 patients. Invasive procedure recommendations were reduced from 57 % without the classifier result to 18 % with a negative (low risk) classifier result (p < 0.001). Invasive procedure recommendations increased from 50 to 65 % with a positive (intermediate risk) classifier result (p < 0.001). When stratifying by ultimate disease diagnosis, there was an overall reduction in invasive procedure recommendations in patients with benign disease when classifier results were reported (54 to 41 %, p < 0.001). For patients ultimately diagnosed with malignant disease, there was an overall increase in invasive procedure recommendations when the classifier results were reported (50 to 64 %, p = 0.003).ConclusionsOur findings suggest that a negative (low risk) bronchial genomic classifier result reduces invasive procedure recommendations following an inconclusive bronchoscopy and that the classifier overall reduces invasive procedure recommendations among patients ultimately diagnosed with benign disease. These results support the potential clinical utility of the classifier to improve management of patients undergoing bronchoscopy for suspect lung cancer by reducing additional invasive procedures in the setting of benign disease.Electronic supplementary materialThe online version of this article (doi:10.1186/s12890-016-0217-1) contains supplementary material, which is available to authorized users.

Analytical performance of a bronchial genomic classifier.

BackgroundThe current standard practice of lung lesion diagnosis often leads to inconclusive results, requiring additional diagnostic follow up procedures that are invasive and often unnecessary due to the high benign rate in such lesions (Chest 143:e78S-e92, 2013). The Percepta bronchial genomic classifier was developed and clinically validated to provide more accurate classification of lung nodules and lesions that are inconclusive by bronchoscopy, using bronchial brushing specimens (N Engl J Med 373:243–51, 2015, BMC Med Genomics 8:18, 2015). The analytical performance of the Percepta test is reported here.MethodsAnalytical performance studies were designed to characterize the stability of RNA in bronchial brushing specimens during collection and shipment; analytical sensitivity defined as input RNA mass; analytical specificity (i.e. potentially interfering substances) as tested on blood and genomic DNA; and assay performance studies including intra-run, inter-run, and inter-laboratory reproducibility.ResultsRNA content within bronchial brushing specimens preserved in RNAprotect is stable for up to 20 days at 4 °C with no changes in RNA yield or integrity. Analytical sensitivity studies demonstrated tolerance to variation in RNA input (157 ng to 243 ng). Analytical specificity studies utilizing cancer positive and cancer negative samples mixed with either blood (up to 10 % input mass) or genomic DNA (up to 10 % input mass) demonstrated no assay interference. The test is reproducible from RNA extraction through to Percepta test result, including variation across operators, runs, reagent lots, and laboratories (standard deviation of 0.26 for scores on > 6 unit scale).ConclusionsAnalytical sensitivity, analytical specificity and robustness of the Percepta test were successfully verified, supporting its suitability for clinical use.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-016-2153-0) contains supplementary material, which is available to authorized users.

Clinical Utility of a Bronchial Genomic Classifier in Patients With Suspected Lung Cancer

Bronchoscopy is often the initial diagnostic procedure performed in patients with pulmonary lesions suggestive of lung cancer. A bronchial genomic classifier was previously validated to identify patients at low risk for lung cancer after an inconclusive bronchoscopy. In this study, we evaluated the potential of the classifier to reduce invasive procedure utilization in patients with suspected lung cancer. In two multicenter trials of patients undergoing bronchoscopy for suspected lung cancer, the classifier was measured in normal-appearing bronchial epithelial cells from a mainstem bronchus. Among patients with low and intermediate pretest probability of cancer (n= 222), subsequent invasive procedures after an inconclusive bronchoscopy were identified. Estimates of the ability of the classifier to reduce unnecessary procedures were calculated. Of the 222 patients, 188 (85%) had an inconclusive bronchoscopy and follow-up procedure data available for analysis. Seventy-seven (41%) patients underwent an additional 99 invasive procedures, which included surgical lung biopsy in 40 (52%) patients. Benign and malignant diseases were ultimately diagnosed in 62 (81%) and 15 (19%) patients, respectively. Among those undergoing surgical biopsy, 20 (50%) were performed in patients with benign disease. If the classifier had been used to guide decision making, procedures could have been avoided in 50%(21 of 42) of patients undergoing further invasive testing. Further, among 35 patients with an inconclusive index bronchoscopy who were diagnosed with lung cancer, the sensitivity of the classifier was 89%, with 4 (11%) patients having a false-negative classifier result. Invasive procedures after an inconclusive bronchoscopy occur frequently, and most are performed in patients ultimately diagnosed with benign disease. Using the genomic classifier as an adjunct to bronchoscopy may reduce the frequency and associated morbidity of these invasive procedures. ClinicalTrials.gov; Nos. NCT01309087 and NCT00746759; URL: www.clinicaltrials.gov.

Diagnostic Performance of a Genomic Classifier for Lung Cancer

Synopsis: The addition of a novel genomic classifier to standard bronchoscopy for the evaluation of lung canner improved diagnostic performance regardless of the size, location or stage of the lesion. Source: Silvestri G, Vachani A, Whitney D, et al. A bronchial genomic classifier for the diagnostic evaluation of lung cancer. N Engl J Med. 2015;373:243–251.

A Bronchial Genomic Classifier for the Diagnostic Evaluation of Lung Cancer

BackgroundBronchoscopy is frequently nondiagnostic in patients with pulmonary lesions suspected to be lung cancer. This often results in additional invasive testing, although many lesions are benign. We sought to validate a bronchial-airway gene-expression classifier that could improve the diagnostic performance of bronchoscopy.MethodsCurrent or former smokers undergoing bronchoscopy for suspected lung cancer were enrolled at 28 centers in two multicenter prospective studies (AEGIS-1 and AEGIS-2). A gene-expression classifier was measured in epithelial cells collected from the normal-appearing mainstem bronchus to assess the probability of lung cancer.ResultsA total of 639 patients in AEGIS-1 (298 patients) and AEGIS-2 (341 patients) met the criteria for inclusion. A total of 43% of bronchoscopic examinations were nondiagnostic for lung cancer, and invasive procedures were performed after bronchoscopy in 35% of patients with benign lesions. In AEGIS-1, the classifier had an area under the receiver-operating-characteristic curve (AUC) of 0.78 (95% confidence interval [CI], 0.73 to 0.83), a sensitivity of 88% (95% CI, 83 to 92), and a specificity of 47% (95% CI, 37 to 58). In AEGIS-2, the classifier had an AUC of 0.74 (95% CI, 0.68 to 0.80), a sensitivity of 89% (95% CI, 84 to 92), and a specificity of 47% (95% CI, 36 to 59). The combination of the classifier plus bronchoscopy had a sensitivity of 96% (95% CI, 93 to 98) in AEGIS-1 and 98% (95% CI, 96 to 99) in AEGIS-2, independent of lesion size and location. In 101 patients with an intermediate pretest probability of cancer, the negative predictive value of the classifier was 91% (95% CI, 75 to 98) among patients with a nondiagnostic bronchoscopic examination.ConclusionsThe gene-expression classifier improved the diagnostic performance of bronchoscopy for the detection of lung cancer. In intermediate-risk patients with a nondiagnostic bronchoscopic examination, a negative classifier score provides support for a more conservative diagnostic approach. (Funded by Allegro Diagnostics and others; AEGIS-1 and AEGIS-2 ClinicalTrials.gov numbers, NCT01309087 and NCT00746759.)

Derivation of a bronchial genomic classifier for lung cancer in a prospective study of patients undergoing diagnostic bronchoscopy.

BackgroundThe gene expression profile of cytologically-normal bronchial airway epithelial cells has previously been shown to be altered in patients with lung cancer. Although bronchoscopy is often used for the diagnosis of lung cancer, its sensitivity is imperfect, especially for small and peripheral suspicious lesions. In this study, we derived a gene expression classifier from airway epithelial cells that detects the presence of cancer in current and former smokers undergoing bronchoscopy for suspect lung cancer and evaluated its sensitivity to detect lung cancer among patients from an independent cohort.MethodsWe collected bronchial epithelial cells (BECs) from the mainstem bronchus of 299 current or former smokers (223 cancer-positive and 76 cancer-free subjects) undergoing bronchoscopy for suspected lung cancer in a prospective, multi-center study. RNA from these samples was run on gene expression microarrays for training a gene-expression classifier. A logistic regression model was built to predict cancer status, and the finalized classifier was validated in an independent cohort from a previous study.ResultsWe found 232 genes whose expression levels in the bronchial airway are associated with lung cancer. We then built a classifier based on the combination of 17 cancer genes, gene expression predictors of smoking status, smoking history, and gender, plus patient age. This classifier had a ROC curve AUC of 0.78 (95% CI, 0.70-0.86) in patients whose bronchoscopy did not lead to a diagnosis of lung cancer (n = 134). In the validation cohort, the classifier had a similar AUC of 0.81 (95% CI, 0.73-0.88) in this same subgroup (n = 118). The classifier performed similarly across a range of mass sizes, cancer histologies and stages. The negative predictive value was 94% (95% CI, 83-99%) in subjects with a non-diagnostic bronchoscopy.ConclusionWe developed a gene expression classifier measured in bronchial airway epithelial cells that is able to detect lung cancer in current and former smokers who have undergone bronchoscopy for suspicion of lung cancer. Due to the high NPV of the classifier, it could potentially inform clinical decisions regarding the need for further invasive testing in patients whose bronchoscopy is non diagnostic.Electronic supplementary materialThe online version of this article (doi:10.1186/s12920-015-0091-3) contains supplementary material, which is available to authorized users.