Clinical validation and utility of Percepta GSC for the evaluation of lung cancer.

The Percepta Genomic Sequencing Classifier (GSC) was developed to up-classify as well as down-classify the risk of malignancy for lung lesions when bronchoscopy is non-diagnostic. We evaluated the performance of Percepta GSC in risk re-classification of indeterminate lung lesions. This multicenter study included individuals who currently or formerly smoked undergoing bronchoscopy for suspected lung cancer from the AEGIS I/ II cohorts and the Percepta Registry. The classifier was measured in normal-appearing bronchial epithelium from bronchial brushings. The sensitivity, specificity, and predictive values were calculated using predefined thresholds. The ability of the classifier to decrease unnecessary invasive procedures was estimated. A set of 412 patients were included in the validation (prevalence of malignancy was 39.6%). Overall, 29% of intermediate-risk lung lesions were down-classified to low-risk with a 91.0% negative predictive value (NPV) and 12.2% of intermediate-risk lesions were up-classified to high-risk with a 65.4% positive predictive value (PPV). In addition, 54.5% of low-risk lesions were down-classified to very low risk with >99% NPV and 27.3% of high-risk lesions were up-classified to very high risk with a 91.5% PPV. If the classifier results were used in nodule management, 50% of patients with benign lesions and 29% of patients with malignant lesions undergoing additional invasive procedures could have avoided these procedures. The Percepta GSC is highly accurate as both a rule-out and rule-in test. This high accuracy of risk re-classification may lead to improved management of lung lesions.

Distinguishing Smoking-Related Lung Disease Phenotypes Via Imaging and Molecular Features.

BACKGROUND: Chronic tobacco smoke exposure results in a broad range of lung pathologies including emphysema, airway disease and parenchymal fibrosis as well as a multitude of extra-pulmonary comorbidities. Prior work using CT imaging has identified several clinically relevant subgroups of smoking related lung disease, but these investigations have generally lacked organ specific molecular correlates. RESEARCH QUESTION: Can CT imaging be used to identify clinical phenotypes of smoking related lung disease that have specific bronchial epithelial gene expression patterns to better understand disease pathogenesis? STUDY DESIGN AND METHODS: Using K-means clustering, we clustered participants from the COPDGene study (n = 5,273) based on CT imaging characteristics and then evaluated their clinical phenotypes. These clusters were replicated in the Detection of Early Lung Cancer Among Military Personnel (DECAMP) cohort (n = 360), and were further characterized using bronchial epithelial gene expression. RESULTS: Three clusters (preserved, interstitial predominant and emphysema predominant) were identified. Compared to the preserved cluster, the interstitial and emphysema clusters had worse lung function, exercise capacity and quality of life. In longitudinal follow-up, individuals from the emphysema group had greater declines in exercise capacity and lung function, more emphysema, more exacerbations, and higher mortality. Similarly, genes involved in inflammatory pathways (tumor necrosis factor-α, interferon-ß) are more highly expressed in bronchial epithelial cells from individuals in the emphysema cluster, while genes associated with T-cell related biology are decreased in these samples. Samples from individuals in the interstitial cluster generally had intermediate levels of expression of these genes. INTERPRETATION: Using quantitative CT imaging, we identified three groups of individuals in older ever-smokers that replicate in two cohorts. Airway gene expression differences between the three groups suggests increased levels of inflammation in the most severe clinical phenotype, possibly mediated by the tumor necrosis factor-α and interferon-ß pathways. CLINICAL TRIAL REGISTRATION: COPDGene (NCT00608764), DECAMP-1 (NCT01785342), DECAMP-2 (NCT02504697).

Performance of a Genomic Sequencing Classifier for the Preoperative Diagnosis of Cytologically Indeterminate Thyroid Nodules.

Importance: Use of next-generation sequencing of RNA and machine learning algorithms can classify the risk of malignancy in cytologically indeterminate thyroid nodules to limit unnecessary diagnostic surgery. Objective: To measure the performance of a genomic sequencing classifier for cytologically indeterminate thyroid nodules. Design, Setting, and Participants: A blinded validation study was conducted on a set of cytologically indeterminate thyroid nodules collected by fine-needle aspiration biopsy between June 2009 and December 2010 from 49 academic and community centers in the United States. All patients underwent surgery without genomic information and were assigned a histopathology diagnosis by an expert panel blinded to all genomic information. There were 210 potentially eligible thyroid biopsy samples with Bethesda III or IV indeterminate cytopathology that constituted a cohort previously used to validate the gene expression classifier. Of these, 191 samples (91.0%) had adequate residual RNA for validation of the genomic sequencing classifier. Algorithm development and independent validation occurred between August 2016 and May 2017. Exposures: Thyroid nodule surgical histopathology diagnosis by an expert panel blinded to all genomic data. Main Outcomes and Measures: The primary end point was measurement of genomic sequencing classifier sensitivity, specificity, and negative and positive predictive values in biopsies from Bethesda III and IV nodules. The secondary end point was measurement of classifier performance in biopsies from Bethesda II, V, and VI nodules. Results: Of the 183 included patients, 142 (77.6%) were women, and the mean (range) age was 51.7 (22.0-85.0) years. The genomic sequencing classifier had a sensitivity of 91% (95% CI, 79-98) and a specificity of 68% (95% CI, 60-76). At 24% cancer prevalence, the negative predictive value was 96% (95% CI, 90-99) and the positive predictive value was 47% (95% CI, 36-58). Conclusions and Relevance: The genomic sequencing classifier demonstrates high sensitivity and accuracy for identifying benign nodules. Its 36% increase in specificity compared with the gene expression classifier potentially increases the number of patients with benign nodules who can safely avoid unnecessary diagnostic surgery.

Alterations in Bronchial Airway miRNA Expression for Lung Cancer Detection.

We have previously shown that gene expression alterations in normal-appearing bronchial epithelial cells can serve as a lung cancer detection biomarker in smokers. Given that miRNAs regulate airway gene expression responses to smoking, we evaluated whether miRNA expression is also altered in the bronchial epithelium of smokers with lung cancer. Using epithelial brushings from the mainstem bronchus of patients undergoing bronchoscopy for suspected lung cancer (as part of the AEGIS-1/2 clinical trials), we profiled miRNA expression via small-RNA sequencing from 347 current and former smokers for which gene expression data were also available. Patients were followed for one year postbronchoscopy until a final diagnosis of lung cancer (n = 194) or benign disease (n = 153) was made. Following removal of 6 low-quality samples, we used 138 patients (AEGIS-1) as a discovery set to identify four miRNAs (miR-146a-5p, miR-324-5p, miR-223-3p, and miR-223-5p) that were downregulated in the bronchial airway of lung cancer patients (ANOVA P < 0.002, FDR < 0.2). The expression of these miRNAs is significantly more negatively correlated with the expression of their mRNA targets than with the expression of other nontarget genes (K-S P < 0.05). Furthermore, these mRNA targets are enriched among genes whose expression is elevated in cancer patients (GSEA FDR < 0.001). Finally, we found that the addition of miR-146a-5p to an existing mRNA biomarker for lung cancer significantly improves its performance (AUC) in the 203 samples (AEGIS-1/2) serving an independent test set (DeLong P < 0.05). Our findings suggest that there are miRNAs whose expression is altered in the cytologically normal bronchial epithelium of smokers with lung cancer, and that they may regulate cancer-associated gene expression differences. Cancer Prev Res; 10(11); 651-9. ©2017 AACR.

Analytical performance of a bronchial genomic classifier.

BACKGROUND: The 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. METHODS: Analytical 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. RESULTS: RNA 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). CONCLUSIONS: Analytical sensitivity, analytical specificity and robustness of the Percepta test were successfully verified, supporting its suitability for clinical use.

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

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. TRIAL REGISTRY: ClinicalTrials.gov; Nos. NCT01309087 and NCT00746759; URL: www.clinicaltrials.gov.

A Bronchial Genomic Classifier for the Diagnostic Evaluation of Lung Cancer.

BACKGROUND: Bronchoscopy 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. METHODS: Current 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. RESULTS: A 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. CONCLUSIONS: The 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.

BACKGROUND: The 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. METHODS: We 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. RESULTS: We 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. CONCLUSION: We 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.

A microRNA expression ratio defining the invasive phenotype in bladder tumors.

OBJECTIVE: The goal of this study was to identify a microRNA (miRNA) signature in bladder cancer capable of differentiating superficial from invasive disease. METHODS: Expression profiling of 343 miRNAs was performed in a microarray format using noninvasive and invasive bladder carcinoma cell lines with differential expression confirmed using a single molecule detection platform assay. miR-21 and miR-205 expression levels were determined in 53 bladder tumors (28 superficial and 25 invasive). Sensitivity, specificity, and a ROC curve were calculated to determine the discriminatory power of the miRNA ratio to predict invasion. Knockdown and forced expression of miRNAs was performed to evaluate their role in invasion. RESULTS: Expression profiling of 343 miRNAs, using noninvasive and invasive bladder cell lines, revealed significant differential expression of 9 miRNAs. Cell lines characterized as invasive showed a miR-21:miR-205 ratio at least 10-fold higher than the quantitative ratio obtained from non-invasive cell lines. The same expression ratio was determined in 53 bladder tumors. From these results, we recorded a sensitivity and specificity of 100% and 78%, respectively, using a cutoff of 1.79 to predict an invasive lesion. The area under the receiver operator characteristic curve was 0.89. Using in vitro invasion assays, we have demonstrated a role for miR-21 in establishing the invasive phenotype of bladder carcinoma cells. CONCLUSION: In this study, we identified a miR-21:miR-205 expression ratio that has the ability to distinguish between invasive and noninvasive bladder tumors with high sensitivity and specificity, with the potential to identify superficial lesions at high risk to progress.

An electrophoretic capture method for efficient recovery of rare sequences from heterogeneous DNA.

It is difficult to isolate rare, PCR-quality DNA from specimens containing large quantities of nonspecific DNA from multiple sources (heterogeneous DNA). Extracting human DNA from stool for colorectal cancer (CRC) screening tests exemplifies this technically challenging sample preparation problem. The stool matrix is complex, the DNA composition heterogeneous, and CRC-associated mutated DNA is rare. This report describes a novel solid phase DNA sequence-specific hybrid capture sample preparation method: the reversible electrophoretic capture affinity protocol (RECAP). We show that RECAP, compared with other methods, is capable of extracting linearly increasing amounts of human DNA from increasing amounts of total stool DNA in a manner that avoids co-purifying PCR inhibitors. RECAP thereby increases the yield of rare mutated DNA molecules and thus increases the detection sensitivity for CRC-associated mutations.

Distinctive patterns of microRNA expression in primary muscular disorders.

The primary muscle disorders are a diverse group of diseases caused by various defective structural proteins, abnormal signaling molecules, enzymes and proteins involved in posttranslational modifications, and other mechanisms. Although there is increasing clarification of the primary aberrant cellular processes responsible for these conditions, the decisive factors involved in the secondary pathogenic cascades are still mainly obscure. Given the emerging roles of microRNAs (miRNAs) in modulation of cellular phenotypes, we searched for miRNAs regulated during the degenerative process of muscle to gain insight into the specific regulation of genes that are disrupted in pathological muscle conditions. We describe 185 miRNAs that are up- or down-regulated in 10 major muscular disorders in humans [Duchenne muscular dystrophy (DMD), Becker muscular dystrophy, facioscapulohumeral muscular dystrophy, limb-girdle muscular dystrophies types 2A and 2B, Miyoshi myopathy, nemaline myopathy, polymyositis, dermatomyositis, and inclusion body myositis]. Although five miRNAs were found to be consistently regulated in almost all samples analyzed, pointing to possible involvement of a common regulatory mechanism, others were dysregulated only in one disease and not at all in the other disorders. Functional correlation between the predicted targets of these miRNAs and mRNA expression demonstrated tight posttranscriptional regulation at the mRNA level in DMD and Miyoshi myopathy. Together with direct mRNA-miRNA predicted interactions demonstrated in DMD, some of which are involved in known secondary response functions and others that are involved in muscle regeneration, these findings suggest an important role of miRNAs in specific physiological pathways underlying the disease pathology.

Improved marker combination for detection of de novo genetic variation and aberrant DNA in colorectal neoplasia.

BACKGROUND: The genetic heterogeneity of sporadic colorectal cancer (CRC) makes the choice of genetic markers and sequence variation-detection technologies critical to the performance of screening assays. We have previously described the effectiveness of a CRC assay composed of 22 known variants in KRAS, APC, TP53, and BAT-26 (V1). We introduce a new marker formulation (V2) that includes detection of de novo variation in APC, PIK3CA, and CTNNB1, hypermethylated sequences within SMARCA3 and VIM, and a single-base variation within BRAF. We compared the abilities of the V1 and V2 markers to detect aberrant DNA in colorectal neoplasias. METHODS: V1 and V2 marker formulations were used to analyze 144 colorectal tissue samples comprising 50 precancerous adenomas, 94 carcinomas, and 11 nonpathologic tissues. V1 analysis consisted of single-base extension analysis of the 22 V1 variants. V2 analysis consisted of DNA scanning of the APC mutation cluster region, PIK3CA exons 9 and 20, CTNNB1 exon 3, analysis for the BRAF Val600Glu substitution, and methylation-specific PCR analysis of VIM and SMARCA3. RESULTS: The V2 marker formulation had significantly higher sensitivity than the V1 markers for carcinomas (93.6% and 72.3%, respectively; P = 0.0002) and adenomas (92.0% and 62.0%, respectively; P = 0.0006). None of the nonpathologic samples were positive for any marker. CONCLUSIONS: We demonstrate improved sensitivity of a new marker formulation (V2) to detect aberrant DNA in CRC and precancerous adenoma tumor tissues.

DNA stabilization is critical for maximizing performance of fecal DNA-based colorectal cancer tests.

We have developed a multitarget, fecal DNA screening assay that detects the presence of gene-specific mutations and long DNA fragments associated with colorectal cancer (CRC). We continue to investigate methods that may be used to optimize clinical sensitivity. The goals of this investigation are to establish how sample handling conditions affect the stability of DNA in stool, thereby potentially limiting clinical sensitivity, and to determine conditions to ameliorate DNA degradation. A study was run comparing paired sample aliquots. Quantitative PCR data for matched aliquots was used to determine first the effect of sample incubation on total recovery and integrity of DNA, then the effect of stabilization buffer addition to stool on recoverable DNA, and finally the impact of buffer addition on assay sensitivity. Comparison of quantitative PCR data for paired aliquots shows that the amount of recoverable human DNA is negatively affected by storing stool samples (N = 43) at room temperature for > or =36 hours (P = 0.0018). However, the addition of stabilization buffer leads to a significant increase in recovery of DNA (P = 0.010), compared with samples incubated without buffer. Whereas the DNA Integrity Assay (DIA) is found to be sensitive to DNA degradation (sensitivity was reduced by 82%; P = 0.0002), point mutation marker sensitivity is more refractory. Overall, DNA can be stabilized by addition of buffer to the sample, leading to increased assay sensitivity.

Enhanced retrieval of DNA from human fecal samples results in improved performance of colorectal cancer screening test.

Colorectal cancer accounts for more than 10% of all cancer deaths but is curable, if detected early. We reported previously on a stool-based screening test in which DNA from stool samples is subjected to genome analysis; sensitivity of the test has been limited in part by inefficiency of retrieving DNA from stool. Our aim was to test the impact of a new purification method that would increase the yield of human DNA from stool. DNA from 86 cancer and 100 non-cancer subjects (diagnosed by colonoscopy) were purified from stool with a new method for DNA recovery based on sequence-specific capture with acrylamide gel immobilized capture probes as well as with a previously developed magnetic bead-capture procedure. The new purification method gives an average 5.4-fold increase in the quantity of human DNA that can routinely be retrieved from fecal samples. The increased recovery of DNA corresponds with an increase in assay sensitivity from 53% (CI: 42 to 64%) to 70% (CI: 59 to 79%); P = 0.0005 (by McNemar's test), with no change in specificity. The newly developed sample preparation method mitigates a major problem in detecting rare cancer-associated genetic changes in heterogeneous clinical samples such as stool.

Multicolor in vitro translation.

In vitro translation is a widely used tool for both analytical and preparative purposes. For analytical purposes, small amounts of proteins are synthesized and visualized by detection of labeled amino acids incorporated during translation. The original strategy of incorporating radioactively labeled amino acids, such as [35S]methionine or [14C]leucine, has been superseded by the addition of antigenic tags or the incorporation of biotin-labeled or BODIPY-FL-labeled amino acids. Such nonradioactive tags are easier to visualize after translation and do not pose a radiation hazard. Among the nonradioactive tags, BODIPY-FL-lysine offers the advantage that proteins that have incorporated this amino acid can be directly visualized after gel electrophoresis. We show here that multiple fluorophores introduced into proteins can considerably extend their usefulness, particularly for the comparison of in vitro-translated proteins from related sources. This technology can be applied in various situations, including the simplified detection of rare truncating mutations in clinical samples from cancer patients.