Analytical validation of the Percepta genomic sequencing classifier; an RNA next generation sequencing assay for the assessment of Lung Cancer risk of suspicious pulmonary nodules

BACKGROUND

Bronchoscopy is a common procedure used for evaluation of suspicious lung nodules, but the low diagnostic sensitivity of bronchoscopy often results in inconclusive results and delays in treatment. Percepta Genomic Sequencing Classifier (GSC) was developed to assist with patient management in cases where bronchoscopy is inconclusive. Studies have shown that exposure to tobacco smoke alters gene expression in airway epithelial cells in a way that indicates an increased risk of developing lung cancer. Percepta GSC leverages this idea of a molecular "field of injury" from smoking and was developed using RNA sequencing data generated from lung bronchial brushings of the upper airway. A Percepta GSC score is calculated from an ensemble of machine learning algorithms utilizing clinical and genomic features and is used to refine a patient's risk stratification.

METHODS

The objective of the analysis described and reported here is to validate the analytical performance of Percepta GSC. Analytical performance studies characterized the sensitivity of Percepta GSC test results to input RNA quantity, the potentially interfering agents of blood and genomic DNA, and the reproducibility of test results within and between processing runs and between laboratories.

RESULTS

Varying the amount of input RNA into the assay across a nominal range had no significant impact on Percepta GSC classifier results. Bronchial brushing RNA contaminated with up to 10% genomic DNA by nucleic acid mass also showed no significant difference on classifier results. The addition of blood RNA, a potential contaminant in the bronchial brushing sample, caused no change to classifier results at up to 11% contamination by RNA proportion. Percepta GSC scores were reproducible between runs, within runs, and between laboratories, varying within less than 4% of the total score range (standard deviation of 0.169 for scores on 4.57 scale).

CONCLUSIONS

The analytical sensitivity, analytical specificity, and reproducibility of Percepta GSC laboratory results were successfully demonstrated under conditions of expected day to day variation in testing. Percepta GSC test results are analytically robust and suitable for routine clinical use.

Identification of Hürthle cell cancers: solving a clinical challenge with genomic sequencing and a trio of machine learning algorithms

BACKGROUND

Identification of Hürthle cell cancers by non-operative fine-needle aspiration biopsy (FNAB) of thyroid nodules is challenging. Resultingly, non-cancerous Hürthle lesions were conventionally distinguished from Hürthle cell cancers by histopathological examination of tissue following surgical resection. Reliance on histopathological evaluation requires patients to undergo surgery to obtain a diagnosis despite most being non-cancerous. It is highly desirable to avoid surgery and to provide accurate classification of benignity versus malignancy from FNAB preoperatively. In our first-generation algorithm, Gene Expression Classifier (GEC), we achieved this goal by using machine learning (ML) on gene expression features. The classifier is sensitive, but not specific due in part to the presence of non-neoplastic benign Hürthle cells in many FNAB.

RESULTS

We sought to overcome this low-specificity limitation by expanding the feature set for ML using next-generation whole transcriptome RNA sequencing and called the improved algorithm the Genomic Sequencing Classifier (GSC). The Hürthle identification leverages mitochondrial expression and we developed novel feature extraction mechanisms to measure chromosomal and genomic level loss-of-heterozygosity (LOH) for the algorithm. Additionally, we developed a multi-layered system of cascading classifiers to sequentially triage Hürthle cell-containing FNAB, including: 1. presence of Hürthle cells, 2. presence of neoplastic Hürthle cells, and 3. presence of benign Hürthle cells. The final Hürthle cell Index utilizes 1048 nuclear and mitochondrial genes; and Hürthle cell Neoplasm Index leverages LOH features as well as 2041 genes. Both indices are Support Vector Machine (SVM) based. The third classifier, the GSC Benign/Suspicious classifier, utilizes 1115 core genes and is an ensemble classifier incorporating 12 individual models.

CONCLUSIONS

The accurate algorithmic depiction of this complex biological system among Hürthle subtypes results in a dramatic improvement of classification performance; specificity among Hürthle cell neoplasms increases from 11.8% with the GEC to 58.8% with the GSC, while maintaining the same sensitivity of 89%.

Analytical performance of Envisia: a genomic classifier for usual interstitial pneumonia

BACKGROUND

Clinical guidelines specify that diagnosis of interstitial pulmonary fibrosis (IPF) requires identification of usual interstitial pneumonia (UIP) pattern. While UIP can be identified by high resolution CT of the chest, the results are often inconclusive, making surgical lung biopsy necessary to reach a definitive diagnosis (Raghu et al., Am J Respir Crit Care Med 183(6):788-824, 2011). The Envisia genomic classifier differentiates UIP from non-UIP pathology in transbronchial biopsies (TBB), potentially allowing patients to avoid an invasive procedure (Brown et al., Am J Respir Crit Care Med 195:A6792, 2017). To ensure patient safety and efficacy, a laboratory developed test (LDT) must meet strict regulatory requirements for accuracy, reproducibility and robustness. The analytical characteristics of the Envisia test are assessed and reported here.

METHODS

The Envisia test utilizes total RNA extracted from TBB samples to perform Next Generation RNA Sequencing. The gene count data from 190 genes are then input to the Envisia genomic classifier, a machine learning algorithm, to output either a UIP or non-UIP classification result. We characterized the stability of RNA in TBBs during collection and shipment, and evaluated input RNA mass and proportions on the limit of detection of UIP. We evaluated potentially interfering substances such as blood and genomic DNA. Intra-run, inter-run, and inter-laboratory reproducibility of test results were also characterized.

RESULTS

RNA content within TBBs preserved in RNAprotect is stable for up to 14 days with no detectable change in RNA quality. The Envisia test is tolerant to variation in RNA input (5 to 30 ng), with no impact on classifier results. The Envisia test can tolerate dilution of non-UIP and UIP classification signals at the RNA level by up to 60% and 20%, respectively. Analytical specificity studies utilizing UIP and non-UIP samples mixed with genomic DNA (up to 30% relative input) demonstrated no impact to classifier results. The Envisia test tolerates up to 22% of blood contamination, well beyond the level observed in TBBs. The test is reproducible from RNA extraction through to Envisia test result (standard deviation of 0.20 for Envisia classification scores on > 7-unit scale).

CONCLUSIONS

The Envisia test demonstrates the robust analytical performance required of an LDT. Envisia can be used to inform the diagnoses of patients with suspected IPF.

Histone deacetylase (HDAC) inhibitor kinetic rate constants correlate with cellular histone acetylation but not transcription and cell viability

Histone deacetylases (HDACs) are critical in the control of gene expression, and dysregulation of their activity has been implicated in a broad range of diseases, including cancer, cardiovascular, and neurological diseases. HDAC inhibitors (HDACi) employing different zinc chelating functionalities such as hydroxamic acids and benzamides have shown promising results in cancer therapy. Although it has also been suggested that HDACi with increased isozyme selectivity and potency may broaden their clinical utility and minimize side effects, the translation of this idea to the clinic remains to be investigated. Moreover, a detailed understanding of how HDACi with different pharmacological properties affect biological functions in vitro and in vivo is still missing. Here, we show that a panel of benzamide-containing HDACi are slow tight-binding inhibitors with long residence times unlike the hydroxamate-containing HDACi vorinostat and trichostatin-A. Characterization of changes in H2BK5 and H4K14 acetylation following HDACi treatment in the neuroblastoma cell line SH-SY5Y revealed that the timing and magnitude of histone acetylation mirrored both the association and dissociation kinetic rates of the inhibitors. In contrast, cell viability and microarray gene expression analysis indicated that cell death induction and changes in transcriptional regulation do not correlate with the dissociation kinetic rates of the HDACi. Therefore, our study suggests that determining how the selective and kinetic inhibition properties of HDACi affect cell function will help to evaluate their therapeutic utility.

Lung gene expression in a rhesus allergic asthma model correlates with physiologic parameters of disease and exhibits common and distinct pathways with human asthma and a mouse asthma model

Experimental nonhuman primate models of asthma exhibit multiple features that are characteristic of an eosinophilic/T helper 2 (Th2)-high asthma subtype, characterized by the increased expression of Th2 cytokines and responsive genes, in humans. Here, we determine the molecular pathways that are present in a house dust mite-induced rhesus asthma model by analyzing the genomewide lung gene expression profile of the rhesus model and comparing it with that of human Th2-high asthma. We find that a prespecified human Th2 inflammation gene set from human Th2-high asthma is also present in rhesus asthma and that the expression of the genes comprising this gene set is positively correlated in human and rhesus asthma. In addition, as in human Th2-high asthma, the Th2 gene set correlates with physiologic markers of allergic inflammation and disease in rhesus asthma. Comparison of lung gene expression profiles from human Th2-high asthma, the rhesus asthma model, and a common mouse asthma model indicates that genes associated with Th2 inflammation are shared by all three species. However, some pathophysiologic aspects of human asthma (ie, subepithelial fibrosis, angiogenesis, neural biology, and immune host defense biology) are better represented in the gene expression profile of the rhesus model than in the mouse model. Further study of the rhesus asthma model may yield novel insights into the pathogenesis of human Th2-high asthma.

CD40 pathway activation status predicts response to CD40 therapy in diffuse large B cell lymphoma

The primary function of B cells, critical components of the adaptive immune response, is to produce antibodies against foreign antigens, as well as to perform isotype class switching, which changes the heavy chain of an antibody so that it can interact with different repertoires of effector cells. CD40 is a member of the tumor necrosis factor superfamily of cell surface receptors that transmits survival signals to B cells. In contrast, in B cell cancers, stimulation of CD40 signaling results in a heterogeneous response in which cells can sometimes undergo cell death in response to treatment, depending on the system studied. We found an association between sensitivity to CD40 stimulation and mutation of the tumor suppressor p53 in a panel of non-Hodgkin's lymphoma cell lines. Consistent with p53's tumor suppressor role, we found that higher levels of intrinsic DNA damage and increased proliferation rates, as well as higher levels of BCL6, a transcriptional repressor proto-oncogene, were associated with sensitivity to CD40 stimulation. In addition, CD40 treatment-resistant cell lines were sensitized to CD40 stimulation after the introduction of DNA-damaging agents. Using gene expression analysis, we also showed that resistant cell lines exhibited a preexisting activated CD40 pathway and that an mRNA expression signature comprising CD40 target genes predicted sensitivity and resistance to CD40-activating agents in cell lines and mouse xenograft models. Finally, the gene signature predicted tumor shrinkage and progression-free survival in patients with diffuse large B cell lymphoma treated with dacetuzumab, a monoclonal antibody with partial CD40 agonist activity. These data show that CD40 pathway activation status may be useful in predicting the antitumor activity of CD40-stimulating therapeutic drugs.

Gene expression patterns of Th2 inflammation and intercellular communication in asthmatic airways

Asthma is canonically thought of as a disorder of excessive Th2-driven inflammation in the airway, although recent studies have described heterogeneity with respect to asthma pathophysiology. We have previously described distinct phenotypes of asthma based on the presence or absence of a three-gene "Th2 signature" in bronchial epithelium, which differ in terms of eosinophilic inflammation, mucin composition, subepithelial fibrosis, and corticosteroid responsiveness. In the present analysis, we sought to describe Th2 inflammation in human asthmatic airways quantitatively with respect to known mediators of inflammation and intercellular communication. Using whole-genome microarray and quantitative real-time PCR analysis of endobronchial biopsies from 27 mild-to-moderate asthmatics and 13 healthy controls with associated clinical and demographic data, we found that asthmatic Th2 inflammation is expressed over a variable continuum, correlating significantly with local and systemic measures of allergy and eosinophilia. We evaluated a composite metric describing 79 coexpressed genes associated with Th2 inflammation against the biological space comprising cytokines, chemokines, and growth factors, identifying distinctive patterns of inflammatory mediators as well as Wnt, TGF-β, and platelet-derived growth factor family members. This integrated description of the factors regulating inflammation, cell migration, and tissue remodeling in asthmatic airways has important consequences for the pathophysiological and clinical impacts of emerging asthma therapeutics targeting Th2 inflammation.

Microarray analysis of RNA extracted from formalin-fixed, paraffin-embedded and matched fresh-frozen ovarian adenocarcinomas

Background

Gene expression profiling of formalin-fixed, paraffin-embedded (FFPE) samples represents a valuable approach for advancing oncology diagnostics and enhancing retrospective clinical studies; however, at present, this methodology still requires optimization and thus has not been extensively used. Here, we utilized thorough quality control methods to assess RNA extracted from FFPE samples and then compared it to RNA extracted from matched fresh-frozen (FF) counterparts. We preformed genome-wide expression profiling of FF and FFPE ovarian serous adenocarcinoma sample pairs and compared their gene signatures to normal ovary samples.

Methods

RNA from FFPE samples was extracted using two different methods, Ambion and Agencourt, and its quality was determined by profiling starting total RNA on Bioanalyzer and by amplifying increasing size fragments of beta actin (ACTB) and claudin 3 (CLDN3) by reverse-transcriptase polymerase chain reaction. Five matched FF and FFPE ovarian serous adenocarcinoma samples, as well as a set of normal ovary samples, were profiled using whole genome Agilent microarrays. Reproducibility of the FF and FFPE replicates was measured using Pearson correlation, whereas comparison between the FF and FFPE samples was done using a Z-score analysis.

Results

Data analysis showed high reproducibility of expression within each FF and FFPE method, whereas matched FF and FFPE pairs demonstrated lower similarity, emphasizing an inherent difference between the two sample types. Z-score analysis of matched FF and FFPE samples revealed good concordance of top 100 differentially expressed genes with the highest correlation of 0.84. Genes characteristic of ovarian serous adenocarcinoma, including a well known marker CLDN3, as well as potentially some novel markers, were identified by comparing gene expression profiles of ovarian adenocarcinoma to those of normal ovary.

Conclusion

Conclusively, we showed that systematic assessment of FFPE samples at the RNA level is essential for obtaining good quality gene expression microarray data. We also demonstrated that profiling of not only FF but also of FFPE samples can be successfully used to identify differentially expressed genes characteristic of ovarian carcinoma.

Thyrotropin-Releasing Hormone Is Induced in the Left Ventricle of Rats With Heart Failure and Can Provide Inotropic Support to the Failing Heart

Background— We reported previously that left ventricular gene expression for thyrotropin-releasing hormone (TRH) precursor was increased in rats with heart failure 8 weeks after myocardial infarction (MI) and that early ACE inhibition tended to cause further myocardial induction of this gene.

Methods and Results— Here, we show that after MI, the expression of pro-TRH is induced in the heart coordinately with the protease PC1, an important enzyme in TRH biosynthesis. Pro-TRH gene expression was induced in cardiac interstitial cells after MI, and this effect was restricted to the heart, because no increase in TRH mRNA abundance was observed in the hypothalamus, kidney, or lung. Transcript abundance of pro-TRH can be increased in cultured cardiac fibroblasts by several adrenergic agonists, indicating that the adrenergic axis may play a regulatory role in cardiac TRH production. Acute intravenous administration of TRH to rats with ischemic cardiomyopathy caused a significant increase in heart rate, mean arterial pressure, cardiac output, stroke volume, and cardiac contractility.

Conclusions— Taken together, these results indicate that TRH is specifically induced in the heart after MI and that it can increase cardiac performance in rats with ischemic cardiomyopathy. Thus, in addition to catecholamine and angiotensin II, pro-TRH/TRH may be another important axis that affects hemodynamics and cardiac function in heart failure.