Sherry Zhang

Shared Gene Expression Alterations in Nasal and Bronchial Epithelium for Lung Cancer Detection

Background: We previously derived and validated a bronchial epithelial gene expression biomarker to detect lung cancer in current and former smokers. Given that bronchial and nasal epithelial gene expression are similarly altered by cigarette smoke exposure, we sought to determine if cancer-associated gene expression might also be detectable in the more readily accessible nasal epithelium. Methods: Nasal epithelial brushings were prospectively collected from current and former smokers undergoing diagnostic evaluation for pulmonary lesions suspicious for lung cancer in the AEGIS-1 (n = 375) and AEGIS-2 (n = 130) clinical trials and gene expression profiled using microarrays. All statistical tests were two-sided. Results: We identified 535 genes that were differentially expressed in the nasal epithelium of AEGIS-1 patients diagnosed with lung cancer vs those with benign disease after one year of follow-up (P < .001). Using bronchial gene expression data from the AEGIS-1 patients, we found statistically significant concordant cancer-associated gene expression alterations between the two airway sites (P < .001). Differentially expressed genes in the nose were enriched for genes associated with the regulation of apoptosis and immune system signaling. A nasal lung cancer classifier derived in the AEGIS-1 cohort that combined clinical factors (age, smoking status, time since quit, mass size) and nasal gene expression (30 genes) had statistically significantly higher area under the curve (0.81; 95% confidence interval [CI] = 0.74 to 0.89, P = .01) and sensitivity (0.91; 95% CI = 0.81 to 0.97, P = .03) than a clinical-factor only model in independent samples from the AEGIS-2 cohort. Conclusions: These results support that the airway epithelial field of lung cancer–associated injury in ever smokers extends to the nose and demonstrates the potential of using nasal gene expression as a noninvasive biomarker for lung cancer detection.

Abstract 2878: Development of the pre-cancer genome atlas (PCGA) for squamous cell lung carcinoma

Squamous cell cancer (SCC) of the lung is a leading cause of cancer mortality in the US, due to late stage diagnosis and lack of effective treatments. Lung SCC arises in the epithelial layer of the bronchial airways and is often preceded by the development of premalignant lesions (PMLs). The molecular events involved in the progression of PMLs to lung SCC are not clearly understood and not all PMLs go on to form carcinoma. By molecularly characterizing PMLs and non-lesion areas in the airway of individuals with PMLs we hypothesize that we will be able to identify early events in the process of lung carcinogenesis that lead to SCC. We used next-generation sequencing to profile bronchial brushings and biopsies obtained from high-risk smokers undergoing lung cancer screening by auto-fluorescence bronchoscopy and CT at the Roswell Park Cancer Institute in Buffalo, NY. For each subject (n = 26), we sampled the PML(s) and the mainstem bronchus repeatedly over time (394 +/- 170 days) with serial bronchoscopies (5 +/- 3 biopsies/subject) as the PML progressed towards or regressed away from frank malignancy. mRNA-Seq (n = 192) and miRNA-Seq (n = 183) were performed on the endobronchial biopsies and brushings and exome-Seq was performed on blood DNA from these subjects. RNA-seq data was aligned to the hg19 and gene/transcript levels were summarized using RSEM/Ensembl 74 or Bedtools/ mirBase 18. Single nucleotide variants were quantified using a modified PRADA pipeline and GATK. We identified gene and miRNA expression changes as well as pathways that are associated with biopsy histological grade as well as progressive/stable disease. HE 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2878. doi:10.1158/1538-7445.AM2015-2878

Molecular Subtyping reveals Immune Alterations associated with Progression of Bronchial Premalignant Lesions

Bronchial premalignant lesions (PMLs) are precursors of lung squamous cell carcinoma, but have variable outcome, and we lack tools to identify and treat PMLs at highest risk for progression to invasive cancer. Profiling endobronchial biopsies of PMLs obtained from high-risk smokers by RNA-Seq identified four PML subtypes with differences in epithelial and immune processes. One molecular subtype (Proliferative) is enriched with dysplastic lesions and exhibits up-regulation of metabolic and cell cycle pathways and down-regulation of ciliary processes. RNA-Seq profiles from normal-appearing uninvolved large airway brushings could identify subjects with Proliferative lesions with high specificity. Expression of interferon signaling and antigen processing/presentation pathways are decreased in progressive/persistent Proliferative lesions and immunofluorescence indicates a depletion of innate and adaptive immune cells in these lesions. Molecular biomarkers measured in PMLs or the uninvolved airway can enhance histopathological grading and suggests that immunoprevention strategies may be effective in intercepting the progression of PMLs to lung cancer.

Abstract A05: Bronchial premalignant lesions have distinct molecular subtypes associated with future histologic progression

Squamous cell carcinoma (SCC) of the lung is a leading cause of cancer mortality in the U.S. due to late-stage diagnosis and lack of effective treatments. Lung SCC arises in the epithelial layer of the bronchial airways and is often preceded by the development of premalignant lesions (PMLs). The molecular alterations involved in the progression of PMLs to lung SCC are not clearly understood as not all PMLs progress to carcinoma. We hypothesize that molecular characterization of PMLs and nonlesion areas will allow us to identify alterations associated with histology and lesion progression. We used mRNA sequencing to profile biopsies obtained from high-risk smokers undergoing lung cancer screening by auto-fluorescence bronchoscopy and CT at the Roswell Park Cancer Institute in Buffalo, NY. For each subject (n=49), a brushing of the airway field (normal fluorescing area) and endobronchial biopsies were collected over time in repeat locations with serial bronchoscopies. The discovery cohort, included 29 subjects, 197 biopsies, and 91 brushes, while the validation cohort included 20 subjects, 111 biopsies and 49 brushes. The mRNA-Seq data were aligned to hg19 using STAR, and gene/transcript levels were summarized using RSEM. Immune, stromal, and epithelial cell content were inferred using xCell. Biopsy molecular subtypes were discovered using consensus clustering in the discovery cohort and used to train a nearest centroid subtype predictor to assign subtypes in the validation cohort and the brushes. We identified four distinct molecular subtypes in the discovery cohort bronchial biopsies using genes (n=3936) co-expressed across the the discovery cohort brushes and biopsies and two additional RNA-seq lung SCC-related datasets. One of the four molecular subtypes is enriched (p We have identified four molecular subclasses of premalignant lung SCC lesions that may associate with prognosis. Molecular classification of PMLs may lead to biomarkers of future disease progression that could be used to stratify patients into prevention trials and to monitor efficacy of the treatment. Additionally, the results suggest that personalized lung cancer chemoprevention that targets specific cancer-related pathways or the immune system may have potential therapeutic benefits. Citation Format: Jennifer E. Beane, Sarah Mazzilli, Ania Tassinari, Joshua Campbell, Christopher Moy, Michael Schaffer, Catalina Perdomo, David Jenkins, Mary Beth Pine, Gang Liu, Sherry Zhang, Hangqio Lin, Jessica Vick, Evan Johnson, Suso Platero, Christopher Stevenson, Marc Lenburg, Mary Reid, Samjot Dhillon, Avrum Spira. Bronchial premalignant lesions have distinct molecular subtypes associated with future histologic progression [abstract]. In: Proceedings of the Fifth AACR-IASLC International Joint Conference: Lung Cancer Translational Science from the Bench to the Clinic; Jan 8-11, 2018; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(17_Suppl):Abstract nr A05.

Abstract 1954: microRNA expression in bronchial epithelium for lung cancer detection

Introduction We have previously shown that gene expression alterations in the cytologically-normal mainstem bronchus can be leveraged as a biomarker for lung cancer detection (Silvestri et al. NEJM 2015), a test that is now used clinically. Extending this approach, we hypothesized that bronchial microRNA (miRNA) expression is altered in patients with lung cancer and that incorporating miRNA expression into the mRNA classifier may improve its performance. Methods Using bronchial brushes collected prospectively from current and former smokers undergoing bronchoscopy for suspect lung cancer across 28 medical centers as part of the AEGIS 1 and 2 clinical trials, we profiled miRNA expression via small RNA sequencing of 341 patients for which gene expression data was also available on the same bronchial brush sample. Patients were followed for up to one year post-bronchoscopy until a final diagnosis was established. 138 patients from AEGIS 1 (88 cancer-positive and 50 cancer-free) served as a discovery set, while other 203 patients from AEGIS 1 and 2 (103 cancer-positive and 100 cancer-free) were used as an independent test set. First, we identified miRNAs whose expression is associated with cancer by linear modeling in the discovery set. We next explored the relationships between the expression of these miRNAs and their predicted mRNA targets. Lastly, using logistic regression, we incorporated a cancer miRNA feature into our bronchial gene-expression classifier (Silvestri et al., NEJM 2015) and validated its performance in the test set. Results We found that expression profiles of 42 miRNAs were associated with cancer status in the discovery set (p Conclusions We have established that there are alterations in miRNA expression in the cytologically normal mainstem bronchus of smokers with lung cancer. Importantly, we demonstrated the potential of these miRNA alterations to improve the performance of an existing bronchial gene expression biomarker for lung cancer detection. Citation Format: Ana Brandusa Pavel, Joshua Campbell, Gang Liu, Sherry Zhang, Hanqiao Liu, Ji Xiao, Kate Porta, Duncan Whitney, Steven Dubinett, David Elashoff, Marc Lenburg, Avrum Spira. microRNA expression in bronchial epithelium for lung cancer detection. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1954.

Abstract 3077: Dysregulation of microRNA-mRNA regulatory networks in the bronchial airway epithelium of smokers with lung cancer

We have previously shown that gene expression alterations in cytologically normal epithelial cells from the bronchial airway can be used as an early detection biomarker for lung cancer in smokers. We hypothesize that bronchial epithelial expression of microRNAs, as regulators of gene expression, may also be affected by the presence of cancer and may regulate some of these gene expression differences. We propose a novel method to identify microRNAs functionally associated with disease that leverages the relationship between microRNA and mRNA expression by determining the differential connectivity (DC) of microRNA-mRNA association networks between disease and normal states. Bronchial epithelial brushes were collected from 220 former and current smokers who underwent bronchoscopy for suspicion of lung cancer (120 lung cancer patients and 100 healthy controls). For these subjects, we profiled microRNA expression via small RNA sequencing and gene expression via microarray. Each microRNA node is assigned a DC score, which captures the overall difference in the pairwise microRNA-gene correlation strengths between lung cancer and control subjects. We quantify the change in both the directionality and strength of the correlations between a microRNA and the gene nodes. Then, the observed DC scores are compared to the DC scores obtained with permuted class labels to identify microRNAs with signinficant disease-specific differences in microRNA-mRNA connectivity. The proposed DC method identifies 54 microRNAs which are significantly differentially connected in lung cancer cases compared to controls (FDR We propose a novel approach for integrating microRNA and gene expression data to identify disease-associated changes in gene regulation by microRNAs and show that the microRNA-mRNA networks are significantly different between disease and normal states. These data suggest that changes in microRNA expression may drive some of the gene expression alterations observed in the cytologically normal epithelium from the proximal airway of patients with lung cancer and that airway microRNA-mRNA expression changes may ultimately serve as a biomarker for lung cancer detection. Citation Format: Ana Brandusa Pavel, Joshua D. Campbell, Gang Liu, Sherry Zhang, Hanqiao Liu, Lingqi Luo, Ji Xiao, Kate Porta, Duncan Whitney, Steven Dubinett, David Elashoff, Marc E. Lenburg, Avrum Spira. Dysregulation of microRNA-mRNA regulatory networks in the bronchial airway epithelium of smokers with lung cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3077. doi:10.1158/1538-7445.AM2015-3077

Abstract 2352: Mapping the airway-wide molecular field of injury in smokers with lung cancer

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA Lung cancer mortality is the leading cause of cancer death in the United States in part because diagnosis occurs after regional or distant metastasis of the disease. Identifying effective early detection biomarkers is crucial for improving lung cancer clinical management. Moreover, molecular biomarkers for early disease detection may provide insight into the molecular pathways associated with disease development and progression. Our lab has shown that smoking-induced gene expression alterations are mirrored in the epithelia of the mainstem bronchus, buccal and nasal cavity. We have additionally demonstrated that gene-expression profiles in cytologically normal mainstem bronchial epithelium can serve as an early diagnostic biomarker for lung cancer. Here we expand on our previous work by spatially mapping the molecular field of injury throughout the entire respiratory tract in smokers with lung cancer. Using Affymetrix Gene ST 2.0 arrays, we profiled genome-wide gene-expression in 1) lung lesions and adjacent normal lung obtained from smokers undergoing surgical resection, 2) epithelial brushings obtained at intraoperative bronchoscopy from the nasal epithelium, main carina and ipsilateral and contralateral proximal and distal bronchi (relative to the location of the resected lung lesion), and 3) epithelial brushings obtained at lobectomy from sub-segmental bronchus (adjacent to tumor). Linear modeling approaches comparing the airways and tumors of patients with cancer to those with benign lung disease were used to explore relationships in cancer-specific gene-expression alterations across sites within the respiratory tract. We found that genes upregulated in the small airways leading to the tumor were enriched in genes upregulated in the mainstem bronchus and main carina of smokers with lung cancer. In addition, genes upregulated in the bronchus and main carina of smokers with lung cancer showed enrichment among cancer associated genes elevated in the nose. Furthermore, a linear mixed effects model uncovered genes and pathways which change in expression in a gradient-like manner as distance from the tumor increases. Our findings suggest that the molecular field of injury encompasses airway-wide alterations throughout the entire respiratory tract of smokers with lung cancer as well as gradient profiles that change with respect to proximity of the nearby tumor. These molecular alterations may ultimately serve as early detection biomarkers for lung cancer and provide new insights into early stages of lung carcinogenesis. Citation Format: Rebecca Kusko, Christina Anderlind, Gerald Wang, Sherry Zhang, W. Dean Wallace, Tonya Wasler, Michael Ebright, Melinda M. Garcia, Rosana Eisenberg, Gina Lee, Gang Liu, David Elashoff, Neda Kalhor, Cesar Moran, Reza Mehran, Junya Fujimoto, Pierre P. Massion, Steven Dubinett, Ignacio Wistuba, Marc Lenburg, Humam Kadara, Avrum Spira. Mapping the airway-wide molecular field of injury in smokers with lung cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2352. doi:10.1158/1538-7445.AM2014-2352

Abstract 1485: Biomarker development for lung cancer diagnosis using integrative microRNA and gene expression networks

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA Introduction: We have previously shown that smoking creates a “molecular field of injury” throughout the epithelial cells that line the respiratory tract and that gene-expression alterations in the cytologically-normal mainstem bronchus epithelium can serve as an early detection biomarker for lung cancer. We hypothesize that microRNAs (miRNAs) regulate these airway gene expression changes and that miRNA expression differences in this tissue can be used as biomarkers for lung cancer diagnosis. Methods: We profiled miRNA expression via small RNA sequencing in bronchial epithelial brushes collected from the mainstem bronchus of 230 subjects undergoing bronchoscopy for suspect lung cancer and gene expression (mRNA) via microarray for 201 matched samples. Bilal et al. (2013) have shown that incorporating biological knowledge into model building improves prediction. Therefore, we sought to test the hypothesis that including information about the expression levels of the predicted mRNA targets of miRNA may improve miRNA feature selection and aid in interpretation of signatures. We used mirConnX which combines miRNA with mRNA data to create disease-specific, genome-wide regulatory networks. Results: First, we show that there is a miRNA expression signal for cancer: across many combinations of feature selection methods, predictive models and different parameters within 100 bootstraps to predict cancer phenotype, we find the AUC values obtained are consistently higher compared to the random control procedure where we randomly shuffle the class labels (p < 0.001). Second, using a training set of 106 samples, we built networks separately for cancer and non-cancer samples, using 10-fold cross validation in order to determine robust cancer and non-cancer specific features. The disease-state specific networks are then aggregated by taking the overlapping features across the ten folds. Next, we select the non-overlapping features (miRNAs and genes) between cancer and non-cancer as those that capture the difference between the two phenotypes. The selected genes are enriched for relevant cancer related pathways, including KEGG pathways in cancer (p = 0.0003), cell cycle (p = 0.008), WNT signaling (p = 0.0001), basal cell carcinoma (p = 0.023), MAPK signaling pathway (p = 0.024), TGF-beta signaling pathway (p = 0.00014), p53 signaling pathway (p = 0.087) etc. Most importantly, the miRNA features from these disease specific networks are found to have higher predictive power (highest AUC 0.72) compared to all miRNA features (highest AUC 0.57), on a second set of 68 samples in cross-validation. Conclusion: Using novel integrative analysis, we improved miRNA biomarker prediction. This is the first report of cancer-associated miRNA expression differences in cytologically normal bronchial epithelium, for lung cancer diagnosis, and it extends our previous work focused on mRNA biomarkers from this tissue. Citation Format: Ana Pavel, Joshua Campbell, Gang Liu, Sherry Zhang, Hanqiao Liu, Steven Dubinett, David Elashoff, Kate Porta, Duncan Whitney, Marc Lenburg, Avrum Spira. Biomarker development for lung cancer diagnosis using integrative microRNA and gene expression networks. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1485. doi:10.1158/1538-7445.AM2014-1485

Abstract A27: Airway molecular alterations associated with premalignant lesion progression and lung cancer development

Recently, the National Lung Screening Trial reported a 20% reduction in lung cancer mortality and lung cancer chemoprevention trials targeting the arachidonic acid pathway have demonstrated decreases in lung cancer associated markers. These studies highlight possibilities for future reductions in lung cancer mortality through early detection and chemoprevention. Our group has previously identified smoking- and lung cancer-specific gene expression alterations in cytologically normal airway epithelial cells that can serve as a clinically-relevant biomarker for the early detection of lung cancer. Here, in an effort that could lead to markers of lung cancer risk, we identify changes in these cells associated with regression of premalignant airway lesions. Airway epithelial cells were collected via bronchoscopy from patients with bronchial dysplasia at baseline, on-treatment, and post-treatment with green tea extract (GTE) or placebo ranging from 2 to 6 months (n=27 patients, n=63 samples). RNA from the samples was processed and hybridized to Affymetrix Human Gene 1.0 ST microarrays. A linear mixed effect model was used to identify a gene expression signature predictive of subsequent dysplasia regression. Further a paired t-test was used to identify genes associated with dysplasia regression over time. Using gene set enrichment analysis (GSEA) we identified that the baseline dysplasia regression signature was enriched (FDR<0.05) among genes whose altered expression was associated with: dysplasia regression over time; the presence or future development of lung cancer; and human bronchial biopsies at successive morphological stages of lung squamous carcinogenesis. The genes associated with dysplasia regression were validated small cohorts of independent samples from chemoprevention trials testing Sulindac, Myo-inositol, and GTE. Analysis of the Connectivity Map identified compounds that reverse the dysplasia regression signature in vitro and are therefore candidate chemoprevention agents. Our studies suggest that the airway “field of injury” is modulated by bronchial premalignant lesions. The molecular signatures identified may be important tools for stratifying high-risk smokers for chemoprevention trials, as surrogate endpoints of efficacy in these trials, and for identification of novel molecular targets for chemoprevention. In addition, the molecular signature of regression of airway dysplasia may have additional utility as a biomarker predictive of the presence of or future lung cancer development. Citation Format: Jennifer Ebel Beane, Kahkeshan Hijazi, Katrina Steiling, Gang Liu, Sherry Zhang, Stephen Lam, Marc Lenburg. Airway molecular alterations associated with premalignant lesion progression and lung cancer development. [abstract]. In: Proceedings of the Eleventh Annual AACR International Conference on Frontiers in Cancer Prevention Research; 2012 Oct 16-19; Anaheim, CA. Philadelphia (PA): AACR; Cancer Prev Res 2012;5(11 Suppl):Abstract nr A27.