Lingqi Luo

Characterizing the Impact of Smoking and Lung Cancer on the Airway Transcriptome Using RNA-Seq

Cigarette smoke creates a molecular field of injury in epithelial cells that line the respiratory tract. We hypothesized that transcriptome sequencing (RNA-Seq) will enhance our understanding of the field of molecular injury in response to tobacco smoke exposure and lung cancer pathogenesis by identifying gene expression differences not interrogated or accurately measured by microarrays. We sequenced the high-molecular-weight fraction of total RNA (>200 nt) from pooled bronchial airway epithelial cell brushings (n = 3 patients per pool) obtained during bronchoscopy from healthy never smoker (NS) and current smoker (S) volunteers and smokers with (C) and without (NC) lung cancer undergoing lung nodule resection surgery. RNA-Seq libraries were prepared using 2 distinct approaches, one capable of capturing non-polyadenylated RNA (the prototype NuGEN Ovation RNA-Seq protocol) and the other designed to measure only polyadenylated RNA (the standard Illumina mRNA-Seq protocol) followed by sequencing generating approximately 29 million 36 nt reads per pool and approximately 22 million 75 nt paired-end reads per pool, respectively. The NuGEN protocol captured additional transcripts not detected by the Illumina protocol at the expense of reduced coverage of polyadenylated transcripts, while longer read lengths and a paired-end sequencing strategy significantly improved the number of reads that could be aligned to the genome. The aligned reads derived from the two complementary protocols were used to define the compendium of genes expressed in the airway epithelium (n = 20,573 genes). Pathways related to the metabolism of xenobiotics by cytochrome P450, retinol metabolism, and oxidoreductase activity were enriched among genes differentially expressed in smokers, whereas chemokine signaling pathways, cytokine–cytokine receptor interactions, and cell adhesion molecules were enriched among genes differentially expressed in smokers with lung cancer. There was a significant correlation between the RNA-Seq gene expression data and Affymetrix microarray data generated from the same samples (P < 0.001); however, the RNA-Seq data detected additional smoking- and cancer-related transcripts whose expression was were either not interrogated by or was not found to be significantly altered when using microarrays, including smoking-related changes in the inflammatory genes S100A8 and S100A9 and cancer-related changes in MUC5AC and secretoglobin (SCGB3A1). Quantitative real-time PCR confirmed differential expression of select genes and non-coding RNAs within individual samples. These results demonstrate that transcriptome sequencing has the potential to provide new insights into the biology of the airway field of injury associated with smoking and lung cancer. The measurement of both coding and non-coding transcripts by RNA-Seq has the potential to help elucidate mechanisms of response to tobacco smoke and to identify additional biomarkers of lung cancer risk and novel targets for chemoprevention. Cancer Prev Res; 4(6); 803–17. ©2011 AACR.

Assessment of microRNA differential expression and detection in multiplexed small RNA sequencing data

Small RNA sequencing can be used to gain an unprecedented amount of detail into the microRNA transcriptome. The relatively high cost and low throughput of sequencing bases technologies can potentially be offset by the use of multiplexing. However, multiplexing involves a trade-off between increased number of sequenced samples and reduced number of reads per sample (i.e., lower depth of coverage). To assess the effect of different sequencing depths owing to multiplexing on microRNA differential expression and detection, we sequenced the small RNA of lung tissue samples collected in a clinical setting by multiplexing one, three, six, nine, or 12 samples per lane using the Illumina HiSeq 2000. As expected, the numbers of reads obtained per sample decreased as the number of samples in a multiplex increased. Furthermore, after normalization, replicate samples included in distinct multiplexes were highly correlated (R > 0.97). When detecting differential microRNA expression between groups of samples, microRNAs with average expression >1 reads per million (RPM) had reproducible fold change estimates (signal to noise) independent of the degree of multiplexing. The number of microRNAs detected was strongly correlated with the log2 number of reads aligning to microRNA loci (R = 0.96). However, most additional microRNAs detected in samples with greater sequencing depth were in the range of expression which had lower fold change reproducibility. These findings elucidate the trade-off between increasing the number of samples in a multiplex with decreasing sequencing depth and will aid in the design of large-scale clinical studies exploring microRNA expression and its role in disease.

Comprehensive Genomic Profiling of the Lung Transcriptome in Emphysema and Idiopathic Pulmonary Fibrosis Using RNA-Seq

Methods 87 LGRC lung tissue samples were sequenced on the Illumina GAIIx, generating 75 nt paired-end reads and approximately 30-40 million reads per sample. Using gapped aligner Tophat, an average of 85% of reads aligned to hg19. Gene expression was quantified using Cufflinks and Ensembl59 known gene annotation (n = 24,249 genes). All lung tissue samples used in this study, as well as additional LGRC lung tissue samples, were run on Agilent V2 human whole genome arrays and Agilent V3 human miRNA microarrays.

Characterizing the small RNA transcriptome associated with COPD and ILD using next-generation sequencing

Background Despite the increasing public health burden associated with chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD), the molecular mechanisms responsible for the pathogenesis of these diseases remain unclear. The goal of this study was to comprehensively profile the lung small RNA transcriptome via next-generation sequencing, and elucidate microRNAs that might contribute to COPD and ILD pathogenesis.

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 3554: Gene and miRNA expression networks specific to never smoker lung adenocarcinoma

While smoking is well recognized as a major risk factor for lung cancer, there is a growing incidence of lung cancer in never smokers which is in turn the fifth leading cause of cancer-related death worldwide. Never smokers (NS) who develop lung cancer exhibit disparate profiles of somatic mutations and clinical responses to targeted therapy relative to lung cancer arising in current or former “ever” smokers (ES), suggesting that ES and NS lung cancer arise through distinct molecular processes. We therefore sought to characterize mRNA and miRNA expression differences specific to NS adenocarcinoma (AdC) to gain insights into the molecular differences underlying NS and ES AdC carcinogenesis. Total RNA was isolated from matched pairs of lung AdC tumor and adjacent histologically normal tissue obtained from 22 subjects (8 NS, 14 ES). Large and small RNA libraries were sequenced on the Illumina HiSeq 2000. Tumor-specific gene and miRNA expression differences between NS and ES were identified using linear mixed-effects ANOVA. MiRConnx was used to construct miRNA-mRNA networks. We identified 120 mRNA and 15 miRNA whose expression was modified uniquely in NS lung AdC. In the predicted miRNA-mRNA regulatory network, additional analysis pinpointed modulation of the development and cellular metabolism canonical pathway within genes connected to several of the differentially expressed miRNA (GATHER, p In summary, the construction of a miRNA-mRNA regulatory network has enabled us to identify molecular alterations that may be specific to NS lung AdC. Ultimately, these findings may serve to broaden the landscape of personalized therapeutic and treatment options by identifying targetable molecular interactions and therapeutic drug candidates for lung AdC in never smokers. Citation Format: Rebecca Kusko, Carly Garrison, Teresa Wang, Josh Campbell, Joseph Perez-Rogers, Lingqi Luo, Jennifer Beane, Gang Liu, Humam Kadara, Steven Belinsky, Marc E. Lenburg, Avrum Spira. Gene and miRNA expression networks specific to never smoker lung adenocarcinoma. [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 3554. doi:10.1158/1538-7445.AM2014-3554

Abstract 1948: Shared and distinct microRNA-expression alterations in lung adenocarcinoma from smokers vs. nonsmokers.

Rationale: While lung adenocarcinoma (ADC) is predominantly associated with the exposure to tobacco smoke, 10-15% of cases arise in never smokers. Small non-coding RNAs such as microRNAs (miRNAs) often act as oncogenes or tumor suppressors to regulate gene expression during disease, and may provide the critical insight needed to address the clinical and molecular disparities consistently observed in ADC of smokers and never smokers. We therefore sought to characterize the similarities and differences in the tumor-associated miRNA transcriptome between lung tumors from active, former, and never smokers. Methods: Total RNA was isolated from paired lung adenocarcinomas (purity ≥ 70%) and adjacent-normal lung tissues resected from 32 subjects with varied smoking statuses (n=8 active; n=11 former; n=13 never). Subjects were matched for gender and age. Small RNA libraries were generated and multiplexed 7-8 per lane for sequencing on the Illumina HiSeq 2000. Through a custom miRNA sequencing analysis pipeline, reads were trimmed, size-selected, and mapped to hg19 using Bowtie. Counts per mature miRNA from aligned reads were computed using Bedtools and a list of genomic features retrieved from miRBase v17. Differential expression analysis was conducted using a likelihood ratio test between two linear models: one adjusting for tumor and smoking status, another with an additional interaction term. Results: Small RNA sequencing generated an average of 10 million high quality miRNA reads per sample. Among the 1906 mature miRNAs examined, 554 miRNAs had at least an average of 20 counts across all samples. We identified 97 miRNAs (q Conclusions: Using small RNA sequencing, we have identified miRNAs that are markedly dysregulated in primary lung ADC tissues as compared to their histologically normal, adjacent counterparts. Subsets of these profiles are both shared and distinct between lung cancer cases that arise in smokers and nonsmokers. The ongoing integration of miRNA and large RNA sequencing data generated from these samples will inform our understanding of mechanisms that are specific to carcinogenesis in the presence or absence of tobacco smoke exposure. These results may yield novel targeted therapies for smoking or nonsmoking-specific ADC subtypes. Citation Format: Teresa Wang, Joshua Campbell, Rebecca Kusko, Lingqi Luo, Carmen Tellez, Gang Liu, Ji Xiao, Marc Lenburg, Steven Belinsky, Avrum Spira. Shared and distinct microRNA-expression alterations in lung adenocarcinoma from smokers vs. nonsmokers. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1948. doi:10.1158/1538-7445.AM2013-1948

Abstract 3154: Sequencing of the small RNA transcriptome in cytologically normal bronchial airway epithelium of smokers with and without lung cancer

Proceedings: AACR 103rd Annual Meeting 2012‐‐ Mar 31‐Apr 4, 2012; Chicago, IL Introduction: Based on the concept that cigarette smoke creates a molecular field of injury in epithelial cells throughout the respiratory tract, we have previously shown that mRNA expression differences in cytologically normal airway epithelial cells in patients with and without lung cancer can serve as a clinically-relevant lung cancer biomarker. MicroRNAs are short, non-coding RNAs that can each regulate the expression of hundreds of target genes and can be reliably detected in clinical samples with variable quality. The goal of this study is to generate a microRNA biomarker in the airway epithelium of smokers for the diagnosis of lung cancer. Methods: Cytologically-normal bronchial airway epithelial cells were collected via brushings of the mainstem bronchus of smokers undergoing fiberoptic bronchoscopy for suspicion of lung cancer (n=128). Subjects were followed after their bronchoscopy until a final diagnosis of lung cancer (n=75) or an alternate benign diagnosis (n=53) was made. The small RNA transcriptome ( 20). 98 of these microRNAs were differentially expressed between current and former smokers and 56 microRNAs differentially expressed in the airway epithelium of smokers with and without lung cancer (p<0.05; 18 expected by chance at this threshold). Conclusions: We have sequenced the small RNA transcriptome in the cytologically-normal proximal airway epithelium of smokers and have identified microRNA expression profiles associated with smoking status and/or a final diagnosis of lung cancer. In the future, a microRNA biomarker will be developed on these samples using procedures outlined in the MicroArray Quality Control (MAQC)-II project and tested on an independent cohort in order to confirm their ability to serve as an early diagnostic tool for lung cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3154. doi:1538-7445.AM2012-3154

Moving Beyond Gene Expression: Identification of Lung-Disease-Associated Novel Transcripts and Alternative Splicing by RNA Sequencing

Moving beyond gene expression: identification of lung-disease-associated novel transcripts and alternative splicing by RNA sequencing John Brothers II, Rebecca Kusko, Gang Liu, Lingqi Luo, Brenda Juan Guardela, John Tedrow, Yuriy Alekesyev, Ivana V Yang, Mick Correll, Mark Geraci, John Quackenbush, Frank Sciurba, Paola Sebastiani, Marc Lenburg, Naftali Kaminski, David A Schwartz, Avrum Spira, Jennifer Beane

Deep sequencing of the microRNA transcriptome in current, former, and never smokers with lung adenocarcinoma

Background Lung cancer is the leading cause of cancer-related death in the USA. While smoking is a major risk factor, about 10% to 15% of cases arise in never smokers. Small non-coding RNAs such as microRNAs (miRNAs) often act as oncogenes or tumor suppressors to regulate gene expression during disease, and represent attractive targets for lung cancer risk assessment and therapeutic intervention. We therefore sought to characterize the tumor-associated miRNA transcriptome of current, former and never smokers.