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.

The beagle dog MicroRNA tissue atlas: identifying translatable biomarkers of organ toxicity

Background

MicroRNAs (miRNA) are varied in length, under 25 nucleotides, single-stranded noncoding RNA that regulate post-transcriptional gene expression via translational repression or mRNA degradation. Elevated levels of miRNAs can be detected in systemic circulation after tissue injury, suggesting that miRNAs are released following cellular damage. Because of their remarkable stability, ease of detection in biofluids, and tissue specific expression patterns, miRNAs have the potential to be specific biomarkers of organ injury. The identification of miRNA biomarkers requires a systematic approach: 1) determine the miRNA tissue expression profiles within a mammalian species via next generation sequencing; 2) identify enriched and/or specific miRNA expression within organs of toxicologic interest, and 3) in vivo validation with tissue-specific toxicants. While miRNA tissue expression has been reported in rodents and humans, little data exists on miRNA tissue expression in the dog, a relevant toxicology species. The generation and evaluation of the first dog miRNA tissue atlas is described here.

Results

Analysis of 16 tissues from five male beagle dogs identified 106 tissue enriched miRNAs, 60 of which were highly enriched in a single organ, and thus may serve as biomarkers of organ injury. A proof of concept study in dogs dosed with hepatotoxicants evaluated a qPCR panel of 15 tissue enriched miRNAs specific to liver, heart, skeletal muscle, pancreas, testes, and brain. Dogs with elevated serum levels of miR-122 and miR-885 had a correlative increase of alanine aminotransferase, and microscopic analysis confirmed liver damage. Other non-liver enriched miRNAs included in the screening panel were unaffected. Eli Lilly authors created a complimentary Sprague Dawely rat miRNA tissue atlas and demonstrated increased pancreas enriched miRNA levels in circulation, following caerulein administration in rat and dog.

Conclusion

The dog miRNA tissue atlas provides a resource for biomarker discovery and can be further mined with refinement of dog genome annotation. The 60 highly enriched tissue miRNAs identified within the dog miRNA tissue atlas could serve as diagnostic biomarkers and will require further validation by in vivo correlation to histopathology. Once validated, these tissue enriched miRNAs could be combined into a powerful qPCR screening panel to identify organ toxicity during early drug development.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2958-x) contains supplementary material, which is available to authorized users.

Abstract A1-66: Leveraging Gene Expression in the Bronchial Airway to Develop a Nasal Biomarker for Early Detection of Lung Cancer

Rationale: Lung cancer results in five times more deaths per year than car accidents in the United States. Approximately 57% of lung cancers diagnosed this year will be diagnosed at a late stage and these patients will exhibit a 5-year survival rate of only 4%. Annual screening of high-risk current and former smokers by chest-CT can reduce cancer mortality, however this procedure has a 95% false positive rate. It is therefore critical to develop methods to rapidly and accurately determine which patients with nodules on chest CT have lung cancer and potentially spare those with benign disease an unnecessary invasive procedure. We have previously demonstrated that specific gene expression alterations in cytologically normal bronchial epithelial cells from patients with lung cancer can be leveraged to form a clinically informative lung cancer biomarker in the population of patients undergoing bronchoscopy for suspect lung cancer. We hypothesized that there might be similar expression differences in nasal epithelium and that these could form the basis of a less invasive test that could be applied more broadly to individuals with screen detected nodules on chest CT.

Methods: Bronchial (n=676) and nasal (n=280) epithelial brushings were collected from current and former smokers undergoing bronchoscopy for clinical suspicion of lung cancer within the AEGIS clinical trial. 271 subjects had matched bronchial and nasal samples. RNA was extracted and hybridized to Affymetrix Human Gene ST 1.0 Arrays. To establish a connection between bronchial and nasal epithelial gene expression signal for cancer, we first applied the bronchial gene expression-based diagnostic test, BronchoGen, directly to our nasal cohort. Gene Set Enrichment Analysis was then used to determine the concordance of cancer signal between the bronchial and nasal epithelium. To develop the nasal gene expression biomarker for lung cancer detection, we examined the correlation of each gene between the bronchial and nasal epithelium as well as the significance of each gene's association with cancer in each tissue. Genes passing our selection criteria were passed to a biomarker discovery pipeline in which we examined the performance of different biomarker algorithm configurations (e.g. feature-selection algorithms, classification algorithms, and other biomarker parameters) using cross-validation.

Results: Direct application of BronchoGen to our nasal cohort resulted in an AUC of 0.64 on a set of NE samples (n=110) with a matched bronchial sample in the training set used to develop the test. On an independent set of nasal samples (n=109), BronchoGen achieved an AUC of 0.67. Gene Set Enrichment Analysis revealed high levels of concordance between cancer-associated nasal and bronchial gene expression. Using a cross-validation approach, we found that nasal biomarkers built from sets of genes showing significant correlation (p&lt;0.05) between the bronchial and nasal epithelium as well as significance for cancer in both tissues (p&lt;0.05) perform better, on average, than biomarkers build from genes significant for cancer (p&lt;0.05) in the nasal epithelium alone.

Conclusions: Given the larger sample size, more isolated location in the airway, and higher RIN scores that characterize the bronchial cohort, we sought to leverage bronchial airway epithelial gene-expression to inform which genes in the nasal epithelium should be indicative of the presence of cancer. We have shown that gene expression in the nasal epithelium reflects the presence of lung cancer and can serve as a diagnostic biomarker. We have further demonstrated concordance between bronchial and nasal airway gene expression differences associated with lung cancer. These results suggest the potential to develop a robust nasal gene expression biomarker for lung cancer diagnosis that leverages cancer-associated gene expression differences occurring at other airway sites.

Citation Format: Joseph F. Perez-Rogers, Joseph Gerrein, Christina Anderlind, Rebecca L. Kusko, Joshua D. Campbell, Teresa W. Wang, Kate Porta, Duncan Whitney, Avrum Spira, Marc Lenburg. Leveraging Gene Expression in the Bronchial Airway to Develop a Nasal Biomarker for Early Detection of Lung Cancer. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A1-66.

Abstract B1-50: Leveraging gene expression in the bronchial airway to develop a nasal biomarker for early detection of lung cancer

Rationale: Lung cancer results in five times more deaths per year than car accidents in the United States. Approximately 57% of lung cancers diagnosed this year will be diagnosed at a late stage and these patients will exhibit a 5-year survival rate of only 4%. Annual screening of high-risk current and former smokers by chest-CT can reduce cancer mortality, however this procedure has a 95% false positive rate. It is therefore critical to develop methods to rapidly and accurately determine which patients with nodules on chest CT have lung cancer and potentially spare those with benign disease an unnecessary invasive procedure. We have previously demonstrated that specific gene expression alterations in cytologically normal bronchial epithelial cells from patients with lung cancer can be leveraged to form a clinically informative lung cancer biomarker in the population of patients undergoing bronchoscopy for suspect lung cancer. We hypothesized that there might be similar expression differences in nasal epithelium and that these could form the basis of a less invasive test that could be applied more broadly to individuals with screen detected nodules on chest CT.

Methods: Bronchial (n=676) and nasal (n=280) epithelial brushings were collected from current and former smokers undergoing bronchoscopy for clinical suspicion of lung cancer within the AEGIS clinical trial. 271 subjects had matched bronchial and nasal samples. RNA was extracted and hybridized to Affymetrix Human Gene ST 1.0 Arrays. To establish a connection between bronchial and nasal epithelial gene expression signal for cancer, we first applied the bronchial gene expression based diagnostic test, BronchoGen, directly to our nasal cohort. Gene Set Enrichment Analysis was then used to determine the concordance of cancer signal between the bronchial and nasal epithelium. To develop the nasal gene-expression biomarker for lung cancer detection, we examined the correlation of each gene between the bronchial and nasal epithelium as well as the significance of each gene's association with cancer in each tissue. Genes passing our selection criteria were passed to a biomarker discovery pipeline in which we examined the performance of different biomarker algorithm configurations (e.g. feature-selection algorithms, classification algorithms, and other biomarker parameters) using cross-validation.

Results: Direct application of BronchoGen to our nasal cohort resulted in an AUC of 0.64 on a set of NE samples (n=110) with a matched bronchial sample in the training set used to develop the test. On an independent set of nasal samples (n=109), BronchoGen achieved an AUC of 0.67. Gene Set Enrichment Analysis revealed high levels of concordance between cancer-associated nasal and bronchial gene expression. Using a cross-validation approach, we found that nasal biomarkers built from sets of genes showing significant correlation (p&lt;0.05) between the bronchial and nasal epithelium as well as significance for cancer in both tissues (p&lt;0.05) perform better, on average, than biomarkers build from genes significant for cancer (p&lt;0.05) in the nasal epithelium alone.

Conclusions: Given the larger sample size, more isolated location in the airway, and higher RIN scores that characterize the bronchial cohort, we sought to leverage bronchial airway epithelial gene expression to inform which genes in the nasal epithelium should be indicative of the presence of cancer. We have shown that gene expression in the nasal epithelium reflects the presence of lung cancer and can serve as a diagnostic biomarker. We have further demonstrated concordance between bronchial and nasal airway gene expression differences associated with lung cancer. These results suggest the potential to develop a robust nasal gene expression biomarker for lung cancer diagnosis that leverages cancer-associated gene expression differences occurring at other airway sites.

Citation Format: Joseph F. Perez-Rogers, Joseph Gerrein, Christina Anderlind, Rebecca L. Kusko, Joshua D. Campbell, Teresa Wang, Kate Porta, Duncan Whitney, Avrum Spira, Marc Lenburg. Leveraging gene expression in the bronchial airway to develop a nasal biomarker for early detection of lung cancer. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B1-50.

Abstract 1574: Leveraging bronchial airway gene expression to develop a nasal biomarker for lung cancer detection

Rationale: Using nasal gene expression to predict the presence of lung cancer would offer a less invasive alternative to diagnostic approaches we have pioneered using bronchial airway epithelial (BE) gene expression. We have previously demonstrated that cytologically normal BE and nasal epithelial (NE) cells harbor gene expression differences that reflect tobacco-related lung disease and that these changes in the BE form the basis of a clinically informative lung cancer biomarker. Given the concordance of BE and NE gene-expression, we hypothesized that gene signatures associated with the presence of lung cancer extend from the airway to the nose and that lung cancer associated BE gene-expression could be leveraged to develop more accurate nasal lung cancer biomarkers.

Methods: BE (n = 676) and NE (n = 280) brushings were collected from current and former smokers undergoing bronchoscopy for clinical suspicion of lung cancer. We leveraged two methods to determine the concordance between BE and NE gene-expression signal for cancer. First we applied the bronchial gene expression-based diagnostic test directly to our nasal cohort. Second, we used Gene Set Enrichment Analysis (GSEA) to quantify the relationship between the BE and NE. To develop the nasal gene expression biomarker, we examined the correlation of each gene between the BE and NE. Genes passing our selection criteria were passed to a biomarker discovery pipeline in which we examined the performance of different biomarker algorithm configurations using cross-validation.

Results: Direct application of the bronchial airway gene-expression classifier to an independent set of nasal samples (n = 109) resulted in an AUC of 0.67. GSEA revealed high concordance (p&lt;0.001) between cancer-associated nasal and bronchial gene expression profiles from the same patients. Using a cross-validation approach, we found that nasal biomarkers built from sets of genes showing significant correlation (p&lt;0.05) between the BE and NE as well as significance for cancer in both tissues (p&lt;0.05) perform better, on average, than biomarkers built from genes significant for cancer (p&lt;0.05) in the NE alone.

Conclusions. We have demonstrated concordance between BE and NE gene expression differences associated with lung cancer. We have further shown that gene expression in the NE reflects the presence of lung cancer and can serve as a diagnostic biomarker. These results demonstrate the feasibility of leveraging cancer-associated gene expression changes throughout the airway to develop a minimally invasive and robust nasal gene expression biomarker for lung cancer diagnosis.

Citation Format: Joseph Perez-Rogers, Joseph Gerrein, Christina Anderlind, Xiaohui Xiao, Hanqiao Liu, Rebecca Kusko, Joshua Campbell, Teresa Wang, Yuriy Alekseyev, Gang Liu, Kate Porta, Duncan Whitney, Avrum Spira, Marc Lenburg. Leveraging bronchial airway gene expression to develop a nasal biomarker for lung cancer detection. [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 1574. doi:10.1158/1538-7445.AM2015-1574

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.

Abstract 3173: Identification of miR-4423 as a primate-specific microRNA highly expressed in airway epithelium and associated with lung cancer

Smoking is a significant risk factor for lung cancer, the leading cause of cancer-related deaths worldwide. Our group has previously shown that epithelial gene expression is altered throughout the airway of smokers and that some of these changes are regulated by microRNAs. Moreover, we have previously identified gene expression differences in cytologically normal bronchial airway epithelial cells between smokers with and without lung cancer that can serve as an early diagnostic biomarker for lung cancer. Here, we use next-generation sequencing of small RNAs to identify novel microRNAs expressed in airway epithelium and associated with lung cancer. We identify miR-4423 as a primate-specific microRNA highly expressed in the airway epithelium. In vitro, the expression of miR-4423 increases as Normal Human Bronchial Epithelial cells are differentiated into mucociliary epithelium at an Air Liquid Interface, while its mRNA targets decrease in expression. Furthermore, the expression of miR-4423 is reduced in lung tumors and in the cytologically normal bronchial airway epithelium of smokers with lung cancer. In gain-of-function experiments, ectopic expression of miR-4423 in lung cancer cell lines resulted in reduced colony formation in soft agar. Taken together, these data support the power of next-generation sequencing in identifying novel cell type- specific transcripts and provides evidence that this newly characterized microRNA may play a role in promoting the differentiation and/or maintenance of airway epithelium, and can reduce anchorage-independent lung cancer cell growth.

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 3173. doi:1538-7445.AM2012-3173

Abstract 3989: Discovery of a novel airway microRNA associated with lung cancer using next generation sequencing

The goal of this study was to characterize the small RNA transcriptome and discover novel microRNAs (miRNAs) associated with lung cancer in human bronchial epithelial cells using massively parallel sequencing. To this end, small RNA (10-40 nts) was isolated from bronchial brushings obtained via bronchoscopy. Samples pooled from healthy non-smokers, healthy smokers, and smokers with and without lung cancer (n=3 per pool) were sequenced with ABI SOLiD, using extremely deep coverage for small RNA in human tissue, 60 million 36nt-long reads/pool. Reads were aligned to the human genome with Bowtie and novel miRNAs were predicted using the miRDeep algorithm. One of the predicted novel miRNAs was selected for experimental validation. In vitro expression of the putative novel microRNA precursor was assayed with and without the siRNA knock-down of Dicer, an enzyme that processes miRNA precursors into mature miRNAs. Tissue specificity of the putative novel miRNA was profiled across 23 human tissue types using qRT-PCR. Potential microRNA targets were identified using transient overexpression of the miRNA in a cell line combined with in silico algorithms.

We identified 143 miRNA that are differentially expressed in the airways of smokers with lung cancer (FC &gt; 2) in our cohort. The miRDeep algorithm identified 131 putative novel miRNAs across all samples, including 68 differentially expressed putative miRNA in the airways of lung cancer subjects (FC &gt; 2). In vitro expression of the putative miRNA was reduced after siRNA knockdown of DICER, providing strong evidence that the novel transcript is truly a miRNA. Out of 23 human tissue types assayed, the microRNA is expressed almost exclusively in the respiratory tract, with highest expression in the bronchus and nose and moderate expression in lung. Importantly, the expression of the miRNA is decreased significantly in lung tumors compared to adjacent normal tissue. In addition, the expression of the novel miRNA is decreased in the bronchial epithelium of smokers with lung cancer as compared to smokers without lung cancer. Overexpression of the novel miRNA in lung cancer cell line has identified putative mRNA targets that are associated with apoptosis and cell proliferation.

In summary, using next generation sequencing, we have identified airway miRNA expression profiles associated with lung cancer, and we discovered a novel miRNA whose expression is reduced in the airway and lung tissue of smokers with lung cancer. This miRNA may serve as a novel biomarker to identify smokers at high risk of developing lung cancer and may also provide new insights into the genomic regulatory networks that underlie lung cancer pathogenesis.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3989. doi:10.1158/1538-7445.AM2011-3989

Abstract 1987: RNA-seq of the bronchial airway transcriptome identifies novel gene and microRNA expression changes associated with smoking and lung cancer

Prior studies have shown that cigarette smoke creates a field of molecular injury in the airway epithelium. Using microarrays, our group has previously identified gene and microRNA expression differences in bronchial airway epithelial cells that are associated with smoking and lung cancer. We hypothesize that RNA-seq of the airway transcriptome will enhance our understanding of the response to tobacco smoke exposure and lung cancer pathogenesis by identifying mRNA splice variants, non-coding RNA, and novel RNA not interrogated by microarrays.

We profiled pooled bronchial airway epithelial cell brushings (n=3 patients/pool) obtained during bronchoscopy from healthy never and current smoker volunteers and smokers with and without lung cancer undergoing surgery for suspicion of lung cancer. The high MW fraction (&gt;200 bp) was amplified using a combination of oligo d(T) and random hexamers (NuGEN, San Carlos, CA) followed by library preparation with Illumina's mRNA Seq Library Prep Kit and sequencing using Illumina's Genome Analyzer generating ∼27-30 million 36 bp reads/sample. The low MW fraction (15-40 bp) was processed using ABI's Small RNA Library Sequencing Kit and sequenced using ABI's SOLiD system generating ∼50-90 million 35 bp reads/sample. The high MW reads were aligned to rRNA (5-13%), the human genome (33-40%), and to computationally generated splice junctions (1%) using BowTie. Differential gene and isoform expression was evaluated using Cufflinks and the R package Genominator. Low MW reads were aligned using both RNA2MAP and Geospiza to a filter containing rRNA, tRNA, and repeats (4-14%), to miRBase (4-10%), and the human genome minus miRBase sequences (4-8%). Expression values were calculated for microRNAs. We compared Affymetrix Exon 1.0 ST, HGU133A2, and Invitrogen miRNA microarrays to RNA-seq and found strong correlation for genes/miRNAs interrogated by microarrays, with most smoking- and cancer related changes in transcript expression being identified by sequencing and not by arrays. Genes found differentially expressed only by sequencing were validated by RT-PCR. RNA-seq also reveals differentially expressed isoforms, potential novel miRNAs, and several isoforms of known miRNAs which are being further investigated.

RNA-seq provides a comprehensive and high-resolution view of the airway transcriptome and will provide insights into the molecular field of injury induced by smoking and the pathogenesis of smoking-related lung disease.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1987.

Rapid diagnosis of late-onset Pompe disease by fluorometric assay of alpha-glucosidase activities in dried blood spots

The enzymatic defect in Pompe disease is insufficient lysosomal acid alpha-glucosidase (GAA) activity which leads to lysosomal glycogen accumulation. We recently introduced a simple and reliable method to measure GAA activity in dried blood spots using Acarbose, a highly selective alpha-glucosidase inhibitor, to eliminate isoenzyme interference. Here we demonstrate that this method efficiently detects late-onset Pompe patients who are frequently misdiagnosed by conventional methods due to residual GAA activity in other tissue types.