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Effect of active smoking on the human bronchial epithelium transcriptome Chari, Raj; Lonergan, Kim M; Ng, Raymond T; MacAulay, Calum; Lam, Wan L; Lam, Stephen Aug 29, 2007

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ralssBioMed CentBMC GenomicsOpen AcceResearch articleEffect of active smoking on the human bronchial epithelium transcriptomeRaj Chari*1, Kim M Lonergan1, Raymond T Ng2, Calum MacAulay3, Wan L Lam†1 and Stephen Lam†3Address: 1Department of Cancer Genetics and Developmental Biology, British Columbia Cancer Research Centre, Vancouver, BC, Canada, 2Department of Computer Science, University of British Columbia, Vancouver, BC, Canada and 3Department of Cancer Imaging, British Columbia Cancer Research Centre, Vancouver, BC, CanadaEmail: Raj Chari* - rchari@bccrc.ca; Kim M Lonergan - klonergan@bccrc.ca; Raymond T Ng - rng@cs.ubc.ca; Calum MacAulay - cmacaula@bccrc.ca; Wan L Lam - wanlam@bccrc.ca; Stephen Lam - slam@bccancer.bc.ca* Corresponding author    †Equal contributorsAbstractBackground: Lung cancer is the most common cause of cancer-related deaths. Tobacco smokeexposure is the strongest aetiological factor associated with lung cancer. In this study, using serialanalysis of gene expression (SAGE), we comprehensively examined the effect of active smoking bycomparing the transcriptomes of clinical specimens obtained from current, former and neversmokers, and identified genes showing both reversible and irreversible expression changes uponsmoking cessation.Results: Twenty-four SAGE profiles of the bronchial epithelium of eight current, twelve formerand four never smokers were generated and analyzed. In total, 3,111,471 SAGE tags representingover 110 thousand potentially unique transcripts were generated, comprising the largest humanSAGE study to date. We identified 1,733 constitutively expressed genes in current, former andnever smoker transcriptomes. We have also identified both reversible and irreversible geneexpression changes upon cessation of smoking; reversible changes were frequently associated witheither xenobiotic metabolism, nucleotide metabolism or mucus secretion. Increased expression ofTFF3, CABYR, and ENTPD8 were found to be reversible upon smoking cessation. Expression ofGSK3B, which regulates COX2 expression, was irreversibly decreased. MUC5AC expression wasonly partially reversed. Validation of select genes was performed using quantitative RT-PCR on asecondary cohort of nine current smokers, seven former smokers and six never smokers.Conclusion: Expression levels of some of the genes related to tobacco smoking return to levelssimilar to never smokers upon cessation of smoking, while expression of others appears to bepermanently altered despite prolonged smoking cessation. These irreversible changes may accountfor the persistent lung cancer risk despite smoking cessation.Background cancer-related deaths in the United States [1]. It has beenPublished: 29 August 2007BMC Genomics 2007, 8:297 doi:10.1186/1471-2164-8-297Received: 2 January 2007Accepted: 29 August 2007This article is available from: http://www.biomedcentral.com/1471-2164/8/297© 2007 Chari et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Page 1 of 13(page number not for citation purposes)Lung cancer has the highest mortality rate among all typesof malignancies, accounting for approximately 29% of allestimated that in 2006 alone, the number of new lungcancer cases will exceed 174,000 and approximatelyBMC Genomics 2007, 8:297 http://www.biomedcentral.com/1471-2164/8/297163,000 people will die of this disease [1]. Tobacco smok-ing accounts for 85% of the lung cancers. Former heavysmokers remain at an elevated risk for developing lungcancer even years after they stop smoking [2,3]. Fifty per-cent of newly diagnosed lung cancer patients are formersmokers [4]. It is therefore important to understand theeffects of tobacco smoking on the bronchial epithelium inboth active and former smokers.Recently, a large-scale microarray study characterized geneexpression differences between current, former, and neversmokers [5], and identified specific genes related to xeno-biotic functions, anti-oxidation, cell adhesion and elec-tron transport to be more highly expressed in currentsmokers relative to never smokers. Genetic regulators ofinflammation and putative tumor suppressor genesexhibited decreased expression in current smokers relativeto never smokers. Most significantly, a number of geneswere identified that exhibited irreversible expressionchanges upon smoking cessation.Additional reports have also identified increased expres-sion of various xenobiotic metabolic enzymes includingmembers of the cytochrome P450 (CYP) and glutathioneS-transferase (GST) families of proteins in response to cig-arette smoke exposure [5-10]. CYP enzymes mediate theconversion of benzo (a) pyrene and other polycyclic aro-matic hydrocarbons (PAH) to carcinogenic intermediatesthat interact with genomic DNA [8], thus contributing tothe formation of DNA adducts in smokers [11-13]. Mem-bers from both of the CYP and GST gene families havebeen implicated as potential susceptibility loci mediatedby the presence of single nucleotide polymorphisms(SNPs) leading to aberrant expression in response tosmoking [14,15].Another important process associated with tobaccosmoke exposure is the airway mucosal response. In ani-mal models, it has been shown that exposure to cigarettesmoke induces goblet cell hyperplasia with accompaniedmucus production [16,17]. Moreover, mucin 5(MUC5AC), has been shown to be the most highlyexpressed mucin in bronchial secretions [18], induced inresponse to cigarette smoke through an EGFR-dependentmechanism [19]. However, beyond this, little is known ofthe genes that are associated with airway remodeling as aresult of tobacco smoking.Serial analysis of gene expression (SAGE) is a quantitativeexperimental procedure widely used to determine expres-sion profiles through the enumeration of short sequencetags and their relative abundance [20]. Although the con-struction and sequencing of an individual SAGE library isthe analysis is not limited to genes represented on anarray. Moreover, comparisons between independentexperiments can be performed without sophisticated nor-malization [21,22].In this study, we compare the bronchial epithelial tran-scriptomes of current, former, and never smokers to deter-mine the effect of active smoking on gene expressionusing bronchial brushings from the peripheral sub-seg-mental airways. Genes whose expression is reversibleupon smoking cessation are expected to differ in abun-dance between current and former smokers, but are simi-lar between former and never smokers. Conversely, geneexpression that is irreversible upon smoking cessation willshow similar levels in current and former (ever) smokersbut differ between ever and never smokers. Here, we focuson identifying both reversible and irreversible geneexpression changes and specifically consider these expres-sion changes in the context of airway mucosal response,and susceptibility to cancer development.Results and DiscussionSAGE library statisticsTwenty-four SAGE libraries were constructed from bron-chial epithelial specimens acquired from eight currentsmokers, twelve former smokers and four never smokers(Table 1). A former smoker was defined as someone whohad stopped smoking for one year or longer. The smokingstatus was verified using exhaled carbon monoxide moni-toring. Raw SAGE data for these transcriptomes has beenmade publicly available at National Center for Biotech-nology Information (NCBI) Gene Expression Omnibus(GEO) with series accession number GSE5473. Fromthese 24 libraries, we have collectively sequenced3,111,471 SAGE tags, yielding 231,866 unique tags, mak-ing this the largest human SAGE study reported to date(Figure 1A). Of the unique tags, nearly half were presentin more than one library at a tag count of one or greater,and 70% (82,983 tags) of these tags map to a UniGenecluster. As multiple tags frequently map to the same Uni-Gene cluster, 25,653 unique UniGene clusters are repre-sented in our dataset. Significantly, over 27,000 tags didnot map to existing annotated genes, reiterating the con-tinuing potential of re-mining this large dataset as tag-to-gene mapping improves with the continuing annotationof human transcripts.Analysis of the current, former and never smoker transcriptomesWe determined both the number of SAGE tags present ineach of the current, former and never smoker transcrip-tomes, as well as those tags equally represented among thethree different datasets. The criteria chosen for preferentialPage 2 of 13(page number not for citation purposes)expensive and laborious compared to microarray analysis,SAGE offers the invaluable potential for gene discovery asexpression was a threshold of a raw tag count of ≥ 2 acrossall samples in a particular set, but not existing in the otherBMC Genomics 2007, 8:297 http://www.biomedcentral.com/1471-2164/8/297sets. Out of 3,033 tags expressed in all current smokers, wefound 227 preferentially expressed tags (Additional file1). In former smokers, 102 tags were found to be prefer-entially expressed (out of 2,579 tags) (Additional file 2),and in never smokers, 2,013 tags were found to be prefer-entially expressed (out of 5,192) (Additional file 3). Itshould be noted that the number of tags preferential tothe never smoker set is substantially higher, most likelydue to the lower sample size of never smokers relative tothe other two groups. However, since we are using neversmokers as a reference, a larger transcriptome will lessenthe likelihood that we would find transcripts that are pref-erentially expressed in current and former smokers thatwere not correct. Looking at those tags which are commonto all three groups, it was found that 1,970 tags (mappingto 1,733 unique genes) were expressed in all 24 libraries(Additional file 4). A Venn diagram illustrating the expres-sion patterns of these three groups is given in Figure 1B.Genes differentially expressed between current and never smokersWe used a Mann Whitney U test to identify tags differen-tially expressed in the transcriptomes of current and neversmokers. Using cut-off requirements of p ≤ 0.05, and aexpressed between current and never smokers (Additionalfile 5).Supervised clustering and principal component analysis (PCA) of current, former and never smokersUsing the 609 tags found to be differentially expressedbetween current and never smokers (Additional file 5),single link hierarchical clustering was performed using theprogram Genesis [23]. We hypothesized that these 609tags would classify current, former and never smokers.Indeed, distinct clusters emerged separating groups of cur-rent and former smokers with one exception of Current4(Figure 2A). Of note, the former smoker who ceasedsmoking for only one year (Former 2) clustered with otherformer smokers. Moreover, principal component analysis(PCA) further validates the distinct groups of current,former and never smokers (Figure 2B).Reversible gene expression changes upon cessation of smokingTo determine reversibility of smoking-related gene expres-sion changes, we intersected tags differentially expressedbetween current and never smokers against tags showingsignificant expression difference between current andTable 1: Demographics of subjects in studySample Name Gender Age at AnalysisPack-Years Smoking Status*Years of smoking cessation (years)Lung function (predicted FEV1 %)Name from previous study**Current 1 F 63 40 CS N/A 69 BE-13Current 2 M 56 62 CS N/A 89 BE-7Current 3 F 63 44 CS N/A 96 BE-12Current 4 M 68 81 CS N/A 76 BE-1Current 5 M 64 45 CS N/A 73 BE-2Current 6 M 66 53 CS N/A 85 -Current 7 M 52 48.1 CS N/A 63 -Current 8 F 55 34.4 CS N/A 81 -Former 1 M 68 33 FS 19 50 BE-3Former 2 M 69 100 FS 1 21 BE-4A/4BFormer 3 M 68 30 FS 1 30 BE-9Former 4 M 70 75 FS 17 76 BE-5Former 5 M 67 55 FS 5 N/A BE-6Former 6 M 65 82 FS 10 59 BE-10Former 7 F 56 64 FS 1.5 71 BE-11AFormer 8 F 63 45 FS 4.5 83 BE-14Former 9 M 72 40 FS 32 87 BE-15Former 10 F 71 56 FS 16 58 BE-16Former 11 M 72 63 FS 6 N/A BE-8BFormer 12 M 69 55.3 FS 21 57 -Never 1 M 58 0 NS N/A 115 -Never 2 F 56 0 NS N/A 104 -Never 3 M 53 0 NS N/A N/A -Never 4 F 81 0 NS N/A N/A -* CS = Current Smoker, FS = Former Smoker, NS = Never Smoker**Subset of samples were used in a previous study by Lonergan et al 2006 [55]Page 3 of 13(page number not for citation purposes)fold change of the means ≥ 2, we identified 609 SAGE tags(mapping to 487 unique genes) to be differentiallyformer smokers using similar criteria. By comparing thesetwo sets, we can deduce which gene expressions are revers-BMC Genomics 2007, 8:297 http://www.biomedcentral.com/1471-2164/8/297ible, i.e., which genes are largely influenced by activesmoking. This analysis yielded 161 tags mapping to 121unique genes, which were deemed statistically significant,and representing 26% of the total number of differentiallyexpressed tags between current and never smokers (Figure3A, Additional file 6). Further analysis of these 121 differ-entially expressed genes has identified two main func-tions: xenobiotic metabolism and nucleotide metabolism(representing 33% of the reversible gene expressionchanges) (Table 2) and airway mucus secretion (repre-senting 12% of the reversible gene expression changes)(Table 3). Genes related to oxidative stress were consid-ered as part of the xenobiotic metabolism/nucleic acidmetabolism category, and those genes previously associ-ated with xenobiotic metabolism and oxidative stressFor example, ectonucleoside triphosphate diphosphohy-drolase 8 (ENTPD8), an extracellular nucleic acid meta-bolic enzyme, is among 18 novel genes (labeled in boldin Table 2) not previously associated with smoking andwhose expression is increased in response to active smok-ing. According to enzyme classification, ENTPD8 isinvolved in purine and pyrimidine metabolism. Hence,this gene may potentially play a role in the chemical for-mation of DNA adducts.Gene expression related to airway muco-ciliary function isalso elevated in both current versus former smokers andcurrent versus never smokers (Table 3). For example, tre-foil factor 3 (TFF3), a structural component of mucus thatis elevated in inflammatory response [26,27], and calcium(A) SAGE library statistics: Summary statistics of the 24 SAGE libraries analyzed in this studyFigure 1(A) SAGE library statistics: Summary statistics of the 24 SAGE libraries analyzed in this study. Mapping information was based on the May 10th, 2006 version of SAGEGenie [45]. In total, over 3,000,000 SAGE tags were sequenced, with over 110,000 unique tags represented upon the exclusion of super singleton tags. (Super singleton tags are tags which have a count of 1 in a single library only). Approximately 75 % of these 110,000 unique tags, (potentially representing as many unique transcripts), mapped to an annotated UniGene cluster. As multiple SAGE tags frequently map to the same UniGene cluster, we have identi-fied at a total of 25,653 distinct UniGene clusters within our dataset, approximately 68% of which represent previously charac-terized genes. Notably, 25% of the unique tags had no mapping, suggesting much information is currently unknown. (B) Transcriptome Venn diagram: Venn diagram of the transcriptomes of current, former and never smokers. Reported is the number of tags which are expressed in every library group at a raw tag count greater than or equal to 2, representing the tags which are constitutively expressed in each set. Nearly 2000 SAGE tags, mapping to over 1700 genes are common to all 24 SAGE libraries. A lower number of never smokers may have contributed to a higher number of preferentially expressed tran-scripts in this group.24 bronchialepithelial libraries3,111,471 SAGEtags sequenced231, 866 uniqueSAGE tags110,289 tagsexcluding singletons82,983 tagsmap toUniGene clusters27,306 tags with no UniGene mapping25,653 distinctUniGene clusters17,363 withannotation8,290 withoutannotationA BCurrent Smoker Transcriptome Former Smoker TranscriptomeNever Smoker Transcriptome197067440769227 1022013Page 4 of 13(page number not for citation purposes)through smoke exposure were among those identified[5,24,25].binding tyrosine-(Y) phosphorylation regulated (CABYR),originally shown to be localized in the principal part ofBMC Genomics 2007, 8:297 http://www.biomedcentral.com/1471-2164/8/297the human sperm flagellum [28], are both highlyexpressed in current smokers relative to former and neversmokers. Though TFF3 was recently shown to beexpressed in response to chronic exposure of nicotine inintestinal cells [29], this is the first report of this genebeing overexpressed within the bronchial epithelium inresponse to active smoking. Based on its assumed role insperm motility, CABYR may be involved in ciliary func-tion associated with muco-ciliary clearance responsewithin the lung [28]. Interestingly, overexpression ofCABYR variants have been reported in a variety of braintumors [30], suggesting a role in carcinogenesis. Previousobservation of increased MUC5AC expression in currentrelative to never smokers and increased expression ofmicroseminoprotein, beta- (MSMB), a gene shown to bepresent in mucosal secretions [31], supports the possibil-ity of induction of airway mucosal response in activesmokers [5,24,25,32].Irreversible gene expression changes upon cessation of smokingBy intersecting genes which are differentially expressedbetween current and never smokers with those that aredifferent between former and never smokers, we can iden-tify irreversible gene expression changes upon smokingcessation. This analysis yielded 152 tags (124 uniquegenes) meeting the criteria of statistical significance (p ≤0.05) at a fold change ≥ 2 (Figure 3B, Additional file 7).Although genes identified by this analysis appear to befunctionally diverse, a small number of genes related tothe cell cycle process and DNA repair have been identifiedhere. For example, expression of P21/Cdc42/Rac1-activatedkinase 1 (PAK1), cyclin D1 (CCND1), and cyclin G2(CCNG2) all appear to be irreversibly lower in ever(former and current) smokers relative to never smokers.This finding is consistent with a previous report ofincreased inhibition of cell proliferation through genessuch as CDKN1A in a higher stage (GOLD-2) of chronicobstructive pulmonary disease (COPD) versus the loweststage (GOLD-0) [33].We also found genes associated with DNA repair to be dif-ferentially expressed between current and never smokers,but similar between current and former smokers. APEXnuclease (multifunctional DNA repair enzyme) 1 (APEX1),High-mobility group box 1 (HMGB1), REV1-like (REV1L),and Tumor suppressor candidate 4 (TUSC4) are repair geneswhich we have found to be irreversibly under-expressed inever smokers. Significantly, APEX1 has been shown toharbor SNPs associated with lung cancer susceptibility[34]. Moreover, REV1L is involved with the recruitment ofDNA polymerase eta to assist in DNA replication atarrested replication forks in areas of DNA lesions such as(A) Cluster analysis of current, former and never smokers: Single link hier rchical lust ring using the 609 SAGE tags comprised in Additional file 5 rep es n i g tags differentially expr ss  b tween curren and nev r smokerFigure 2(A) Cluster analysis of current, former and never smokers: Single link hierarchical clustering using the 609 SAGE tags comprised in Additional file 5 representing tags differentially expressed between current and never smokers. Distance measure used was a Euclidean distance. The visualization package Genesis [23] was used for clustering. Green rectan-gles represent samples with lower expression for the particu-lar gene amongst the samples, and red rectangles represent samples where the gene is highly expressed relative to other samples. (B) Principal component analysis of current, former and never smokers. Expression values used were scaled to tags per million (TPM). Each tag was then normalized by dividing its value by the maximum value for that tag seen in all the libraries. Subsequently, this value was then multiplied by 6 and then subtracted by 3 to put the values ratios in the range of -3 to 3. A co-variance based approach was used and the statistics toolbox in MatLab (Mathworks) was used. Current smokers are represented in red, former smokers are repre-sented in blue and never smokers are represented in green.A-40 -30 -20 -10 0 10 20 30 40-40-30-20-10010Principal Component 1Principal Component 2BPage 5 of 13(page number not for citation purposes)those formed by thymine dimmers [35,36]. TUSC4, alsoknown as NPRL2, has recently been shown to increaseBMC Genomics 2007, 8:297 http://www.biomedcentral.com/1471-2164/8/297sensitivity to cisplatin [37]. Finally, HMGB1 has also beensuggested to be involved with the recruitment of otherrepair-related proteins [38].It should be noted that a significant proportion of formersmokers in our sample set exhibited low FEV1 levels, rais-ing the possibility that airflow obstruction may be a con-founding issue in this analysis. To address this, we usedthe 20 individuals with available FEV1 data to comparewith at most mild COPD (FEV1 ≥ 80%, n = 8) according tothe GOLD staging classification based on FEV1 status[39,40]. Of the 157 tags differentially expressed betweenthese two groups, only 6 tags overlap with our list of irre-versible genes (Additional file 8). This minimal overlapsuggests that the irreversible genes identified are not sig-nificantly associated with airway obstruction based onFEV1 status. Nonetheless, airway obstruction should beconsidered in the interpretation of differential geneTable 2: Reversible gene expression upon smoking cessation related to xenobiotic metabolism and DNA adduct formation (genes in bold have not been previously associated with smoking)Tag Gene Symbol Gene Name CS Mean* FS Mean* NS Mean* P-Value (CVsF)GGCCCAGGCC ALDH3A1 Aldehyde dehydrogenase 3 family, memberA1 4355 313 261 0.00002TTAAAAATTC ADH7 Alcohol dehydrogenase 7 (class IV) 899 145 130 0.00002AGGTCTGCCA*** AKR1C2 Aldo-keto reductase family 1, member C2 547 116 74 0.00002AATGCTTTTA CYP1B1 Cytochrome P450, family 1, subfamily B, polypeptide 1 204 13 0 0.00002TTGGAATCCA STAU2 Staufen, RNA binding protein, homolog 2 (Drosophila) 67 17 23 0.00002TTATCAAATC NQO1 NAD(P)H dehydrogenase, quinone 1 809 202 149 0.00003CAAATAAACC PIR Pirin (iron-binding nuclear protein) 260 47 43 0.00003GGCCCCATTT CBR1 Carbonyl reductase 1 144 31 24 0.00003TATTTTTGTT TXNRD1 Thioredoxin reductase 1 250 88 78 0.00006GGTGGTGTCT GPX2 Glutathione peroxidase 2 (gastrointestinal) 384 40 46 0.00011TATTTTTGAA DRB1 Developmentally regulated RNA-binding protein 1 204 32 22 0.00011TGGGAGTGGG** NMNAT2 Nicotinamide nucleotide adenylyltransferase 2 175 17 9 0.00011CAAGACCAGT GSTA2 Glutathione S-transferase A2 1436 485 528 0.00019GCTTGAATAA AKR1B10 Aldo-keto reductase family 1, member B10 (aldose reductase) 332 10 15 0.0003GTGCAGGGAG SPDEF SAM pointed domain containing ets transcription factor 239 64 50 0.0003GGAGGCTTCC MECR Mitochondrial trans-2-enoyl-CoA reductase 85 26 22 0.0003GTGATGTAAG SRXN1 Sulfiredoxin 1 homolog (S. cerevisiae) 63 14 11 0.0003TATGCTTTAA NT5DC1 5'-nucleotidase domain containing 1 59 23 24 0.0003GAACGCCTAA DPYSL2 Dihydropyrimidinase-like 2 1 21 23 0.0004TTTTCTGAAA TXN Thioredoxin 698 326 212 0.00048CTTGCATAAG CYP1A1 Cytochrome P450, family 1, subfamily A, polypeptide 1 89 2 0 0.00048GCAAGAAGAG ALDH3A1 Aldehyde dehydrogenase 3 family, memberA1 77 10 2 0.00048AGAACAAAAC PRDX1 Peroxiredoxin 1 1043 418 510 0.00071AAATATTTAA SLC35A3 Solute carrier family 35, member A3 47 14 19 0.00071CGGCTGAATT PGD Phosphogluconate dehydrogenase 252 104 80 0.00106CTTATCAGTA BTBD7 BTB (POZ) domain containing 7 94 22 2 0.00106AAGAGTTTTG AKR1B1 Aldo-keto reductase family 1, member B1 (aldose reductase) 25 5 6 0.00141GCTGAGATGA** CYP4F11 Cytochrome P450, family 4, subfamily F, polypeptide 11 22 6 2 0.00141GGCGCCTCCT TALDO1 Transaldolase 1 232 76 94 0.00152GACACAGCAA ENTPD8 Ectonucleoside triphosphate diphosphohydrolase 8 24 3 2 0.00159CAGTCTAAAA UCHL1 Ubiquitin carboxyl-terminal esterase L1 (ubiquitin thiolesterase)92 4 0 0.00197ACATCCTAGG ALDH1A1 Aldehyde dehydrogenase 1 family, member A1 60 28 30 0.00216TTAGAAGGAA NQO1 NAD(P)H dehydrogenase, quinone 1 41 14 9 0.00216AGGTCTACCA AKR1C2 Aldo-keto reductase family 1, member C2 270 32 8 0.00292ATTAGGCCTG TXNRD1 Thioredoxin reductase 1 51 19 17 0.00297GAGAGCTTTG AKR1C3 Aldo-keto reductase family 1, member C3 149 21 22 0.00298TACGCTTGGT CYB5R1 Cytochrome b5 reductase 1 68 32 30 0.00298CACTGCCTTG FTH1 Ferritin, heavy polypeptide 1 59 23 17 0.00298CTGCTGCACT GSR Glutathione reductase 126 54 50 0.0041GGCAAAATTA SLC35A3 Solute carrier family 35, member A3 73 32 35 0.0041ACCTTGGGGT NQO1 NAD(P)H dehydrogenase, quinone 1 73 19 6 0.0041AATGTTCAGG COQ6 Coenzyme Q6 homolog, monooxygenase (yeast) 29 12 4 0.00708CACTGACCAG NOD27 Nucleotide-binding oligomerization domains 27 31 10 0 0.00927CTCGGAGGCC SEPX1 Selenoprotein X, 1 71 32 28 0.00956CTCCAAAAAA CPSF2 Cleavage and polyadenylation specific factor 2, 100 kDa 118 44 14 0.02013AATGGAAACT GCLM Glutamate-cysteine ligase, modifier subunit 34 16 9 0.03186*Mean in tags per million (TPM)** Changed mapping with TAGMapper [56]***Tag maps with equal reliability to AKR1C1Page 6 of 13(page number not for citation purposes)individuals with moderate or severe COPD (FEV1 < 80%,n = 12) with those individuals that would be classifiedexpression between current and former smokers.BMC Genomics 2007, 8:297 http://www.biomedcentral.com/1471-2164/8/297A similar approach to that described here was undertakenby Spira et al. where the expression of 13 genes, includingsome putative oncogenes and tumor suppressor genes,was deemed irreversible upon cessation of smoking. How-ever, none of these 13 genes overlapped with those iden-tified in our study. This lack of overlap may reflect thediffering locations from which the bronchial brushingswere obtained as Spira et al [5] sampled from the rightmain bronchus whereas we have sampled peripheral sub-segmental airways.It is interesting to note that MUC5AC appears in both thelists of statistically reversible and irreversible gene expres-sion changes suggesting that expression of this gene exhib-its distinct states of expression among current, former andnever smokers. Moreover, it should also be noted thatalthough 311 of the 609 tags were classified as eitherreversible or irreversible, the remaining 298 tags did notmeet the statistical criteria for either category.Validation of select gene expression changes using quantitative RT-PCRIn addition to the SAGE analysis, which identified genesassociated with airway mucosal response and xenobiotic/nucleic acid metabolism as distinguishing featuresbetween current and former smokers, we have performedquantitative RT-PCR on a secondary cohort of current,former and never smokers to validate selected genes forexpression changes (Additional file 9). In total, five geneswere selected for validation. From the set of reversiblegenes, we have chosen CABYR, ENTPD8, and TFF3because their expression has not been associated withsmoking previously. In addition, from the irreversiblegenes, we have selected MUC5AC. Using the delta-delta-Ct method to derive expression values, we then employeda Mann Whitney U Test to determine significance. Thepattern of reversible over-expression in current smokersfor CABYR, ENTPD8, and TFF3 (Figure 4A) and the irre-versible over-expression of MUC5AC (Figure 4B)observed from the SAGE data, was validated by quantita-tive RT-PCR (Additional file 10). Raw cycle thresholds foreach gene are available in Additional file 9.Airway epithelium response genes and their role in inflammation and cancerAlthough the role of xenobiotic metabolism in smoking-induced carcinogenesis has been well documented [9,15],the potential influence mediated by changes in the com-position of the airway mucosa in the development of lungcancer, has not been thoroughly investigated. It is possiblethat constant dysregulation of expression of genes associ-ated with mucus secretion (such as TFF3 and MUC5AC)by smoking could potentially have a direct or indirect rolePrincipal component of current, former and never smokers us g (A) the 161 tags deem d reversible upon smoking ce -sation (Additional file 6) and (B) th  152 tags de med irr -versible upon smoking c ssation (Additio al fil  7)Figure 3Principal component of current, former and never smokers using (A) the 161 tags deemed reversible upon smoking ces-sation (Additional file 6) and (B) the 152 tags deemed irre-versible upon smoking cessation (Additional file 7). Expression values used were scaled to tags per million (TPM). Each tag was then normalized by dividing its value by the maximum value for that tag seen in all the libraries. Sub-sequently, this value was then multiplied by 6 and then sub-tracted by 3 to put the values in the range of -3 to 3. A co-variance based approach was used and the statistics toolbox in MatLab (Mathworks) was used. Current smokers are rep-resented in red, former smokers are represented in blue and never smokers are represented in green.AB-2 0 -1 5 -1 0 -5 0 5 1 0 1 5-1 5-1 0-5051 01 5P rin c ip a l C o m p o n e n t 1Principal Component 2-1 5 -1 0 -5 0 5 1 0 1 5 2 0-5051 01 52 0P rin c ip a l C o m p o n e n t 1Principal Component 2Page 7 of 13(page number not for citation purposes)in smoking-induced carcinogenesis.BMC Genomics 2007, 8:297 http://www.biomedcentral.com/1471-2164/8/297One of the many genes involved in lung cancer develop-ment is cyclooxygenase 2 (COX2), which plays a multi-fac-eted role in cellular proliferation, migration andinvasiveness [41]. Notably, secretoglobin, family 1A,member 1 (SCGB1A1) protein has been shown to inhibitCOX2 at the mRNA level [42,43]. We observed thatSCGB1A1 expression is drastically reduced in currentsmokers but is expressed at similar levels in former andnever smokers, and a previous study showed decreasedserum SCGB1A1 level in smokers [44]. It should also benoted that none of the SAGE sequence tags identified inthe analysis mapping to SCGB1A1 are the most reliabletag according to SAGE Genie [45]. However, even thoughthe most reliable tag to this gene, CTTTGAGTCC did notpass statistically, the trend of reduced expression in cur-rent smokers relative to former smokers and similarexpression between former and never smokers is consist-ent with the sequence tags that did appear in the analysis.Moreover, given that multiple tags have appeared fromour analysis, although not as reliably mapped, we are con-fident that we are detecting SCGB1A1 mRNA expression.Interestingly, COX2 mRNA expression was not detected inthe bronchial epithelium of current, former and neversmokers from our SAGE data. A recent report demon-strated a significant increase in COX2 expression in nor-mal lung fibroblasts when exposed to cigarette smokeextracts [46]. It is possible that SCGB1A1 involvement isin the stroma and not in epithelial cells.Despite lack of knowledge about CABYR, one of its fewknown interactions occurs with GSK3B [30].CABYR is asubstrate of GSK3B [30], and exhibits reversible, increasedexpression with active smoking (Figure 4A). Thoughrevealed a trend of similar decreased expression in currentand former smokers relative to never smokers. Moreover,quantitative RT-PCR using a secondary cohort of samplesvalidated that GSK3B expression is irreversibly reduced inever smokers (Figure 4B). Recently, a published reportusing porcine tracheobronchial epithelial cells exposed tocigarette smoke components in vitro, demonstrated aninhibition of GSK3B gene expression [47]. GSK3B hasbeen shown to negatively interact with COX2 [48].Reduced expression of GSK3B may therefore account forexaggerated inflammatory response despite smoking ces-sation and may contribute to development of lung cancer.In this study, we have demonstrated differential expres-sion of various components of respiratory tract mucus(including TFF3 and MUC5AC) according to smoking sta-tus (Table 3). However, our data indicates that MUC5ACexpression is not completely reversible upon smoking ces-sation and in fact, exhibits three statistically distinct levelsof expression between current, former and never smokers(Figure 4B). TFF2, a related motogen to TFF3, in conjunc-tion with epidermal growth factor (EGF), has been shown topromote airway restitution, (i.e., movement of neighbor-ing airway epithelial cells in response to injury mimickingrapid epithelium regeneration), through the activation ofthe epidermal growth factor receptor (EGFR) [49], expressedin the normal bronchial mucosa [50,51]. Other studieshave also demonstrated increased expression ofMUC5AC, along with EGFR and v-erb-b2 erythroblasticleukemia viral oncogene homolog 3 (ERBB3) in active smok-ers [26,32]. We examined EGFR expression in relation tosmoking and found that there was a modest increase ofapproximately 1.5-fold between current and formerTable 3: Reversible gene expression upon smoking cessation related to mucus secretion (genes in bold have not been previously associated with smoking)Tag Gene Symbol Gene Name CS Mean* FS Mean* NS Mean* P-Value (CVsF)GAATGAACTG EDIL3 EGF-like repeats and discoidin I-like domains 3 72 5 8 0.00011CTCCACCCGA TFF3 Trefoil factor 3 (intestinal) 4974 1978 1722 0.00019GTGGAGAAGA CLDN10 Claudin 10 89 23 26 0.00019GGAATTGCCC BPIL1 Bactericidal/permeability-increasing protein-like 1 43 4 4 0.00029TTGGTTTTTG CXCL6 Chemokine (C-X-C motif) ligand 6 147 414 371 0.0003CCTATCAGTA MSMB Microseminoprotein, beta- 15881 4405 2948 0.00048CTTCCTGTGA SBEM Small breast epithelial mucin 154 27 32 0.00071TGGAAATGTG CBARA1 Calcium binding atopy-related autoantigen 1 49 18 15 0.00141CAAGCATAAA CABYR Calcium binding tyrosine-(Y)-phosphorylation regulated 63 4 4 0.00241AGGGAGGCAG SCGB1A1 Secretoglobin, family 1A, member 1 135 473 436 0.0041TATCACATTC CXCL6 Chemokine (C-X-C motif) ligand 6 10 42 29 0.00573TTGCACCCTT MSMB Microseminoprotein, beta- 71 16 9 0.00735AGCTTAATGA** SCGB1A1 Secretoglobin, family 1A, member 1 557 1478 3269 0.00956GAAAAAATAG SCGB1A1 Secretoglobin, family 1A, member 1 (uteroglobin) 88 288 281 0.0124GTGGCCACGG S100A9 S100 calcium binding protein A9 (calgranulin B) 26 101 63 0.0124AAAATGTATT CAV2 Caveolin 2 20 6 4 0.0144GACAAGGATG CX3CL1 Chemokine (C-X3-C motif) ligand 1 29 63 93 0.01586*Mean in tags per million (TPM)** Changed mapping with TAGMapper [56]Page 8 of 13(page number not for citation purposes)GSK3B was not identified as a smoking-related gene inour primary analysis, investigation of the SAGE datasmokers in our SAGE data. As enhanced expression ofEGFR is well documented in lung cancer [52,53], theseBMC Genomics 2007, 8:297 http://www.biomedcentral.com/1471-2164/8/297Page 9 of 13(page number not for citation purposes)SAGE and quantitative PCR (qRT-PCR) analysis of select genes: (A) Genes found to have reversible expression upon smoking cessatioFigure 4SAGE and quantitative PCR (qRT-PCR) analysis of select genes: (A) Genes found to have reversible expression upon smoking cessation. Box plots of SAGE data and histograms for qRT-PCR for CABYR, ENTPD8 and TFF3. Distribution of ratios between both current vs. former and current vs. former and never (Additional file IV) were found to be statistically different. (B) Genes found to be either partially or fully irreversible. Box plots of SAGE data and histograms for qRT-PCR for MUC5AC and GSK3B. Distribution of ratios between current vs. former and former vs. never were statistically different for MUC5AC and in addition, GSK3B was statistically significant for the combination of current and former vs. never. Box plot analysis was done using the Statistics toolbox from the MathWorks MatLab program. Red lines in the boxes represent the median expression value in terms of tags per million (TPM), and red "plus" signs represent outliers (values which are greater than 1.5 times the maximum value). The bottom and top part of the boxes represent the 2nd and 3rd quartiles of the data respectively. The error bars represent the 5th and 95th percentiles of the data. Quantitative RT-PCR validation was performed on a second cohort of nine current smok-ers, seven former smokers and six never smokers. Plotted is the average expression ratio relative to the average expression in never smokers of current (red), former (blue) and never (green) smokers. Statistical significance was determined using a one-tailed p-value from the Mann Whitney U Test (Supplemental Table IX).A02040800120060140100Current Former Never Current Former NeverCABYRCurrent Former Never51015202530354020004000600080001000012000ENTPD8 TFF3B01000200040006000300070005000Current Former NeverMUC5AC GSK3B0102030405060708090Current Former NeverExpression (TPM)Current Former NeverCurrent Former NeverCurrent Former NeverCurrent Former Never0.51.51.02.02.500.51.51.02.02.500.20.60.40.81.000.20.60.40.81.002.53.03.51.21.41.61.2Fold changeExpression (TPM)26481001214Current Former NeverFold changeBMC Genomics 2007, 8:297 http://www.biomedcentral.com/1471-2164/8/297results imply that enhanced expression of TFF3 (and per-haps other genes associated with airway epithelialresponse and mucus secretion) may promote airway resti-tution in response to active smoking and that constantinduction of airway reconstruction may play a role in thedevelopment of lung cancer (Figure 5).ConclusionThis study represents the largest human SAGE studyreported to date. Over three million SAGE tags weresequenced, representing over 110 thousand potentiallyunique transcripts expressed within the bronchial epithe-lium relative to cigarette smoke exposure. These librariesprovide a valuable resource for future data mining. Basedon the gene expression profiles of 24 current, former andnever smokers, we identified both reversible and irrevers-ible gene expression changes upon smoking cessation.Specifically, amongst those genes reversibly expressed,three main functions were identified: xenobiotic metabo-lism, nucleotide metabolism, and mucus secretion. Inaddition, some of the genes associated with airwaymucosal response are strongly involved with airway epi-thelium repair and regeneration. Interestingly, investigat-ing airway repair and regeneration revealed genes varyingin the degree of reversibility, including those completelyreversible (TFF3, CABYR), partially reversible (MUC5AC)and irreversible (GSK3B) expression changes upon smok-ing cessation. We have validated the SAGE expression datafor TFF3, CABYR, MUC5AC, GSK3B and ENTPD8 using asecondary cohort of current, former and never smokers.This is the first study demonstrating smoking-inducedexpression changes for this particular set of genes andimportantly, it is the first time partial reversibility(MUC5AC) and irreversibility (GSK3B) and has beendemonstrated using two different cohorts of samples withtwo independent assays for expression quantification. Bycomprehensively identifying gene expression changes thatare reversible upon smoking cessation, we have intro-duced genes which may in future studies be investigatedfor polymorphisms, as those genes which are not suffi-ciently induced in response to smoking may identify can-didate loci of susceptibility. Similarly, those genes andfunctions which do not revert to normal levels uponsmoking cessation may also provide insight into whyformer smokers still maintain a risk of developing lungcancer.MethodsSpecimen collectionBronchial epithelial cells were collected by bronchialbrushings from 24 subjects – 9 current smokers, 11 formersmokers and 4 never smokers summarized in Table 1 – bybronchial brushing as described previously [54,55]. Thesubjects were volunteer smokers recruited from the com-munity as part of a NCI-sponsored chemoprevention trial.The inclusion criteria were: age > 45 years of age and asmoking history of ≥ 30 pack years. A former smoker wasdefined as one who had stopped smoking for at least oneyear or more. None of the subjects were on bronchodila-tor or inhaled steroids. The samples were obtained priorto treatment with an investigational chemopreventionagent.Brushings were obtained from the peripheral airwaysusing a 1.8 mm brush. A table of the basic demographicsof the subjects used is listed in Table 1.Construction of SAGE librariesTo deduce the gene expression profiles, we used a methodcalled serial analysis of gene expression (SAGE) whichquantifies gene expression by the enumeration of tran-script derived sequence tags [20]. SAGE libraries were con-Expression trends of specific genes related to muco-ciliary function a d airway restitution as compared with smoking status and lung cancer: TFF3, CABYR, and MUC5AC are over e e in current mokers with lowe expressi n inbo h f rmer nd ever smokersFig re 5Expression trends of specific genes related to muco-ciliary function and airway restitution as compared with smoking status and lung cancer: TFF3, CABYR, and MUC5AC are over expressed in current smokers with lowered expression in both former and never smokers. Conversely, SCGB1A1 shows the opposite effect, with lowered expression in cur-rent smokers as compared to former and never smokers. MUC5AC and TFF3 are known to be components of mucus. EGFR levels are positively correlated with smoking status, with modestly higher levels in current smokers. MUC5AC and EGF have been shown to interact with EGFR in the proc-ess of airway restitution and SCGB1A1 has been shown to decrease levels of cyclooxygenase 2 (COX2) in cancer cells. Interestingly, within this process alone, we see reversible (TFF3, CABYR), partially reversible (MUC5AC) and completely irreversible (GSK3B) expression changes upon smoking ces-sation. Values refer to tag counts as tags-per-million (TPM).TFF3CABYRMUC5ACEGFRSCGB1A1GSK3BEGFCOX2MucosalComponentsAirway Repair andRegenerationphosphorylatesXXGene (SAGE Tag) CSMean FSMean NSMean MUC5AC (GTGATCAGCT) 3609 1526 448 TFF3 (CTCCACCCGA) 4974 1978 1722 SCGB1A1 (CTTTGAGTCC)  22002 43016 36372 EGF (GAGGCAGGAG) 0 1 2 EGFR (AGTACCTTAT) 29 20 22 CABYR (CAAGCATAAA) 63 4 4 GSK3B (CAATAAAGGT) 8 16 33 COX2 (CTGTTCCTTT) 0 3 0  Page 10 of 13(page number not for citation purposes)structed from each sample using the MicroSAGE protocol[55], and sequenced to a depth of ~150,000 SAGE tags perBMC Genomics 2007, 8:297 http://www.biomedcentral.com/1471-2164/8/297library. SAGE libraries were deposited in NCBI GEO withaccession number GSE5473. Reproducibility of SAGElibraries obtained from the same bronchial brush wasshown by our group previously. The R value between twolibraries from the same lysate was 0.97 [55].SAGE tag-to-gene mappingTag-to-gene mapping was performed using a combinationof the May 10th, 2006 build of SAGEGenie [45]. Tags withlow reliability from SAGEGenie in Table 2 and 3 were alsocross-referenced with TagMapper [56].Statistical analysis of differentially expressed genesStringently, only tags which exhibited a mean tag count of≥ 20 tags per million (TPM) in at least one of current,former or never smoker SAGE libraries were used in com-parative analysis. For each specific comparison, in addi-tion to the tag count requirement, a minimum foldchange of the means of two was also required. The tagabundance requirement of a mean tag count of 20 TPMwas used to filter the list of tags prior to statistical compar-ison to reduce the number of false positives. 8148 tagsmeet this criterion. Given the variability in smokers andlimited sample size in this study, a non-parametric MannWhitney U Test was used to determine if a given tag (rep-resenting a gene) was differentially expressed using a p-value threshold of p ≤ 0.05, unadjusted for multiple com-parisons.Validation of SAGE-specific targets using quantitative RT-PCRSelect targets identified in the SAGE study were validatedusing quantitative RT-PCR (qRT-PCR) in a second cohortof nine current, seven former and six never smokers.Briefly, 100 ng of RNA was isolated and converted tocDNA in a 50 μl reaction volume using the High-CapacitycDNA Archive Kit (cat # 4322171, Applied Biosystems). 1μl of the resulting cDNA was analysed by qPCR, with spec-ified Taqman primers and TaqMan Universal PCR MasterMix (cat # 4326708), using the iCycler iQTM Real-TimePCR Detection System (Bio-Rad). CABYR, TFF3,MUC5AC, GSK3B and Actin Beta were monitored for 40cycles of PCR and ENTPD8 for 50 cycles. Primers used forqRT-PCR are listed in Additional file 11.Authors' contributionsRC analyzed the SAGE and quantitative PCR data todeduce the key findings, and wrote the manuscript.KML led the construction of all SAGE libraries and con-tributed to data interpretation and manuscript editing.RTN provided insight to statistical analysis.CM provided insight to statistical analysis as well as man-uscript editing.SL isolated the clinical samples from current, former andnever smokers, and contributed to interpretation ofresults.SL and WLL are the principal investigators of this project.Additional materialAdditional file 1Supplementary Table 1 – Tags expressed in all current smoker libraries. Tags which have a raw count of greater than 2 in all 8 current smoker SAGE libraries.Click here for file[http://www.biomedcentral.com/content/supplementary/1471-2164-8-297-S1.xls]Additional file 2Supplementary Table 2 – Tags expressed in all former smoker libraries. Tags which have a raw count of greater than 2 in all 12 former smoker SAGE libraries.Click here for file[http://www.biomedcentral.com/content/supplementary/1471-2164-8-297-S2.xls]Additional file 3Supplementary Table 3 – Tags expressed in all never smoker libraries. Tags which have a raw count greater than 2 in all 4 never smoker SAGE libraries.Click here for file[http://www.biomedcentral.com/content/supplementary/1471-2164-8-297-S3.xls]Additional file 4Supplementary Table 4 – Tags expressed in all 24 SAGE libraries. Tags which have a raw count greater than 2 in all 24 SAGE libraries.Click here for file[http://www.biomedcentral.com/content/supplementary/1471-2164-8-297-S4.xls]Additional file 5Supplementary Table 5 – 609 tags differentially expressed between cur-rent and never smokers. 609 differentially expressed tags between current and never smokers.Click here for file[http://www.biomedcentral.com/content/supplementary/1471-2164-8-297-S5.xls]Additional file 6Supplementary Table 6 – 161 tags with reversible expression upon smok-ing cessation. 161 tags which exhibit statistically reversible gene expres-sion upon smoking cessation.Click here for file[http://www.biomedcentral.com/content/supplementary/1471-2164-8-297-S6.xls]Page 11 of 13(page number not for citation purposes)BMC Genomics 2007, 8:297 http://www.biomedcentral.com/1471-2164/8/297AcknowledgementsWe thank William W. Lockwood, Jonathan J. Davies, Bradley P. Coe, Ian M. Wilson and Teresa L. Mastracci for useful discussion. We also would like to thank Andrea Pusic for assistance with quantitative RT-PCR validation and SAGE library construction and Baljit Kamoh and Blair Gervan for assist-ance with SAGE library construction. This work was supported by funds from Genome Canada/Genome British Columbia, Canadian Institutes of Health Research, and NIDCR grant RO1 DE15965-01. RC is supported by scholarships from the Canadian Institutes of Health Research and the Michael Smith Foundation for Health Research.References1. Jemal A, Siegel R, Ward E, Murray T, Xu J, Smigal C, Thun MJ: Cancerstatistics, 2006.  CA Cancer J Clin 2006, 56(2):106-130.2. Halpern MT, Gillespie BW, Warner KE: Patterns of absolute riskof lung cancer mortality in former smokers.  J Natl Cancer Inst1993, 85(6):457-464.3. Peto R, Darby S, Deo H, Silcocks P, Whitley E, Doll R: Smoking,smoking cessation, and lung cancer in the UK since 1950:combination of national statistics with two case-controlstudies.  Bmj 2000, 321(7257):323-329.5. 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