Cigarette smoke contributes to almost 90% of all lung cancer and chronic obstructive pulmonary disease (COPD) deaths, up to 10-20% smokers suffer from these diseases. Lung cancer is the second most common cancer in worldwide [1, 2]. According to world health organization (WHO), around 6 million people die each year due tobacco consumption. Tobacco smoking prevalence in Pakistan is 36% for male and 9% for female . Cigarette smoke drastically affects the stability of genome, p53 status, gene expression, methylation and epithelial cells that lines the airway comprising buccal, nasal and bronchial mucosa [2,3,4].
Prior works have revealed that field of injury is generated by smoking in epithelial cells of respiratory tract. The hypothesis of field of injury states that similar molecular response all over the respiratory tract is elicited due to exposure of inhaled toxins e.g. cigarette smoke. Global gene expression profile gives a complete picture covering molecular aspects of this physiological response. Such field defect is also generated in response to pulmonary diseases. The alterations occur in mRNA and microRNA expression throughout the respiratory system give understanding of the molecular characteristics of these diseases, leads to develop diagnostic biomarkers. In normal airway of smokers, smoking related differential expression has shown significant difference, considering this many authors have conclude that development of lung disease i.e. lung cancer [5,6] and COPD  depends on smoker’s response to tobacco smoke.
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Gene Expression Studies on Smoking Induced alterations in the Airways
Attributable to the increasing rate of lung diseases caused by cigarette smoking, few studies [7,8] have determined the changes occur throughout the human pulmonary airway epithelium exposed to cigarette smoke or reversible changes in epithelial cells of former smokers . Spira et al. [a] using gene expression profiles across broad spectrum of healthy individuals demonstrated the normal functioning of set of epithelial cells from a complex organ. The authors have found smoking induced alterations in human bronchial airway epithelial transcriptome. Cigarette smoke induces up-regulation of genes engaged in oncogenesis, xenobiotic and regulation of oxidant stress, and suppresses genes engaged in tumor suppression and regulation of inflammation. In the follow up study by the same group a bronchial airway gene expression profile was proposed, used to differentiate smokers with and without lung cancer [a].
To assay the host response toward the exposure of tobacco smoke, oral and nasal epithelium are interesting candidates as they are collected non-invasively and feasible to obtain sufficient RNA [b]. Sridhar et al. [c] investigated healthy smokers and non-smokers, and generated relationships in global gene expression between extrathorcic (nasal and buccal) and intrathoracic( bronchial). Employing the previously defined genes expressed in the normal bronchial airway of never smokers, authors determined that gene expression in both bronchial and nasal epithelium were similar when contrasts with other epithelial and non-epithelial tissues. In both nose and bronchus, high expression of many antioxidant, detoxification, and structural genes has been observed. Principal component analysis was performed on smoking-induced genes collected from bronchus indicated that consequences of smoking on gene expression were similar in nasal epithelium. Gene set enrichment analysis showed that smoking had significant effect on this set of genes in samples of nasal and buccal epithelial.
miRNAs are a class of small ~22 nucleotide long non coding RNAs, synthesized in the nucleus and cytoplasm both. miRNAs play a significant role as a post-transcriptional regulator of gene expression, down regulate gene expression by binding at 3’UTR of the target genes. Initially in the biogenesis of miRNAs, a long transcript named as pri-miRNA is generated in nucleus by RNA pol II. Pri-miRNAs exhibit hairpin and stem loop structures recognized by microprocessors complex (Drosha-DGCR8) for cleavage, producing pre-miRNAs ~70 nucleotides in length directed to cytoplasm through Exprotin-5. The major processing step occurs in cytoplasm when Dicer cleaved pre-miRNAs forming ~22 nucleotide strands. RISC complex incorporates either one or both strands lead to down regulate target mRNAs by degrading transcript or repressing translation. miRNAs mediate physiological response in the airway, lung and other tissues toward stress such as cigarette smoke and other inhaled toxins [9,10]. Therefore, miRNAs may prove as potential biological biomarkers.
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microRNAs response to cigarette smoke
Exposure of cigarette smoke is the key source of cellular stress i.e. oxidative stress  and hypoxic . Local cell hypoxia and DNA damage [13-14] induced by cigarette smoke activates many protective mechanism, includes the stimulation of stress proteins associated with COPD development such as HIF-1α and Rtp801 . Several studies have reported miRNAs in the respiratory tract got affected by the components of cigarette smoke, indicating miRNAs involvement in the potent protective mechanisms. Izzotti et al. studied the response of miRNAs in the whole lung of rats after their exposure to cigarette smoke for four weeks . This study identified 484 rat miRNAs assayed, out of which 25 %( 126 miRNAs) shown 2-fold decreased in the expression in the lungs of exposed subjects, whereas up-regulated miRNAs were only 7. Moreover, the most decreased subset of miRNAs found, were situated in genomic sites readily knocked out in lung cancer, and had implicated in cell proliferation, stress response, oncogene and tumor suppressor pathways. In the same experiment, authors also found several inverse relationships between miRNAs and its target, significantly intervene the cigarette smoke effect like miRNA 219 with its stress response Erg gene, and miRNA-34c and the Bcl2-associated agonist gene (target).
Smoking induced miRNA down regulation is also observed in humans. Lenburg et al. have unfolded the response of airway associated miRNA expression to exposure of cigarette smoke . Whole genome RNA and miRNA profiling of 20 healthy subjects (non -smokers: 10, smokers: 10 ) was performed on the bronchial airway epithelial cells obtained from mainstem bronchi. By comparing active smokers with never smokers, the significantly differentially expressed 28 miRNAs were identified, 80% of them were down-regulated. The most down-regulated miRNA by 4-fold in the airway epithelial cells of smokers was MiRNA-218. A number of inverse miRNA-mRNA target relationships were observed, indicating alteration in expression of few miRNAs could initiate the cascades of smoking associated changes in gene expression.
Venter et al.  proposed the seminal work of sequencing whole human genome by employing better coverage methods and performed accurate analysis to untangle the information embedded in genome. High-throughput technologies are being widely used in different aspects of biology including genome, epigenome and transcriptome. Sequencing does not have the limitations exists in preceding technologies i.e microarray (Table: 01).RNA-seq is sequencing steady-state RNA in a sample, has tendency to access the transcriptome complexities namely novel promoters, isoforms and allele-specific expression [19-20]. Analysis methodology of high-throughput technology is critical and data interpretation is not an easy job.
In general RNA-seq experiment, RNA is collected from sample, fragmentized and converted into cDNA with attached adaptors on one or both ends. Every fragment is sequence on high throughput platforms i.e. Illumina GA/ HiSeq, SOLiD or Roche 454 . This step produces millions of short reads typically 25-300bp long obtain from one end (single-end read) or both ends (paired-end reads). After sequencing, short reads are mapped either on reference genome or reference transcripts or another option is de novo assembly of the transcriptome to achieve genome wide transcriptional map consisting gene level expression and/or transcriptional structure .
Sequencing on microRNAs
As far our knowledge, the first study to explore the genome-wide miRNA expression profiles is conducted by Yong et al in 2013 [d]. This study has determined the association of genome-wide miRNA expression alterations occurred in the Down Syndrome (DS) fetuses due to trisomy of human chromosome 21 (Hsa21). RNA sequencing was used to analyze the miRNA expression profiles of DS and normal fetus cord blood mononuclear cells (CBMCs) with the purpose to examine the distinctive feature of miRNAs expression and locate miRNA gene on Hsa21. The authors found the significantly expressed miRNAs were 149 out of 395, exhibiting fold change > 2.0 and P<0.001. From 181 candidates, 2 novel HSA21-derived miRNAs were identified located in the ‘DS critical region’. Enrichment analysis unraveled the functionality of miRNAs expressing abnormally, serves as a regulator of transcription, cellular biosynthetic process, nucleic acid metabolic process and gene expression. The majority of mRNA targets of identified miRNAs were players of immune modulation such as MXD4, BCLAF1, SOD1, FOXO1, SOD1, PBX1.
Using the same approach of miRNA-seq expression profiles, Vucic et al. [d] conducted a cross sectional study on current smokers, former smokers and never smokers, to interrogate the smoke status specific expression of miRNA in lung tumors and parenchymal tissues. miRNA-mRNA gene networks indicated disruption in miRNA transcriptome disturb distinct biological pathways in smoke status dependent manner. Moreover, this study has identified miRNAs that influence the prognosis of lung cancer patient differentially.
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Longitudinal study has to be conducted to identify the underlying biology of smoke induced diseases or alterations by using the above-mentioned approach of miRNA-seq expression profiling. Unlike cross sectional studies, in longitudinal study data is collected multiple times from the same subjects while keeping the procedure constant, often last for many years. The advantage of this study is we can detect the sequence of events or changes occur in the transcriptome of the target population at the group and individual level as well.