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Differential expression of C-Reactive protein and Serum amyloid A in different cell types in the lung tissue of chronic obstructive pulmonary disease patients
© Calero et al.; licensee BioMed Central Ltd. 2014
Received: 11 February 2014
Accepted: 21 May 2014
Published: 30 May 2014
Chronic systemic inflammatory syndrome has been implicated in the pathobiology of extrapulmonary manifestations of chronic obstructive pulmonary disease (COPD). We aimed to investigate which cell types within lung tissue are responsible for expressing major acute-phase reactants in COPD patients and disease-free (“resistant”) smokers.
An observational case–control study was performed to investigate three different cell types in surgical lung samples of COPD patients and resistant smokers via expression of the C-reactive protein (CRP) and serum amyloid A (SAA1, SAA2 and SAA4) genes. Epithelial cells, macrophages and fibroblasts from the lung parenchyma were separated by magnetic microbeads (CD326, CD14 and anti-fibroblast), and gene expression was evaluated by RT-PCR.
The sample consisted of 74 subjects, including 40 COPD patients and 34 smokers without disease. All three cell types were capable of synthesizing these biomarkers to some extent. In fibroblasts, gene expression analysis of the studied biomarkers demonstrated increased SAA2 and decreased SAA1 in patients with COPD. In epithelial cells, there was a marked increase in CRP, which was not observed in fibroblasts or macrophages. In macrophages, however, gene expression of these markers was decreased in COPD patients compared to controls.
These results provide novel information regarding the gene expression of CRP and SAA in different cell types in the lung parenchyma. This study revealed differences in the expression of these markers according to cell type and disease status and contributes to the identification of cell types that are responsible for the secretion of these molecules.
KeywordsChronic obstructive pulmonary disease Chronic systemic inflammatory syndrome Acute-phase reactants C-reactive protein Serum amyloid A
Chronic obstructive pulmonary disease (COPD) is associated with important extrapulmonary manifestations including cardiovascular disease, weight loss, skeletal muscle dysfunction, depression and osteoporosis . Although the pathobiology of these extra-pulmonary manifestations has not been fully determined, systemic inflammation has been implicated in the pathogenesis of the majority of these manifestations [2, 3]. In fact, several authors have suggested that COPD is part of a chronic systemic inflammatory syndrome .
Patients with COPD display systemic inflammation, measured either as increased circulating cytokines, chemokines and acute-phase proteins or as abnormalities in circulating cells [5, 6]. Acute-phase reactants are among the most studied biomarkers. In particular, C-reactive protein (CRP) is related to an accelerated decline in lung function and many other clinically relevant outcomes [7, 8]. Serum amyloid A (SAA), the other major acute-phase reactant in humans, has also been shown to be elevated in COPD patients .
There has been considerable interest in identifying the nature of COPD-mediated systemic inflammation, as such knowledge may help predict clinical responses to therapy and identify new therapeutic targets. One important issue is identifying the origin of systemic inflammation, which is currently controversial . This would be a major advancement, and doing so could have an important diagnostic impact by identifying therapeutic targets to prevent disease progression to other organs, thereby preventing comorbidities . The current hypothesis holds that this inflammation is generated within the lung and produces an overflow (referred to in the literature as “spill-over”) of inflammatory mediators into the bloodstream .
Previous studies have described how lung tissue can synthesize acute-phase biomarkers in healthy tissue as well as in animal or cell models . Additionally, our group has reported that, in addition to the liver, the lung can also synthesize CRP and SAA. Interestingly, de-novo synthesis of CRP and SAA is increased in patients with COPD compared to disease-free smokers (“resistant smokers”), and this synthesis is differentially expressed in whole tissue samples depending on the anatomical location, such as the bronchus or the parenchyma .
In the present study, we aimed to investigate the cell types within lung tissue that express these biomarkers. We hypothesized that the expression of acute-phase reactants in lung tissue would differ with respect to the cell type used and would vary between COPD patients and healthy smokers. The objectives of this study were to characterize the gene expression of CRP and SAA in key lung cell types, including epithelial cells, macrophages and human lung fibroblasts, and to compare the gene expression profiles of COPD patients and healthy smokers.
We recruited consecutive patients from the surgical waiting list from February 2010 to June 2012 who were about to undergo elective pneumonectomy or lobectomy for suspected primary lung cancer. The study was approved by the institutional review board at Hospital Virgen del Rocío, and patients provided written informed consent prior to being included in the study. Each patient was identified upon his or her day of admission (i.e., the day before surgery was planned). Patients who were under 40 years of age, had a history of acute respiratory infection during the preceding 2 months, had been previously diagnosed with a neoplasm, had received radiotherapy or chemotherapy prior to the surgery or had suffered from chronic inflammatory disease were excluded from the study. Furthermore, time from the opening of the cutaneous layer to the extraction of the anatomical sample was measured, and cases in which this time was greater than 3 hours were also excluded from the study, as any potential stimulation of the studied biomarkers due to surgery could not be ruled out.
Medical records were checked to ensure that the patients had recently been tested for lung function. Patients whose pre-surgical spirometry results revealed a forced expiratory volume in the first second (FEV1)/forced vital capacity (FVC) ratio <0.7 were classified as COPD, and the remaining resistant smokers were used as control subjects. All patients completed a standardized questionnaire regarding their medical history, tobacco consumption and actual treatments. Comorbidities were evaluated using the Charlson index . Furthermore, the TNM staging of the primary lesion  and information regarding the surgical procedure were also collected. During surgery, a portion of the lung parenchyma of approximately 1 cm2 in area and 0.5 cm thick that was grossly normal and distant from the injury that had motivated the intervention was selected. This separation was performed in the operating room, and the sample was immediately placed in sterile surgical biopsy ice for preservation. The rest of the surgical piece followed the usual guidelines according to hospital protocol and the patient’s clinical case. To exclude bronchial colonization that could bias our results, analyses of microbiological colonization were performed at two time points: first, during the bronchoscopy that was performed to establish the diagnosis and to study the extent of the primary lesion, and second, prior to extraction of the tissue by obtaining an intrabronchial sample from the resected bronchus.
The collected samples consisted of pulmonary parenchyma tissues from each of the patients (COPD cases and controls).To determine the gene expression levels of acute-phase reactants in different cell types, we performed cell disintegration of the fibroblasts, epithelial cells and macrophages. Disintegration consisted of mechanical grinding using a scalpel to achieve fragmentation and treatment with enzymes in a digestion medium composed of RPMI, 5% fetal bovine serum (FBS), 1% streptomycin/penicillin,1% L-glutamine (all from PAA Laboratories, Gmb, Germany), 0.1 mM 2-β-mercaptoethanol (Sigma, GmbH, Germany), 1 mg/mL collagenase I (Sigma, GmbH, Germany) and 0.02 mg/mL DNase I. The samples were maintained in this medium at 37°C for 25 minutes and were then neutralized with collagenase and DNase in RPMI supplemented with 5% FBS, 1% streptomycin/penicillin and 1% L-glutamine. Once neutralized, the samples were centrifuged at 1000 rpm for 10 minutes at 4°C. The supernatant was then removed, and the pellets were washed with a solution of PBS/10 mM EDTA. Next, the samples were filtered at 40 microns (Becton Dickinson, NJ, USA) and were again centrifuged at 1000 rpm for 5 min at 4°C, followed by removal of the supernatant. We performed erythrocyte lysis on the pellets (Erythrocyte lysis buffer, QIAGEN, Gmb, Germany) following the manufacturer’s protocol. Separation of the different cell types was performed by binding cell-specific antibodies to magnetic beads (MACS microbeads, Miltenyi Biotec, Bergisch Gladbach, Germany) according to the manufacturer’s instructions. The selected markers were CD326 (for epithelial cells), CD14 (for macrophages) and anti-fibroblast (for fibroblasts). After incubating the samples with the various antibodies, they were passed through a magnetic separation column (MACS MS column, Miltenyi Biotec, Bergisch Gladbach, Germany). Then, the cells remaining in the columns were collected (CD326+, CD14+ or fibroblasts), and RNA extraction was performed using the TRIzol-chloroform method (TRIsureTM, Bioline Ltd., United Kingdom). The RNA was treated with RNase-free DNase using a commercial kit (QIAgen, GmbH) to remove any residual genomic DNA, and cDNA was synthesized using an iScript kit (Bio-Rad, CA). Each reaction was duplicated at a total volume of 25 μL and contained 2 μL cDNA (40 ng/μL) and 12.5 μL SYBR Green. Cell purity was determined by flow cytometry in all of the samples. The results indicated cell purity values close to 90%, with no major differences among samples.
Primers used in this study
Statistical analysis was performed using the Statistical Package for Social Sciences (SPSS), version 20.0 (IBM Corporation, Somers, NY, USA). Absolute and relative frequencies were used to describe qualitative variables. Quantitative variables were expressed in terms of means and standard deviations. The analysis of RFA expression at the cellular level between COPD patients and resistant smokers was performed using the Mann–Whitney U test. Correlations were assessed using Spearman’s coefficient. Logistic regression analysis was used to investigate whether significant differences between the two study groups persisted after adjustment for body mass index, age, gender, FEV1 and the Charlson index. The accepted alpha error was 0.05.
Patients and procedures
Controls (n = 34)
COPD (n = 40)
Tobacco history (pack-years)
Comorbidities (Charlson index)
Expression of acute-phase reactants in epithelial cells, macrophages and human lung fibroblasts
Within one cell type, the gene expression patterns of these biomarkers were correlated. In fibroblasts, there was a strong correlation between the SAA1 and SAA2 genes (r = 0.608, p < 0001). However, there was no evidence of a correlation between SAA1 (r = 0.387, p = 0.001) or SAA2 (r = 0.201, p = 0.086) and CRP. In epithelial cells, the highest correlations were between the different SAA genes (SAA1 vs. SAA2: r = 0.962, p < 0.001), with weaker correlations between the SAA and CRP genes (CRP and SAA1: r = 0.579, p < 0.001; CRP and SAA2: r = 0.452, p < 0.001). However, in macrophages, the correlations were uniformly low across all biomarkers, with r values of approximately 0.4 and p values <0.001 for all comparisons.
Gene expression of acute-phase reactants in these cell groups between COPD patients and healthy smokers
In epithelial cells, gene expression was also increased, albeit the difference was less striking (Figure 3). In epithelial cells, there was a striking increase in CRP, which was not observed in fibroblasts or macrophages. In macrophages, however, gene expression was decreased in COPD patients compared to controls, particularly for SAA1 and SAA2, with no change in CRP (Figure 4). The results of multivariate analysis indicated that these results did not appreciably change after adjustment for potential confounders, including body mass index, age, gender, FEV1 and the Charlson index.
The present study provides novel information regarding the expression of CRP and SAA in the lung parenchyma. We identified differences in production according to the cell type and the presence or absence of disease. The results of the present study reflect two main findings: firstly, all fibroblasts, epithelial cells and macrophages express CRP and SAA, and secondly, expression of both markers differs according to cell type and the presence of disease.
To correctly interpret the results, several issues should be considered. First, because all the study subjects were admitted for a pulmonary resection (lobectomy or pneumonectomy) for suspected primary lung cancer and therefore met the criteria for surgery, 92.3% of the COPD patients had mildly or moderately impaired lung function. Therefore, this was not representative of all COPD patients because there were few surgical specimens from patients with advanced-stage COPD. Second, the resected neoplasms included several tumor types and several non-neoplastic cases, and it is unclear whether the observed changes were dependent on tumor type. In the present study, histological types were adequately distributed with proportional numbers for each type of neoplasm, and we found no influence of tumor type on the results. Third, although the tissues analyzed were not macroscopically affected by the tumors, it remains unclear whether microscopic influences maybe involved. Data from the diagnostic techniques and current high-resolution images make this possibility very unlikely. However, different genetic predispositions for COPD cases with and without lung cancer have previously been described . Therefore, the results of our project should be strictly applied to patients with COPD with similarly located lung neoplasms. Fourth, because surgery itself can potentially stimulate the studied biomarkers, cases for which the time between the opening of the skin plane and surgical excision exceeded 3 hours were excluded. The described increase in reactants occurs several hours following acute injury and remains elevated for several days . Therefore, three hours was considered a reasonable time for such surgical procedures without complications. Fifth, these results apply to the lung parenchyma. This implies that fibroblasts, macrophages and epithelial cells are obtained, in the best case, in the terminal bronchi and the lung parenchyma. In this regard, the roles of these cells may be more relevant to heavier gauged airways . In contrast, the expected effect of COPD on the parenchyma would be emphysema, which would result from an imbalance between various pathogenetic mechanisms, such as oxidation-antioxidation equilibrium , protease-antiprotease equilibrium  and potentiation of apoptosis . Consequently, epithelial cells, macrophages and fibroblasts are absent or diminished in number. However, we have been able to demonstrate differential gene expression in the bronchus compared to the parenchyma in COPD patients . Thus, future studies should also include samples from the bronchial airway to complement the present study. Sixth, there are other cell types that maybe potential sources of these biomarkers, including dendritic or endovascular cells. The present study should be expanded to include other cell types to more comprehensively represent the true scenario. Finally, we did not measure serum protein concentrations of these biomarkers to test whether gene expression translates to the serum, which would provide a necessary link to systemic inflammation.
The role of these cell types in the pathogenesis of COPD has previously been studied, and the differential expression patterns in fibroblasts and epithelial cells compared to macrophages merits comment. Our results seem to suggest that epithelial cells and fibroblasts play a major role in inflammatory gene expression in COPD. Bronchial biopsy studies have identified epithelial cells as components of inflammation . Moreover, this relationship is associated with smoking intensity . The predominance of synthesis in epithelial cells of COPD patients could be a consequence of remodeling that occurs in the lung tissue of patients with COPD . In this regard, one potential mechanism contributing to airway fibrosis is the transition of airway epithelial cells to a mesenchymal phenotype expressing myofibroblast characteristics and capable to migrate into the lamina propria. Such a process has been termed epithelial mesenchymal transition (EMT) . When this phenomenon is accompanied by angiogenesis, it can explain the increased risk of malignant transformation predominantly observed in the large airways of COPD patients . The potential role played by EMT in the pathogenesis of COPD is currently a very active area of research . Although this study was not specifically focused on this issue, we believe that it may contribute to the ongoing scientific debate in the field.
Fibroblasts are principally responsible for the production and maintenance of the lung extracellular matrix . These cells are involved in the pathogenesis of COPD, particularly in the small bronchial airway, and their peribronchiolar proliferation has been described as the most limiting factor in the pathogenesis of chronic airflow obstruction . Furthermore, alterations in the functional capacity of these fibroblasts can play a role in the pathogenesis of pulmonary emphysema, which results in a breakdown of the tissue.
Conversely, gene expression in macrophages has the reverse pattern. Macrophages play a very important role in the pathogenesis of COPD . They are central to coordinating immunity against inhaled particles dissolved in smoke due to their role as first-line, innate defenders against chronic noxious stimuli in the airway and lung parenchyma. However, their role in the synthesis of these biomarkers is decreased. One explanation might be that they are dedicated to other inflammatory functions in the context of COPD.
The differences found in our study did not appreciably change after adjusting for potential confounders, including body mass index, age, gender, FEV1 and the Charlson index. Although these variables have been associated with the systemic inflammatory load [34, 35], few data are available on their relationships with local inflammatory biomarkers in respiratory tissues. In the present study, we failed to identify such an association. However, the current results should be taken with caution because the sample size may be too small for assessing the potential impact of such variables. Future studies may utilize the information provided in this study for determining an adequate sample size to investigate such associations. Moreover, further research is needed to assess the potential relationships of potential confounders with respiratory biomarkers obtained using non-invasive methods .
Although in this study we did not specifically measure the systemic inflammatory load of the study participants, one of the most obvious explanations for the presence of systemic inflammation in COPD is that local inflammatory processes occurring in the lung may cause a “spills over” of proinflammatory molecules into the systemic circulation . However, the results of previous studies do not completely support this hypothesis because of the lack of association between airway cytokine concentrations and the corresponding systemic levels . Even though a correlation between serum and tissue expression should be obtained to support the “spill over” hypothesis, mRNA quantification cannot provide reliable information as to whether: a) the mRNA will be translated into a protein, b) a functional protein will be translated and c) if such a protein will be finally released into the circulation . It is also noteworthy that mRNA and protein concentrations do not always correlate . Further functional studies are needed to understand the complex relationships between local and systemic inflammation in COPD patients.
The present study provides novel data regarding the expression of CRP and SAA genes in the lung parenchyma and indicates which cell types are primarily responsible for gene expression of CRP and SAA. The study also uncovers differences in production according to cell type and the presence or absence of COPD. The results of the present study advance the field’s understanding of COPD pathogenesis and the role of systemic inflammation. Future studies should advance our understanding of gene expression in other cell types and the relationship between gene expression and the final serum concentrations of these proteins.
The authors are thankful to Enzo Emanuele, MD, PhD (Living Research s.a.s., Robbio, Italy) for his expert editorial assistance.
- López Varela MV, Montes de Oca M, Halbert R, Muiño A, Tálamo C, Pérez-Padilla R, Jardim JR, Valdivia G, Pertuzé J, Menezes AM, PLATINO team: Comorbidities and health status in individuals with and without COPD in five latin american cities: the PLATINO study. Arch Bronconeumol. 2013, 49: 468-474.View ArticlePubMedGoogle Scholar
- Vanfleteren LE, Spruit MA, Groenen M, Gaffron S, van Empel VP, Bruijnzeel PL, Rutten EP, Op ’t Roodt J, Wouters EF, Franssen FM: Clusters of comorbidities based on validated objective measurements and systemic inflammation in patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2013, 187: 728-735. 10.1164/rccm.201209-1665OC.View ArticlePubMedGoogle Scholar
- Miller J, Edwards LD, Agusti A, Bakke P, Calverley PM, Celli B, Coxson HO, Crim C, Lomas DA, Miller BE, Rennard S, Silverman EK, Tal-Singer R, Vestbo J, Wouters E, Yates JC, Macnee W: Comorbidity, systemic inflammation and outcomes in the ECLIPSE cohort. Respir Med. 2013, 107: 1376-1384. 10.1016/j.rmed.2013.05.001.View ArticlePubMedGoogle Scholar
- Fabbri LM, Rabe KF: From COPD to chronic systemic inflammatory syndrome?. Lancet. 2007, 370: 797-799. 10.1016/S0140-6736(07)61383-X.View ArticlePubMedGoogle Scholar
- Garcia-Rio F, Miravitlles M, Soriano JB, Munoz L, Duran-Tauleria E, Sánchez G, Sobradillo V, Ancochea J, EPI-SCAN Steering Committee: Systemic inflammation in chronic obstructive pulmonary disease: a population-based study. Respir Res. 2010, 11: 63-10.1186/1465-9921-11-63.View ArticlePubMedPubMed CentralGoogle Scholar
- Agusti A, Soriano JB: COPD as a systemic disease. COPD. 2008, 5: 133-138. 10.1080/15412550801941349.View ArticlePubMedGoogle Scholar
- Gan WQ, Man SF, Senthilselvan A, Sin DD: Association between chronic obstructive pulmonary disease and systemic inflammation: a systematic review and a meta-analysis. Thorax. 2004, 59: 574-580. 10.1136/thx.2003.019588.View ArticlePubMedPubMed CentralGoogle Scholar
- Wouters EF, Groenewegen KH, Dentener MA, Vernooy JH: Systemic inflammation in chronic obstructive pulmonary disease: the role of exacerbations. Proc Am Thorac Soc. 2007, 4: 626-634. 10.1513/pats.200706-071TH.View ArticlePubMedGoogle Scholar
- Smith DJ, Yerkovich ST, Towers MA, Carroll ML, Thomas R, Upham JW: Reduced soluble receptor for advanced glycation end-products in COPD. Eur Respir J. 2011, 37: 516-522. 10.1183/09031936.00029310.View ArticlePubMedGoogle Scholar
- Sunyer J, Pistelli R, Plana E, Andreani M, Baldari F, Kolz M, Koenig W, Pekkanen J, Peters A, Forastiere F: Systemic inflammation, genetic susceptibility and lung function. Eur Respir J. 2008, 32: 92-97. 10.1183/09031936.00052507.View ArticlePubMedGoogle Scholar
- Sode BF, Dahl M, Nordestgaard BG: Myocardial infarction and other co-morbidities in patients with chronic obstructive pulmonary disease: a Danish nationwide study of 7.4 million individuals. Eur Heart J. 2011, 32: 2365-2375. 10.1093/eurheartj/ehr338.View ArticlePubMedGoogle Scholar
- Sinden NJ, Stockley RA: Systemic inflammation and comorbidity in COPD: a result of ‘overspill’ of inflammatory mediators from the lungs? Review of the evidence. Thorax. 2010, 65: 930-936. 10.1136/thx.2009.130260.View ArticlePubMedGoogle Scholar
- Donaldson GC, Seemungal TA, Patel IS, Bhowmik A, Wilkinson TM, Hurst JR, MacCallum PK, Wedzicha JA: Airway and systemic inflammation and decline in lung function in patients with COPD. Chest. 2005, 128: 1995-2004. 10.1378/chest.128.4.1995.View ArticlePubMedGoogle Scholar
- López-Campos JL, Calero C, Rojano B, López-Porras M, Sáenz-Coronilla J, Blanco AI, Sánchez-López V, Tobar D, Montes-Worboys A, Arellano E: C-reactive protein and serum amyloid a overexpression in lung tissues of chronic obstructive pulmonary disease patients: a case–control study. Int J Med Sci. 2013, 10: 938-947. 10.7150/ijms.6152.View ArticlePubMedPubMed CentralGoogle Scholar
- Charlson M, Szatrowski TP, Peterson J, Gold J: Validation of a combined comorbidity index. J Clin Epidemiol. 1994, 47: 1245-1251. 10.1016/0895-4356(94)90129-5.View ArticlePubMedGoogle Scholar
- León-Atance P, Moreno-Mata N, González-Aragoneses F, Cañizares-Carretero MÁ, García-Jiménez MD, Genovés-Crespo M, Honguero-Martínez AF, Rombolá CA, Simón-Adiego CM, Peñalver-Pascual R: Multicenter analysis of survival and prognostic factors in pathologic stage I non-small-cell lung cancer according to the new 2009 TNM classification. Arch Bronconeumol. 2011, 47: 441-446.PubMedGoogle Scholar
- Malle E, De Beer FC: Human serum amyloid A (SAA) protein: a prominent acute-phase reactant for clinical practice. Eur J Clin Invest. 1996, 26: 427-435. 10.1046/j.1365-2362.1996.159291.x.View ArticlePubMedGoogle Scholar
- Schmittgen TD, Livak KJ: Analyzing real-time PCR data by the comparative C(T) method. Nat Protoc. 2008, 3: 1101-1108. 10.1038/nprot.2008.73.View ArticlePubMedGoogle Scholar
- de Andrade M, Li Y, Marks RS, Deschamps C, Scanlon PD, Olswold CL, Jiang R, Swensen SJ, Sun Z, Cunningham JM, Wampfler JA, Limper AH, Midthun DE, Yang P: Genetic variants associated with the risk of chronic obstructive pulmonary disease with and without lung cancer. Cancer Prev Res (Phila). 2012, 5: 365-373. 10.1158/1940-6207.CAPR-11-0243.View ArticleGoogle Scholar
- Gabay C, Kushner I: Acute-phase proteins and other systemic responses to inflammation. N Engl J Med. 1999, 340: 448-454. 10.1056/NEJM199902113400607.View ArticlePubMedGoogle Scholar
- Gorska K, Maskey-Warzechowska M, Krenke R: Airway inflammation in chronic obstructive pulmonary disease. Curr Opin Pulm Med. 2010, 16: 89-96. 10.1097/MCP.0b013e3283341ba0.View ArticlePubMedGoogle Scholar
- Rahman I, Adcock IM: Oxidative stress and redox regulation of lung inflammation in COPD. Eur Respir J. 2006, 28: 219-242. 10.1183/09031936.06.00053805.View ArticlePubMedGoogle Scholar
- Elkington PT, Friedland JS: Matrix metalloproteinases in destructive pulmonary pathology. Thorax. 2006, 61: 259-266. 10.1136/thx.2005.051979.View ArticlePubMedPubMed CentralGoogle Scholar
- Henson PM, Cosgrove GP, Vandivier RW: State of the art. Apoptosis and cell homeostasis in chronic obstructive pulmonary disease. Proc Am Thorac Soc. 2006, 3: 512-516. 10.1513/pats.200603-072MS.View ArticlePubMedPubMed CentralGoogle Scholar
- Saetta M, Di Stefano A, Maestrelli P, Ferraresso A, Drigo R, Potena A, Ciaccia A, Fabbri LM: Activated T-lymphocytes and macrophages in bronchial mucosa of subjects with chronic bronchitis. Am Rev Respir Dis. 1993, 147: 301-306. 10.1164/ajrccm/147.2.301.View ArticlePubMedGoogle Scholar
- Auerbach O, Stout AP, Hammond EC, Garfinkel L: Changes in bronchial epithelium in relation to cigarette smoking and in relation to lung cancer. N Engl J Med. 1961, 265: 253-267. 10.1056/NEJM196108102650601.View ArticlePubMedGoogle Scholar
- Górska K, Krenke R, Kosciuch J, Korczynski P, Zukowska M, Domagala-Kulawik J, Maskey-Warzechowska M, Chazan R: Relationship between airway inflammation and remodeling in patients with asthma and chronic obstructive pulmonary disease. Eur J Med Res. 2009, 14 (Suppl 4): 90-96.PubMedPubMed CentralGoogle Scholar
- Sohal SS, Reid D, Soltani A, Ward C, Weston S, Muller HK, Wood-Baker R, Walters EH: Evaluation of epithelial mesenchymal transition in patients with chronic obstructive pulmonary disease. Respir Res. 2011, 12: 130-10.1186/1465-9921-12-130.View ArticlePubMedPubMed CentralGoogle Scholar
- Wang Q, Wang Y, Zhang Y, Zhang Y, Xiao W: The role of uPAR in epithelial-mesenchymal transition in small airway epithelium of patients with chronic obstructive pulmonary disease. Respir Res. 2013, 14: 67-10.1186/1465-9921-14-67.View ArticlePubMedPubMed CentralGoogle Scholar
- Sohal SS, Reid D, Soltani A, Ward C, Weston S, Muller HK, Wood-Baker R, Walters EH: Reticular basement membrane fragmentation and potential epithelial mesenchymal transition is exaggerated in the airways of smokers with chronic obstructive pulmonary disease. Respirology. 2010, 15: 930-938. 10.1111/j.1440-1843.2010.01808.x.View ArticlePubMedGoogle Scholar
- Hogg JC, Chu F, Utokaparch S, Woods R, Elliott WM, Buzatu L, Cherniack RM, Rogers RM, Sciurba FC, Coxson HO, Paré PD: The nature of small-airway obstruction in chronic obstructive pulmonary disease. N Engl J Med. 2004, 350: 2645-2653. 10.1056/NEJMoa032158.View ArticlePubMedGoogle Scholar
- Togo S, Holz O, Liu X, Sugiura H, Kamio K, Wang X, Kawasaki S, Ahn Y, Fredriksson K, Skold CM, Mueller KC, Branscheid D, Welker L, Watz H, Magnussen H, Rennard SI: Lung fibroblast repair functions in patients with chronic obstructive pulmonary disease are altered by multiple mechanisms. Am J Respir Crit Care Med. 2008, 178: 248-260. 10.1164/rccm.200706-929OC.View ArticlePubMedPubMed CentralGoogle Scholar
- Spurzem JR, Rennard SI: Pathogenesis of COPD. Semin Respir Crit Care Med. 2005, 26: 142-153. 10.1055/s-2005-869535.View ArticlePubMedGoogle Scholar
- Thomsen M, Dahl M, Lange P, Vestbo J, Nordestgaard BG: Inflammatory biomarkers and comorbidities in chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2012, 186: 982-988. 10.1164/rccm.201206-1113OC.View ArticlePubMedGoogle Scholar
- Gaki E, Kontogianni K, Papaioannou AI, Bakakos P, Gourgoulianis KI, Kostikas K, Alchanatis M, Papiris S, Loukides S: Associations between BODE index and systemic inflammatory biomarkers in COPD. COPD. 2011, 8: 408-413. 10.3109/15412555.2011.619599.View ArticlePubMedGoogle Scholar
- Hillas G, Loukides S, Kostikas K, Bakakos P: Biomarkers obtained by non-invasive methods in patients with COPD: where do we stand, what do we expect?. Curr Med Chem. 2009, 16: 2824-2838. 10.2174/092986709788803178.View ArticlePubMedGoogle Scholar
- Vernooy JH, Küçükaycan M, Jacobs JA, Chavannes NH, Buurman WA, Dentener MA, Wouters EF: Local and systemic inflammation in patients with chronic obstructive pulmonary disease: soluble tumor necrosis factor receptors are increased in sputum. Am J Respir Crit Care Med. 2002, 166: 1218-1224. 10.1164/rccm.2202023.View ArticlePubMedGoogle Scholar
- Bustin SA, Benes V, Garson JA, Hellemans J, Huggett J, Kubista M, Mueller R, Nolan T, Pfaffl MW, Shipley GL, Vandesompele J, Wittwer CT: The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin Chem. 2009, 55: 611-622. 10.1373/clinchem.2008.112797.View ArticlePubMedGoogle Scholar
- Gygi SP, Rochon Y, Franza BR, Aebersold R: Correlation between protein and mRNA abundance in yeast. Mol Cell Biol. 1999, 19: 1720-1730.View ArticlePubMedPubMed CentralGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2466/14/95/prepub
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