Disease progression of chronic obstructive pulmonary disease (COPD) is variable, with some patients having a relatively stable course, while others suffer relentless progression leading to severe breathlessness, frequent acute exacerbations of COPD (AECOPD), respiratory failure and death. Radiological markers such as CT emphysema index, bronchiectasis and coronary artery calcification (CAC) have been linked with increased mortality in COPD patients. Molecular changes in lung tissue reflect alterations in lung pathology that occur with disease progression; however, lung tissue is not routinely accessible. Cell counts (including neutrophils) and mediators in induced sputum have been associated with lung function and risk of exacerbations. Examples of peripheral blood biological markers (biomarkers) include those associated with lung function (reduced CC-16), emphysema severity (increased adiponectin, reduced sRAGE), exacerbations and mortality [increased CRP, fibrinogen, leukocyte count, IL-6, IL-8, and tumor necrosis factor α (TNF-α)] including increased YKL-40 with mortality. Emerging approaches to discovering markers of gene-environment interaction include exhaled breath analysis [volatile organic compounds (VOCs), exhaled breath condensate], cellular and systemic responses to exposure to air pollution, alterations in the lung microbiome, and biomarkers of lung ageing such as telomere length shortening and reduced levels of sirtuins. Overcoming methodological challenges in sampling and quality control will enable more robust yet easily accessible biomarkers to be developed and qualified, in order to optimise personalised medicine in patients with COPD.
Pulmonary disease; chronic obstructive; disease progression; biological markers (biomarkers); lung; sputum; blood
Chronic obstructive pulmonary disease (COPD) is a complex chronic lung disease characterised by progressive fixed airflow limitation and acute exacerbations that frequently require hospitalisation. Evidence-based clinical guidelines for the diagnosis and management of COPD are now widely available. However, the uptake of these COPD guidelines in clinical practice is highly variable, as is the case for many other chronic disease guidelines. Studies have identified many barriers to implementation of COPD and other guidelines, including factors such as lack of familiarity with guidelines amongst clinicians and inadequate implementation programs. Several methods for enhancing adherence to clinical practice guidelines have been evaluated, including distribution methods, professional education sessions, electronic health records (EHR), point of care reminders and computer decision support systems (CDSS). Results of these studies are mixed to date, and the most effective ways to implement clinical practice guidelines remain unclear. Given the significant resources dedicated to evidence-based medicine, effective dissemination and implementation of best practice at the patient level is an important final step in the process of guideline development. Future efforts should focus on identifying optimal methods for translating the evidence into everyday clinical practice to ensure that patients receive the best care.
Pulmonary disease; chronic obstructive; clinical practice guidelines; health services; evidence-based practice
MicroRNAs (MiRNA) are small non-coding RNAs that regulate gene expression. The aim of this study was to identify miRNAs differentially expressed between mild and moderately emphysematous lung, as well as their functional target mRNAs. Resected lung from patients with COPD undergoing lung cancer surgery was profiled using miRNA (Agilent Human miRNA profiler G4470 V1.01) and mRNA (OperonV2.0) microarrays. Cells of lung origin (BEAS-2B and HFL1) were profiled using mRNA microarrays (Illumina HumanHT-12 V3) after in vitro manipulation.
COPD patients had mean (SD) age 68 (6) years, FEV1 72 (17)% predicted and gas transfer (KCO) 70 (10)% predicted. Five miRNAs (miR-34c, miR-34b, miR-149, miR-133a and miR-133b) were significantly down-regulated in lung from patients with moderate compared to mild emphysema as defined by gas transfer (p < 0.01). In vitro upregulation of miR-34c in respiratory cells led to down-regulation of predicted target mRNAs, including SERPINE1, MAP4K4, ZNF3, ALDOA and HNF4A. The fold change in ex-vivo expression of all five predicted target genes inversely correlated with that of miR-34c in emphysematous lung, but this relationship was strongest for SERPINE1 (p = 0.05).
Differences in miRNA expression are associated with emphysema severity in COPD patients. MiR-34c modulates expression of its putative target gene, SERPINE1, in vitro in respiratory cell lines and ex vivo in emphysematous lung tissue.
Chronic obstructive pulmonary disease; microRNA; miR-34c; Microarray
Screening using low-dose computed tomography (CT) represents an exciting new development in the struggle to improve outcomes for people with lung cancer. Randomised controlled evidence demonstrating a 20% relative lung cancer mortality benefit has led to endorsement of screening by several expert bodies in the US and funding by healthcare providers. Despite this pivotal result, many questions remain regarding technical and logistical aspects of screening, cost-effectiveness and generalizability to other settings. This review discusses the rationale behind screening, the results of on-going trials, potential harms of screening and current knowledge gaps.
Lung neoplasms/mortality; mass screening tomography; helical computed; early detection of cancer/methods
Lung cancer is a disease with a dismal prognosis and is the biggest cause of cancer deaths in many countries. Nonetheless, rapid technological developments in genome science promise more effective prevention and treatment strategies. Since the Human Genome Project, scientific advances have revolutionized the diagnosis and treatment of human cancers, including thoracic cancers. The latest, massively parallel, next generation sequencing (NGS) technologies offer much greater sequencing capacity than traditional, capillary-based Sanger sequencing. These modern but costly technologies have been applied to whole genome-, and whole exome sequencing (WGS and WES) for the discovery of mutations and polymorphisms, transcriptome sequencing for quantification of gene expression, small ribonucleic acid (RNA) sequencing for microRNA profiling, large scale analysis of deoxyribonucleic acid (DNA) methylation and chromatin immunoprecipitation mapping of DNA-protein interaction.
With the rise of personalized cancer care, based on the premise of precision medicine, sequencing technologies are constantly changing. To date, the genomic landscape of lung cancer has been captured in several WGS projects. Such work has not only contributed to our understanding of cancer biology, but has also provided impetus for technical advances that may improve our ability to accurately capture the cancer genome. Issues such as short read lengths contribute to sequenced libraries that contain challenging gaps in the aligned genome. Emerging platforms promise longer reads as well as the ability to capture a range of epigenomic signals. In addition, ongoing optimization of bioinformatics strategies for data analysis and interpretation are critical, especially for the differentiation between driver and passenger mutations.
Moreover, broader deployment of these and future generations of platforms, coupled with an increasing bioinformatics workforce with access to highly sophisticated technologies, could see many of these discoveries translated to the clinic at a rapid pace. We look forward to these advances making a difference for the many patients we treat in the Asia-Pacific region and around the world.
High-throughput nucleotide sequencing; genomics; lung neoplasms; non-small cell lung carcinoma (NSCLC); small cell lung carcinoma (SCLC)
Malignant mesothelioma is an aggressive tumour of serosal surfaces most commonly pleura. Characterised cell lines represent a valuable tool to study the biology of mesothelioma. The aim of this study was to develop and biologically characterise six malignant mesothelioma cell lines to evaluate their potential as models of human malignant mesothelioma.
Five lines were initiated from pleural biopsies, and one from pleural effusion of patients with histologically proven malignant mesothelioma. Mesothelial origin was assessed by standard morphology, Transmission Electron Microscopy (TEM) and immunocytochemistry. Growth characteristics were assayed using population doubling times. Spectral karyotyping was performed to assess chromosomal abnormalities. Authentication of donor specific derivation was undertaken by DNA fingerprinting using a panel of SNPs.
Most of cell lines exhibited spindle cell shape, with some retaining stellate shapes. At passage 2 to 6 all lines stained positively for calretinin and cytokeratin 19, and demonstrated capacity for anchorage-independent growth. At passage 4 to 16, doubling times ranged from 30–72 hours, and on spectral karyotyping all lines exhibited numerical chromosomal abnormalities ranging from 41 to 113. Monosomy of chromosomes 8, 14, 22 or 17 was observed in three lines. One line displayed four different karyotypes at passage 8, but only one karyotype at passage 42, and another displayed polyploidy at passage 40 which was not present at early passages. At passages 5–17, TEM showed characteristic features of mesothelioma ultrastructure in all lines including microvilli and tight intercellular junctions.
These six cell lines exhibit varying cell morphology, a range of doubling times, and show diverse passage-dependent structural chromosomal changes observed in malignant tumours. However they retain characteristic immunocytochemical protein expression profiles of mesothelioma during maintenance in artificial culture systems. These characteristics support their potential as in vitro model systems for studying cellular, molecular and genetic aspects of mesothelioma.
The diagnosis of malignant pleural effusions (MPE) is often clinically challenging, especially if the cytology is negative for malignancy. DNA integrity index has been reported to be a marker of malignancy. The aim of this study was to evaluate the utility of pleural fluid DNA integrity index in the diagnosis of MPE.
We studied 75 pleural fluid and matched serum samples from consecutive subjects. Pleural fluid and serum ALU DNA repeats [115bp, 247bp and 247bp/115bp ratio (DNA integrity index)] were assessed by real-time quantitative PCR. Pleural fluid and serum mesothelin levels were quantified using ELISA.
Based on clinico-pathological evaluation, 52 subjects had MPE (including 16 mesotheliomas) and 23 had benign effusions. Pleural fluid DNA integrity index was higher in MPE compared with benign effusions (1.2 vs. 0.8; p<0.001). Cytology had a sensitivity of 55% in diagnosing MPE. If cytology and pleural fluid DNA integrity index were considered together, they exhibited 81% sensitivity and 87% specificity in distinguishing benign and malignant effusions. In cytology-negative pleural effusions (35 MPE and 28 benign effusions), elevated pleural fluid DNA integrity index had an 81% positive predictive value in detecting MPEs. In the detection of mesothelioma, at a specificity of 90%, pleural fluid DNA integrity index had similar sensitivity to pleural fluid and serum mesothelin (75% each respectively).
Pleural fluid DNA integrity index is a promising diagnostic biomarker for identification of MPEs, including mesothelioma. This biomarker may be particularly useful in cases of MPE where pleural aspirate cytology is negative, and could guide the decision to undertake more invasive definitive testing. A prospective validation study is being undertaken to validate our findings and test the clinical utility of this biomarker for altering clinical practice.
Malignant pleural effusions; Mesothelioma; Lung cancer; DNA integrity index; Mesothelin
Pulmonary hypertension (PH) is a complication of chronic obstructive pulmonary disease (COPD). This study examined genetic variations in mediators of vascular remodelling and their association with PH in patients with COPD. In patients with COPD, we genotyped 7 SNPs in 6 candidate PH genes (NOS3, ACE, EDN1, PTGIS, SLC6A4, VEGFA). We tested for association with right ventricular systolic pressure (RVSP), spirometry and gas transfer, and hypoxemia.
In patients with COPD, we genotyped 7 SNPs in 6 candidate PH genes (NOS3, ACE, EDN1, PTGIS, SLC6A4, VEGFA). We tested for association with right ventricular systolic pressure (RVSP), spirometry and gas transfer, and hypoxemia.
580 COPD patients were recruited, 341 patients had a transthoracic echocardiogram, with RVSP measurable in 278 patients (mean age 69 years, mean FEV1 50% predicted, mean RVSP 44 mmHg, median history of 50 pack-years). Of the 7 tested SNPs, the NOS3-VNTR polymorphism was significantly associated with RVSP in a dose-dependent fashion for the risk allele: mean RVSP for a/a and a/b genotypes were 52.0 and 46.6 mmHg respectively, compared to 43.2 mmHg for b/b genotypes (P = 0.032). No associations were found between RVSP and other polymorphisms. ACE II or ID genotypes were associated with a lower FEV1% predicted than the ACE DD genotype (P = 0.028). The NOS3-298 TT genotype was associated with lower KCO % predicted than the NOS3-298 GG or GT genotype (P = 0.031).
The NOS3-VNTR polymorphism was associated with RVSP in patients with COPD, supporting its involvement in the pathogenesis of PH in COPD. ACE and NOS3 genotypes were associated with COPD disease severity, but not with the presence of PH. Further study of these genes could lead to the development of prognostic and screening tools for PH in COPD.
COPD; Pulmonary hypertension; Genetic polymorphism
Asbestos-related lung cancer accounts for 4–12% of lung cancers worldwide. We have previously identified ADAM28 as a putative oncogene involved in asbestos-related lung adenocarcinoma (ARLC-AC). We hypothesised that similarly gene expression profiling of asbestos-related lung squamous cell carcinomas (ARLC-SCC) may identify candidate oncogenes for ARLC-SCC. We undertook a microarray gene expression study in 56 subjects; 26 ARLC-SCC (defined as lung asbestos body (AB) counts >20AB/gram wet weight (gww) and 30 non-asbestos related lung squamous cell carcinoma (NARLC-SCC; no detectable lung asbestos bodies; 0AB/gww). Microarray and bioinformatics analysis identified six candidate genes differentially expressed between ARLC-SCC and NARLC-SCC based on statistical significance (p<0.001) and fold change (FC) of >2-fold. Two genes MS4A1 and CARD18, were technically replicated by qRT-PCR and showed consistent directional changes. As we also found MS4A1 to be overexpressed in ARLC-ACs, we selected this gene for biological validation in independent test sets (one internal, and one external dataset (2 primary tumor sets)). MS4A1 RNA expression dysregulation was validated in the external dataset but not in our internal dataset, likely due to the small sample size in the test set as immunohistochemical (IHC) staining for MS4A1 (CD20) showed that protein expression localized predominantly to stromal lymphocytes rather than tumor cells in ARLC-SCC. We conclude that differential expression of MS4A1 in this comparative gene expression study of ARLC-SCC versus NARLC-SCC is a stromal signal of uncertain significance, and an example of the rationale for tumor cell enrichment in preparation for gene expression studies where the aim is to identify markers of particular tumor phenotypes. Finally, our study failed to identify any strong gene candidates whose expression serves as a marker of asbestos etiology. Future research is required to determine the role of stromal lymphocyte MS4A1 dysregulation in pulmonary SCCs caused by asbestos.
Lung cancer is a leading cause of cancer related morbidity and mortality globally, and carries a dismal prognosis. Improved understanding of the biology of cancer is required to improve patient outcomes. Next-generation sequencing (NGS) is a powerful tool for whole genome characterisation, enabling comprehensive examination of somatic mutations that drive oncogenesis. Most NGS methods are based on polymerase chain reaction (PCR) amplification of platform-specific DNA fragment libraries, which are then sequenced. These techniques are well suited to high-throughput sequencing and are able to detect the full spectrum of genomic changes present in cancer. However, they require considerable investments in time, laboratory infrastructure, computational analysis and bioinformatic support. Next-generation sequencing has been applied to studies of the whole genome, exome, transcriptome and epigenome, and is changing the paradigm of lung cancer research and patient care. The results of this new technology will transform current knowledge of oncogenic pathways and provide molecular targets of use in the diagnosis and treatment of cancer. Somatic mutations in lung cancer have already been identified by NGS, and large scale genomic studies are underway. Personalised treatment strategies will improve care for those likely to benefit from available therapies, while sparing others the expense and morbidity of futile intervention. Organisational, computational and bioinformatic challenges of NGS are driving technological advances as well as raising ethical issues relating to informed consent and data release. Differentiation between driver and passenger mutations requires careful interpretation of sequencing data. Challenges in the interpretation of results arise from the types of specimens used for DNA extraction, sample processing techniques and tumour content. Tumour heterogeneity can reduce power to detect mutations implicated in oncogenesis. Next-generation sequencing will facilitate investigation of the biological and clinical implications of such variation. These techniques can now be applied to single cells and free circulating DNA, and possibly in the future to DNA obtained from body fluids and from subpopulations of tumour. As costs reduce, and speed and processing accuracy increase, NGS technology will become increasingly accessible to researchers and clinicians, with the ultimate goal of improving the care of patients with lung cancer.
High-throughput nucleotide sequencing; DNA sequence analysis; lung neoplasms; non-small cell lung carcinoma; small cell lung carcinoma
Primary tumor recurrence commonly occurs after surgical resection of lung squamous cell carcinoma (SCC). Little is known about the genes driving SCC recurrence.
We used array comparative genomic hybridization (aCGH) to identify genes affected by copy number alterations that may be involved in SCC recurrence. Training and test sets of resected primary lung SCC were assembled. aCGH was used to determine genomic copy number in a training set of 62 primary lung SCCs (28 with recurrence and 34 with no evidence of recurrence) and the altered copy number of candidate genes was confirmed by quantitative PCR (qPCR). An independent test set of 72 primary lung SCCs (20 with recurrence and 52 with no evidence of recurrence) was used for biological validation. mRNA expression of candidate genes was studied using qRT-PCR. Candidate gene promoter methylation was evaluated using methylation microarrays and Sequenom EpiTYPER analysis.
18q22.3 loss was identified by aCGH as being significantly associated with recurrence (p = 0.038). Seven genes within 18q22.3 had aCGH copy number loss associated with recurrence but only SOCS6 copy number was both technically replicated by qPCR and biologically validated in the test set. SOCS6 copy number loss correlated with reduced mRNA expression in the study samples and in the samples with copy number loss, there was a trend for increased methylation, albeit non-significant. Overall survival was significantly poorer in patients with SOCS6 loss compared to patients without SOCS6 loss in both the training (30 vs. 43 months, p = 0.023) and test set (27 vs. 43 months, p = 0.010).
Reduced copy number and mRNA expression of SOCS6 are associated with disease recurrence in primary lung SCC and may be useful prognostic biomarkers.
To classify automatically lung tumor–node–metastases (TNM) cancer stages from free-text pathology reports using symbolic rule-based classification.
By exploiting report substructure and the symbolic manipulation of systematized nomenclature of medicine–clinical terms (SNOMED CT) concepts in reports, statements in free text can be evaluated for relevance against factors relating to the staging guidelines. Post-coordinated SNOMED CT expressions based on templates were defined and populated by concepts in reports, and tested for subsumption by staging factors. The subsumption results were used to build logic according to the staging guidelines to calculate the TNM stage.
The accuracy measure and confusion matrices were used to evaluate the TNM stages classified by the symbolic rule-based system. The system was evaluated against a database of multidisciplinary team staging decisions and a machine learning-based text classification system using support vector machines.
Overall accuracy on a corpus of pathology reports for 718 lung cancer patients against a database of pathological TNM staging decisions were 72%, 78%, and 94% for T, N, and M staging, respectively. The system's performance was also comparable to support vector machine classification approaches.
A system to classify lung TNM stages from free-text pathology reports was developed, and it was verified that the symbolic rule-based approach using SNOMED CT can be used for the extraction of key lung cancer characteristics from free-text reports. Future work will investigate the applicability of using the proposed methodology for extracting other cancer characteristics and types.
Chronic obstructive pulmonary disease (COPD) is a major public health problem with increasing prevalence worldwide. The primary aim of this study was to identify genes and gene ontologies associated with COPD severity. Gene expression profiling was performed on total RNA extracted from lung tissue of 18 former smokers with COPD. Class comparison analysis on mild (n = 9, FEV1 80–110% predicted) and moderate (n = 9, FEV1 50–60% predicted) COPD patients identified 46 differentially expressed genes (p<0.01), of which 14 genes were technically confirmed by quantitative real-time-PCR. Biological replication in an independent test set of 58 lung samples confirmed the altered expression of ten genes with increasing COPD severity, with eight of these genes (NNMT, THBS1, HLA-DPB1, IGHD, ETS2, ELF1, PTGDS and CYRBD1) being differentially expressed by greater than 1.8 fold between mild and moderate COPD, identifying these as candidate determinants of COPD severity. These genes belonged to ontologies potentially implicated in COPD including angiogenesis, cell migration, proliferation and apoptosis. Our secondary aim was to identify gene ontologies common to airway obstruction, indicated by impaired FEV1 and KCO. Using gene ontology enrichment analysis we have identified relevant biological and molecular processes including regulation of cell-matrix adhesion, leukocyte activation, cell and substrate adhesion, cell adhesion, angiogenesis, cell activation that are enriched among genes involved in airflow obstruction. Exploring the functional significance of these genes and their gene ontologies will provide clues to molecular changes involved in severity of COPD, which could be developed as targets for therapy or biomarkers for early diagnosis.
MicroRNAs (miRNAs) are a family of small, non-coding RNA species functioning as negative regulators of multiple target genes including tumour suppressor genes and oncogenes. Many miRNA gene loci are located within cancer-associated genomic regions. To identify potential new amplified oncogenic and/or deleted tumour suppressing miRNAs in lung cancer, we inferred miRNA gene dosage from high dimensional arrayCGH data. From miRBase v9.0 (http://microrna.sanger.ac.uk), 474 human miRNA genes were physically mapped to regions of chromosomal loss or gain identified from a high-resolution genome-wide arrayCGH study of 132 primary non-small cell lung cancers (NSCLCs) (a training set of 60 squamous cell carcinomas and 72 adenocarcinomas). MiRNAs were selected as candidates if their immediately flanking probes or host gene were deleted or amplified in at least 25% of primary tumours using both Analysis of Copy Errors algorithm and fold change (≥±1.2) analyses. Using these criteria, 97 miRNAs mapped to regions of aberrant copy number. Analysis of three independent published lung cancer arrayCGH datasets confirmed that 22 of these miRNA loci showed directionally concordant copy number variation. MiR-218, encoded on 4p15.31 and 5q35.1 within two host genes (SLIT2 and SLIT3), in a region of copy number loss, was selected as a priority candidate for follow-up as it is reported as underexpressed in lung cancer. We confirmed decreased expression of mature miR-218 and its host genes by qRT-PCR in 39 NSCLCs relative to normal lung tissue. This downregulation of miR-218 was found to be associated with a history of cigarette smoking, but not human papilloma virus. Thus, we show for the first time that putative lung cancer-associated miRNAs can be identified from genome-wide arrayCGH datasets using a bioinformatics mapping approach, and report that miR-218 is a strong candidate tumour suppressing miRNA potentially involved in lung cancer.
Chronic obstructive pulmonary disease (COPD) is a major public health problem. The aim of this study was to identify genes involved in emphysema severity in COPD patients.
Gene expression profiling was performed on total RNA extracted from non-tumor lung tissue from 30 smokers with emphysema. Class comparison analysis based on gas transfer measurement was performed to identify differentially expressed genes. Genes were then selected for technical validation by quantitative reverse transcriptase-PCR (qRT-PCR) if also represented on microarray platforms used in previously published emphysema studies. Genes technically validated advanced to tests of biological replication by qRT-PCR using an independent test set of 62 lung samples.
Class comparison identified 98 differentially expressed genes (p < 0.01). Fifty-one of those genes had been previously evaluated in differentiation between normal and severe emphysema lung. qRT-PCR confirmed the direction of change in expression in 29 of the 51 genes and 11 of those validated, remaining significant at p < 0.05. Biological replication in an independent cohort confirmed the altered expression of eight genes, with seven genes differentially expressed by greater than 1.3 fold, identifying these as candidate determinants of emphysema severity.
Gene expression profiling of lung from emphysema patients identified seven candidate genes associated with emphysema severity including COL6A3, SERPINF1, ZNHIT6, NEDD4, CDKN2A, NRN1 and GSTM3.
Cancer staging provides a basis for planning clinical management, but also allows for meaningful analysis of cancer outcomes and evaluation of cancer care services. Despite this, stage data in cancer registries is often incomplete, inaccurate, or simply not collected. This article describes a prototype software system (Cancer Stage Interpretation System, CSIS) that automatically extracts cancer staging information from medical reports. The system uses text classification techniques to train support vector machines (SVMs) to extract elements of stage listed in cancer staging guidelines. When processing new reports, CSIS identifies sentences relevant to the staging decision, and subsequently assigns the most likely stage. The system was developed using a database of staging data and pathology reports for 710 lung cancer patients, then validated in an independent set of 179 patients against pathologic stage assigned by two independent pathologists. CSIS achieved overall accuracy of 74% for tumor (T) staging and 87% for node (N) staging, and errors were observed to mirror disagreements between human experts.