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1.  MicroRNA-34c is associated with emphysema severity and modulates SERPINE1 expression 
BMC Genomics  2014;15:88.
Background
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.
Results
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).
Conclusion
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.
doi:10.1186/1471-2164-15-88
PMCID: PMC3922660  PMID: 24479666
Chronic obstructive pulmonary disease; microRNA; miR-34c; Microarray
2.  The pivotal role of pathology in the management of lung cancer 
Journal of Thoracic Disease  2013;5(Suppl 5):S463-S478.
The last decade has seen significant advances in our understanding of lung cancer biology and management. Identification of key driver events in lung carcinogenesis has contributed to the development of targeted lung cancer therapies, heralding the era of personalised medicine for lung cancer. As a result, histological subtyping and molecular testing has become of paramount importance, placing increasing demands on often small diagnostic specimens. This has triggered the review and development of the first structured classification of lung cancer in small biopsy/cytology specimens and a new classification of lung adenocarcinoma from the IASLC/ATS/ERS. These have enhanced the clinical relevance of pathological diagnosis, and emphasise the role of the modern surgical pathologist as an integral member of the multidisciplinary team, playing a crucial role in clinical trials and determining appropriate and timely management for patients with lung cancer.
doi:10.3978/j.issn.2072-1439.2013.08.43
PMCID: PMC3804871  PMID: 24163740
Lung Neoplasms; pathology; non-small-cell lung carcinoma (NSCLC); small cell lung carcinoma (SCLC)
3.  Phenotypes and Karyotypes of Human Malignant Mesothelioma Cell Lines 
PLoS ONE  2013;8(3):e58132.
Background
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.
Methods
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.
Results
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.
Conclusion
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.
doi:10.1371/journal.pone.0058132
PMCID: PMC3597627  PMID: 23516439
4.  Pleural fluid cell-free DNA integrity index to identify cytologically negative malignant pleural effusions including mesotheliomas 
BMC Cancer  2012;12:428.
Background
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.
Methods
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.
Results
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).
Conclusion
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.
doi:10.1186/1471-2407-12-428
PMCID: PMC3495778  PMID: 23009708
Malignant pleural effusions; Mesothelioma; Lung cancer; DNA integrity index; Mesothelin
5.  Whole genome sequencing for lung cancer 
Journal of Thoracic Disease  2012;4(2):155-163.
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.
doi:10.3978/j.issn.2072-1439.2012.02.01
PMCID: PMC3378223  PMID: 22833821
High-throughput nucleotide sequencing; DNA sequence analysis; lung neoplasms; non-small cell lung carcinoma; small cell lung carcinoma
6.  Array-Comparative Genomic Hybridization Reveals Loss of SOCS6 Is Associated with Poor Prognosis in Primary Lung Squamous Cell Carcinoma 
PLoS ONE  2012;7(2):e30398.
Background
Primary tumor recurrence commonly occurs after surgical resection of lung squamous cell carcinoma (SCC). Little is known about the genes driving SCC recurrence.
Methods
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.
Results
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).
Conclusion
Reduced copy number and mRNA expression of SOCS6 are associated with disease recurrence in primary lung SCC and may be useful prognostic biomarkers.
doi:10.1371/journal.pone.0030398
PMCID: PMC3281847  PMID: 22363434
7.  Symbolic rule-based classification of lung cancer stages from free-text pathology reports 
Objective
To classify automatically lung tumor–node–metastases (TNM) cancer stages from free-text pathology reports using symbolic rule-based classification.
Design
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.
Measurements
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.
Results
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.
Conclusion
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.
doi:10.1136/jamia.2010.003707
PMCID: PMC2995652  PMID: 20595312
8.  MicroRNA-218 Is Deleted and Downregulated in Lung Squamous Cell Carcinoma 
PLoS ONE  2010;5(9):e12560.
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.
doi:10.1371/journal.pone.0012560
PMCID: PMC2933228  PMID: 20838434
9.  Collection of Cancer Stage Data by Classifying Free-text Medical Reports 
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.
doi:10.1197/jamia.M2130
PMCID: PMC2213490  PMID: 17712093
10.  MS4A1 Dysregulation in Asbestos-Related Lung Squamous Cell Carcinoma Is Due to CD20 Stromal Lymphocyte Expression 
PLoS ONE  2012;7(4):e34943.
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.
doi:10.1371/journal.pone.0034943
PMCID: PMC3325913  PMID: 22514692
11.  Genes and Gene Ontologies Common to Airflow Obstruction and Emphysema in the Lungs of Patients with COPD 
PLoS ONE  2011;6(3):e17442.
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.
doi:10.1371/journal.pone.0017442
PMCID: PMC3057973  PMID: 21423603

Results 1-11 (11)