Molecular Diagnosis of Idiopathic Interstitial Pneumonias: a Prospective Study
Study Details
Study Description
Brief Summary
Molecular diagnosis of idiopathic interstitial pneumonias is an innovative way to potentially improve the diagnostic accuracy of surgical lung biopsies (SLBs), introducing molecular classifiers of idiopathic pulmonary fibrosis (IPF) vs. non-specific interstitial pneumonia (NSIP), the 2 main types of idiopathic interstitial pneumonias (IIPs).
The investigators hypothesize that pre-defined gene expression profiles previously identified on large lung explants can still be identified and reproducible on smaller, clinically available surgical lung biopsies (SLBs), and can be used to increase diagnostic accuracy during multi-disciplinary discussion.
The investigators also hypothesize that the expression level of individual, preselected genes that accurately differentiate IPF from NSIP on lung explants can be reproduced on SLBs.
The investigators will isolate RNA from SLBs obtained from patients with IIP and perform microarray analysis to verify the reproducibility of gene expression profiles on SLBs. Individual genes expression levels will be determined by RT-PCR.
The diagnosis will be determined by MDD and further validated by prospective follow-up of patients for a period of 3 years.
The investigators will assess the impact of molecular diagnostic techniques on interobserver agreement during multi-disciplinary discussion.
The investigators will prospectively follow the clinical course of patients after SLB for a period of 3 years to validate the diagnosis, and asses the diagnostic accuracy of molecular techniques.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
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Detailed Description
Aim of the study This is a prospective, observational trial to collect samples of SLB, extract RNA, analyze transcriptional profiles by microarray, and validate previously identified gene expression profiles and individual genes expression levels against the diagnosis of IIP (IPF vs. NSIP), defined by multi-disciplinary discussion, and further confirmed by subsequent clinical course. There is no experimental drug involved.
Specific objectives:
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Test and validate the reproducibility of gene expression profiles of IPF and NSIP on the transcriptome obtained from surgical lung biopsies (lung homogenates), prospectively collected.
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Test the gene expression profiles of IPF and NSIP, respectively, as predictors of 3-year survival from the time of biopsy. .
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Test individual gene expression levels (markers of NSIP or IPF) in lung homogenates from SLB with real-time RT-PCR, as discriminators of IPF vs. NSIP.
Although the diagnosis of IPF or NSIP will be established by multi-disciplinary discussion, as per guidelines, in order to further validate gene signatures and singles genes as reliable discriminators of IPF vs. NSIP, we will prospectively follow the clinical course of patients for a period of 3 years, to make sure that the clinical course is consistent with either IPF (worse) or NSIP (better). The average clinical courses of IPF and NSIP are clearly established by our 6-year interstitial lung disease database experience.
Assessment of expected outcomes:
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Definition of a diagnosis of IPF vs. NSIP by MDD among Respirologist, Chest Radiologist and Lung Pathologist, as per current clinical practice. Kappa statistics will be also used to evaluate the diagnostic impact of molecular diagnostic techniques.
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Comprehensive microarray analysis of all SLB, including significance analysis of microarray, principal component analysis, hierarchical clustering and Ingenuity pathway analysis. The reproducibility of predefined gene expression profiles of IPF and NSIP will be studied on surgical lung biopsies.
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Real time RT-PCR to measure the gene expression levels of 6 selected genes that may differentiate IPF from NSIP.
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Prospective follow-up of clinical course (3 years) to further validate diagnostic accuracy.
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Study of the predictive power of gene expression profiles of IPF and NSIP (categorical variables) and of the expression level of 6 selected genes (continuous variables) towards 3-year survival from the time of biopsy.
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Assessment of diagnostic accuracy area under the curve, sensitivity, specificity) of molecular techniques, after validation of diagnosis with 3-year post-biopsy clinical course.
Subjects After ruling out known causes (rheumatoid disorders, occupational, environmental or domestic exposures, drugs) of pulmonary fibrosis, patients being referred for a SLB to clarify the diagnosis of IIP (IPF vs. NSIP) will be recruited in the study. Informed, written consent will be obtained.
Demographic characteristics and pulmonary function tests prior to the SLB will be recorded. The pre-SLB high resolution chest CT scan will be considered together with the SLB during MDD.
Storage and processing of samples At the time of SLB, an adequate sample of each SLB will be snap frozen with liquid nitrogen and stored at -80ºC, until RNA extraction is carried on.
RNA extraction and Microarray analysis RNA will be isolated, labeled, and hybridized to the human gene 1.0 set array by the London Regional Genomic Centre according to the manufacturer's protocols (Illumina EpiCentre ScriptSeq).
Data sets for microarray experiments will be made available at the Gene Expression Omnibus repository.
Partek software (St.Louis, MO) will be used for the preliminary analysis. Probe-level data will be pre-processed. This will include robust multi-array average background correction and data normalization, which will be performed across all arrays using quantile normalization. Background-adjusted, normalized values will then be compiled, or summarized, using the median polish technique, to generate a single measure of expression. As an exploratory data analysis, principal component analysis mapping and F Ratio analysis (signal-to-noise ratio) will also be performed.
For Significant Analysis of Microarray, 33,297 probe sets will be used. The q value will be adopted as a multiple comparison correction and used to identify differentially expressed genes. The q value represents the minimal false discovery ratio (FDR) at which an individual hypothesis test may be called significant.
For hierarchical clustering, Cluster 3.0 and Treeview (Eisen's laboratory, Standford Univ.) will be used. Unsupervised clustering does not take any of the experimental variables such, as treatment, phenotype, tissue, etc., into account while clustering.
Ingenuity Pathway analysis (IPA) is fundamental role to determine gene expression and protein-protein interactions within the context of metabolic or signaling pathways, and to understand how proteins operate and form pathways, in the context of the selected expression profiles. IPA is a powerful curated database and analysis system for understanding how proteins work together to effect cellular changes.
Gene expression profiles to be considered for validation on SLB were published (Respiratory Research 2018 Aug 15;19:153). The gene signature of NSIP consists of 86 genes, while the gene signature of IPF consists of 60 genes. Receiver operating characteristics analysis will be used to determine the accuracy of gene expression analysis in determining the diagnosis of IPF vs. NSIP (area under the curve, sensitivity, specificity).
RT-PCR Ribosomal protein large P0 will be used as housekeeping gene. Based on our previous results on lung explants, 6 genes will be tested as discriminators of IPF vs. NSIP on lung homogenates from SLB. All genes were cross checked against normal controls.
Statistical analysis The Kolmogorov-Smirnov test will be used to assess demographic, functional and RT-PCR variables' distribution. For comparison of groups (IPF vs. NSIP), either unpaired t-test or the Mann-Whitney test, where indicated, will be used. Cox proportional hazard analysis and receiver operating characteristics will be used to determine the strength of RT-PCR variables in predicting outcome. Kappa statistics will be used to asses diagnostic agreement during MDD. Receiver operating characteristics analysis will be used to assess diagnostic accuracy (sensitivity, specificity, area under the curve).
Definition of diagnosis and post-biopsy clinical course The specific diagnosis of IIP (IPF vs. NSIP) will be defined based on multi-disciplinary discussion (MDD) among treating clinician, chest radiologist and lung pathologist, taking into consideration clinical information chest CT scan radiographic pattern and pathology pattern seen on the SLB. The diagnosis will be reached by consensus, as per current standard of practice.
To validate the diagnosis, patients will be followed for a period of 3 years after the SLB. Rate of clinical progression and survival are significantly different in IPF vs. NSIP.
Clinical progression from the time of diagnosis (SLB) will be defined as either: >10% absolute reduction in forced vital capacity (FVC) % pred; >50 m decline in 6-minute walk distance (6MWD); admission to hospital for respiratory causes; lung transplantation (LTx) assessment; or death.
Clinic visits take place at 4-6 months intervals, as dictated by the clinician. At each visit, MRC dyspnea score, pulmonary function tests and 6-minute walk tests data will be collected.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Idiopathic interstitial pneumonias Patients with idiopathic interstitial pneumonias undergoing surgical lung biopsy |
Diagnostic Test: Microarray analysis
Microarray analysis to identify gene expression profiles that distinguish IPF from NSIP
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Outcome Measures
Primary Outcome Measures
- Reproducibility of gene expression profiles on surgical lung biopsies [February 2019-January 2022]
Proportion of patients (% of the total) with reproducible predefined gene expression profiles of either IPF or NSIP on surgical lung biopsy.
Secondary Outcome Measures
- Prognostic impact of gene expression profiles of IPF and NSIP [February 2019-January 2025]
Hazard ratios of IPF and NSIP gene expression profiles (categorical variables) towards 3-year survival from the time of biopsy
- Prognostic impact of selected genes expression levels [February 2019-January 2025]
Hazard ratios of gene expression levels of 6 selected genes (continuous variables) towards 3-year survival from the time of biopsy.
Eligibility Criteria
Criteria
Inclusion criteria:
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Chronic interstitial lung disease not caused by connective tissue disease, drug-induced toxicity or environmental occupational or domestic exposures. These criteria equal to a diagnosis of idiopathic interstitial pneumonia (IIP).
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High resolution chest CT scan not consistent with an idiopathic pulmonary fibrosis pattern, therefore requiring a surgical lung biopsy to clarify the exact diagnosis of IIP.
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No contraindications to undergo a surgical lung biopsy (advanced disease stage; significant cardiac disease; significant obesity; or associated pulmonary hypertension).
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Patient able to provide informed consent.
Exclusion criteria:
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Chronic interstitial lung disease caused by connective tissue disease, drug-induced toxicity or environmental occupational or domestic exposures.
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High resolution chest CT scan consistent with an idiopathic pulmonary fibrosis pattern, therefore not requiring a surgical lung biopsy.
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Contraindications to undergo a surgical lung biopsy (advanced disease stage; significant cardiac disease; significant obesity; or associated pulmonary hypertension).
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | London Health Science Centre | London | Ontario | Canada | N6A 5W9 |
Sponsors and Collaborators
- Lawson Health Research Institute
Investigators
- Principal Investigator: Marco Mura, MD, PhD, Western University
Study Documents (Full-Text)
None provided.More Information
Publications
- Cecchini MJ, Hosein K, Howlett CJ, Joseph M, Mura M. Comprehensive gene expression profiling identifies distinct and overlapping transcriptional profiles in non-specific interstitial pneumonia and idiopathic pulmonary fibrosis. Respir Res. 2018 Aug 15;19(1):153. doi: 10.1186/s12931-018-0857-1.
- Mura M, Anraku M, Yun Z, McRae K, Liu M, Waddell TK, Singer LG, Granton JT, Keshavjee S, de Perrot M. Gene expression profiling in the lungs of patients with pulmonary hypertension associated with pulmonary fibrosis. Chest. 2012 Mar;141(3):661-673. doi: 10.1378/chest.11-0449. Epub 2011 Aug 11.
- Mura M, Porretta MA, Bargagli E, Sergiacomi G, Zompatori M, Sverzellati N, Taglieri A, Mezzasalma F, Rottoli P, Saltini C, Rogliani P. Predicting survival in newly diagnosed idiopathic pulmonary fibrosis: a 3-year prospective study. Eur Respir J. 2012 Jul;40(1):101-9. doi: 10.1183/09031936.00106011. Epub 2012 Jan 12.
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