<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03836417</url>
  </required_header>
  <id_info>
    <org_study_id>6156</org_study_id>
    <nct_id>NCT03836417</nct_id>
  </id_info>
  <brief_title>Molecular Diagnosis of Idiopathic Interstitial Pneumonias: a Prospective Study</brief_title>
  <official_title>Molecular Diagnosis of Idiopathic Interstitial Pneumonias: a Prospective Study</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Lawson Health Research Institute</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Lawson Health Research Institute</source>
  <oversight_info>
    <has_dmc>Yes</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      Molecular diagnosis of idiopathic interstitial pneumonias is an innovative way to potentially&#xD;
      improve the diagnostic accuracy of surgical lung biopsies (SLBs), introducing molecular&#xD;
      classifiers of idiopathic pulmonary fibrosis (IPF) vs. non-specific interstitial pneumonia&#xD;
      (NSIP), the 2 main types of idiopathic interstitial pneumonias (IIPs).&#xD;
&#xD;
      The investigators hypothesize that pre-defined gene expression profiles previously identified&#xD;
      on large lung explants can still be identified and reproducible on smaller, clinically&#xD;
      available surgical lung biopsies (SLBs), and can be used to increase diagnostic accuracy&#xD;
      during multi-disciplinary discussion.&#xD;
&#xD;
      The investigators also hypothesize that the expression level of individual, preselected genes&#xD;
      that accurately differentiate IPF from NSIP on lung explants can be reproduced on SLBs.&#xD;
&#xD;
      The investigators will isolate RNA from SLBs obtained from patients with IIP and perform&#xD;
      microarray analysis to verify the reproducibility of gene expression profiles on SLBs.&#xD;
      Individual genes expression levels will be determined by RT-PCR.&#xD;
&#xD;
      The diagnosis will be determined by MDD and further validated by prospective follow-up of&#xD;
      patients for a period of 3 years.&#xD;
&#xD;
      The investigators will assess the impact of molecular diagnostic techniques on interobserver&#xD;
      agreement during multi-disciplinary discussion.&#xD;
&#xD;
      The investigators will prospectively follow the clinical course of patients after SLB for a&#xD;
      period of 3 years to validate the diagnosis, and asses the diagnostic accuracy of molecular&#xD;
      techniques.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Aim of the study This is a prospective, observational trial to collect samples of SLB,&#xD;
      extract RNA, analyze transcriptional profiles by microarray, and validate previously&#xD;
      identified gene expression profiles and individual genes expression levels against the&#xD;
      diagnosis of IIP (IPF vs. NSIP), defined by multi-disciplinary discussion, and further&#xD;
      confirmed by subsequent clinical course. There is no experimental drug involved.&#xD;
&#xD;
      Specific objectives:&#xD;
&#xD;
        1. Test and validate the reproducibility of gene expression profiles of IPF and NSIP on the&#xD;
           transcriptome obtained from surgical lung biopsies (lung homogenates), prospectively&#xD;
           collected.&#xD;
&#xD;
        2. Test the gene expression profiles of IPF and NSIP, respectively, as predictors of 3-year&#xD;
           survival from the time of biopsy. .&#xD;
&#xD;
        3. Test individual gene expression levels (markers of NSIP or IPF) in lung homogenates from&#xD;
           SLB with real-time RT-PCR, as discriminators of IPF vs. NSIP.&#xD;
&#xD;
      Although the diagnosis of IPF or NSIP will be established by multi-disciplinary discussion,&#xD;
      as per guidelines, in order to further validate gene signatures and singles genes as reliable&#xD;
      discriminators of IPF vs. NSIP, we will prospectively follow the clinical course of patients&#xD;
      for a period of 3 years, to make sure that the clinical course is consistent with either IPF&#xD;
      (worse) or NSIP (better). The average clinical courses of IPF and NSIP are clearly&#xD;
      established by our 6-year interstitial lung disease database experience.&#xD;
&#xD;
      Assessment of expected outcomes:&#xD;
&#xD;
        1. Definition of a diagnosis of IPF vs. NSIP by MDD among Respirologist, Chest Radiologist&#xD;
           and Lung Pathologist, as per current clinical practice. Kappa statistics will be also&#xD;
           used to evaluate the diagnostic impact of molecular diagnostic techniques.&#xD;
&#xD;
        2. Comprehensive microarray analysis of all SLB, including significance analysis of&#xD;
           microarray, principal component analysis, hierarchical clustering and Ingenuity pathway&#xD;
           analysis. The reproducibility of predefined gene expression profiles of IPF and NSIP&#xD;
           will be studied on surgical lung biopsies.&#xD;
&#xD;
        3. Real time RT-PCR to measure the gene expression levels of 6 selected genes that may&#xD;
           differentiate IPF from NSIP.&#xD;
&#xD;
        4. Prospective follow-up of clinical course (3 years) to further validate diagnostic&#xD;
           accuracy.&#xD;
&#xD;
        5. Study of the predictive power of gene expression profiles of IPF and NSIP (categorical&#xD;
           variables) and of the expression level of 6 selected genes (continuous variables)&#xD;
           towards 3-year survival from the time of biopsy.&#xD;
&#xD;
        6. Assessment of diagnostic accuracy area under the curve, sensitivity, specificity) of&#xD;
           molecular techniques, after validation of diagnosis with 3-year post-biopsy clinical&#xD;
           course.&#xD;
&#xD;
      Subjects After ruling out known causes (rheumatoid disorders, occupational, environmental or&#xD;
      domestic exposures, drugs) of pulmonary fibrosis, patients being referred for a SLB to&#xD;
      clarify the diagnosis of IIP (IPF vs. NSIP) will be recruited in the study. Informed, written&#xD;
      consent will be obtained.&#xD;
&#xD;
      Demographic characteristics and pulmonary function tests prior to the SLB will be recorded.&#xD;
      The pre-SLB high resolution chest CT scan will be considered together with the SLB during&#xD;
      MDD.&#xD;
&#xD;
      Storage and processing of samples At the time of SLB, an adequate sample of each SLB will be&#xD;
      snap frozen with liquid nitrogen and stored at -80ºC, until RNA extraction is carried on.&#xD;
&#xD;
      RNA extraction and Microarray analysis RNA will be isolated, labeled, and hybridized to the&#xD;
      human gene 1.0 set array by the London Regional Genomic Centre according to the&#xD;
      manufacturer's protocols (Illumina EpiCentre ScriptSeq).&#xD;
&#xD;
      Data sets for microarray experiments will be made available at the Gene Expression Omnibus&#xD;
      repository.&#xD;
&#xD;
      Partek software (St.Louis, MO) will be used for the preliminary analysis. Probe-level data&#xD;
      will be pre-processed. This will include robust multi-array average background correction and&#xD;
      data normalization, which will be performed across all arrays using quantile normalization.&#xD;
      Background-adjusted, normalized values will then be compiled, or summarized, using the median&#xD;
      polish technique, to generate a single measure of expression. As an exploratory data&#xD;
      analysis, principal component analysis mapping and F Ratio analysis (signal-to-noise ratio)&#xD;
      will also be performed.&#xD;
&#xD;
      For Significant Analysis of Microarray, 33,297 probe sets will be used. The q value will be&#xD;
      adopted as a multiple comparison correction and used to identify differentially expressed&#xD;
      genes. The q value represents the minimal false discovery ratio (FDR) at which an individual&#xD;
      hypothesis test may be called significant.&#xD;
&#xD;
      For hierarchical clustering, Cluster 3.0 and Treeview (Eisen's laboratory, Standford Univ.)&#xD;
      will be used. Unsupervised clustering does not take any of the experimental variables such,&#xD;
      as treatment, phenotype, tissue, etc., into account while clustering.&#xD;
&#xD;
      Ingenuity Pathway analysis (IPA) is fundamental role to determine gene expression and&#xD;
      protein-protein interactions within the context of metabolic or signaling pathways, and to&#xD;
      understand how proteins operate and form pathways, in the context of the selected expression&#xD;
      profiles. IPA is a powerful curated database and analysis system for understanding how&#xD;
      proteins work together to effect cellular changes.&#xD;
&#xD;
      Gene expression profiles to be considered for validation on SLB were published (Respiratory&#xD;
      Research 2018 Aug 15;19:153). The gene signature of NSIP consists of 86 genes, while the gene&#xD;
      signature of IPF consists of 60 genes. Receiver operating characteristics analysis will be&#xD;
      used to determine the accuracy of gene expression analysis in determining the diagnosis of&#xD;
      IPF vs. NSIP (area under the curve, sensitivity, specificity).&#xD;
&#xD;
      RT-PCR Ribosomal protein large P0 will be used as housekeeping gene. Based on our previous&#xD;
      results on lung explants, 6 genes will be tested as discriminators of IPF vs. NSIP on lung&#xD;
      homogenates from SLB. All genes were cross checked against normal controls.&#xD;
&#xD;
      Statistical analysis The Kolmogorov-Smirnov test will be used to assess demographic,&#xD;
      functional and RT-PCR variables' distribution. For comparison of groups (IPF vs. NSIP),&#xD;
      either unpaired t-test or the Mann-Whitney test, where indicated, will be used. Cox&#xD;
      proportional hazard analysis and receiver operating characteristics will be used to determine&#xD;
      the strength of RT-PCR variables in predicting outcome. Kappa statistics will be used to&#xD;
      asses diagnostic agreement during MDD. Receiver operating characteristics analysis will be&#xD;
      used to assess diagnostic accuracy (sensitivity, specificity, area under the curve).&#xD;
&#xD;
      Definition of diagnosis and post-biopsy clinical course The specific diagnosis of IIP (IPF&#xD;
      vs. NSIP) will be defined based on multi-disciplinary discussion (MDD) among treating&#xD;
      clinician, chest radiologist and lung pathologist, taking into consideration clinical&#xD;
      information chest CT scan radiographic pattern and pathology pattern seen on the SLB. The&#xD;
      diagnosis will be reached by consensus, as per current standard of practice.&#xD;
&#xD;
      To validate the diagnosis, patients will be followed for a period of 3 years after the SLB.&#xD;
      Rate of clinical progression and survival are significantly different in IPF vs. NSIP.&#xD;
&#xD;
      Clinical progression from the time of diagnosis (SLB) will be defined as either: &gt;10%&#xD;
      absolute reduction in forced vital capacity (FVC) % pred; &gt;50 m decline in 6-minute walk&#xD;
      distance (6MWD); admission to hospital for respiratory causes; lung transplantation (LTx)&#xD;
      assessment; or death.&#xD;
&#xD;
      Clinic visits take place at 4-6 months intervals, as dictated by the clinician. At each&#xD;
      visit, MRC dyspnea score, pulmonary function tests and 6-minute walk tests data will be&#xD;
      collected.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Recruiting</overall_status>
  <start_date type="Actual">June 28, 2019</start_date>
  <completion_date type="Anticipated">June 30, 2025</completion_date>
  <primary_completion_date type="Anticipated">June 30, 2024</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Cohort</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Reproducibility of gene expression profiles on surgical lung biopsies</measure>
    <time_frame>February 2019-January 2022</time_frame>
    <description>Proportion of patients (% of the total) with reproducible predefined gene expression profiles of either IPF or NSIP on surgical lung biopsy.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Prognostic impact of gene expression profiles of IPF and NSIP</measure>
    <time_frame>February 2019-January 2025</time_frame>
    <description>Hazard ratios of IPF and NSIP gene expression profiles (categorical variables) towards 3-year survival from the time of biopsy</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Prognostic impact of selected genes expression levels</measure>
    <time_frame>February 2019-January 2025</time_frame>
    <description>Hazard ratios of gene expression levels of 6 selected genes (continuous variables) towards 3-year survival from the time of biopsy.</description>
  </secondary_outcome>
  <number_of_groups>1</number_of_groups>
  <enrollment type="Anticipated">100</enrollment>
  <condition>Idiopathic Interstitial Pneumonia</condition>
  <condition>Idiopathic Pulmonary Fibrosis</condition>
  <condition>Nonspecific Interstitial Pneumonia</condition>
  <arm_group>
    <arm_group_label>Idiopathic interstitial pneumonias</arm_group_label>
    <description>Patients with idiopathic interstitial pneumonias undergoing surgical lung biopsy</description>
  </arm_group>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>Microarray analysis</intervention_name>
    <description>Microarray analysis to identify gene expression profiles that distinguish IPF from NSIP</description>
    <arm_group_label>Idiopathic interstitial pneumonias</arm_group_label>
  </intervention>
  <biospec_retention>Samples With DNA</biospec_retention>
  <biospec_descr>
    <textblock>
      Lung tissue biopsies&#xD;
    </textblock>
  </biospec_descr>
  <eligibility>
    <study_pop>
      <textblock>
        After ruling out known causes (connective tissue disease; occupational, environmental or&#xD;
        domestic exposures; drug-induced lung toxicity) of interstitial lung disease, patients&#xD;
        being referred for a surgical lung biopsy to clarify the diagnosis of IIP (IPF vs. NSIP)&#xD;
        will be recruited in the study.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion criteria:&#xD;
&#xD;
          1. Chronic interstitial lung disease not caused by connective tissue disease,&#xD;
             drug-induced toxicity or environmental occupational or domestic exposures. These&#xD;
             criteria equal to a diagnosis of idiopathic interstitial pneumonia (IIP).&#xD;
&#xD;
          2. High resolution chest CT scan not consistent with an idiopathic pulmonary fibrosis&#xD;
             pattern, therefore requiring a surgical lung biopsy to clarify the exact diagnosis of&#xD;
             IIP.&#xD;
&#xD;
          3. No contraindications to undergo a surgical lung biopsy (advanced disease stage;&#xD;
             significant cardiac disease; significant obesity; or associated pulmonary&#xD;
             hypertension).&#xD;
&#xD;
          4. Patient able to provide informed consent.&#xD;
&#xD;
        Exclusion criteria:&#xD;
&#xD;
          1. Chronic interstitial lung disease caused by connective tissue disease, drug-induced&#xD;
             toxicity or environmental occupational or domestic exposures.&#xD;
&#xD;
          2. High resolution chest CT scan consistent with an idiopathic pulmonary fibrosis&#xD;
             pattern, therefore not requiring a surgical lung biopsy.&#xD;
&#xD;
          3. Contraindications to undergo a surgical lung biopsy (advanced disease stage;&#xD;
             significant cardiac disease; significant obesity; or associated pulmonary&#xD;
             hypertension).&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Marco Mura, MD, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Western University</affiliation>
  </overall_official>
  <overall_contact>
    <last_name>Marco Mura, MD, PhD</last_name>
    <phone>5196676744</phone>
    <email>marco.mura@lhsc.on.ca</email>
  </overall_contact>
  <overall_contact_backup>
    <last_name>Karishma Hosein, MSc</last_name>
    <phone>5196676744</phone>
    <email>karishma.hosein@lhsc.on.ca</email>
  </overall_contact_backup>
  <location>
    <facility>
      <name>London Health Science Centre</name>
      <address>
        <city>London</city>
        <state>Ontario</state>
        <zip>N6A 5W9</zip>
        <country>Canada</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Marco Mura, MD, PhD</last_name>
      <phone>5196676744</phone>
      <email>marco.mura@lhsc.on.ca</email>
    </contact>
    <contact_backup>
      <last_name>Karishma Hosein, MSc</last_name>
      <phone>5196676744</phone>
      <email>karishma.hosein@lhsc.on.ca</email>
    </contact_backup>
  </location>
  <location_countries>
    <country>Canada</country>
  </location_countries>
  <reference>
    <citation>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.</citation>
    <PMID>30111332</PMID>
  </reference>
  <reference>
    <citation>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.</citation>
    <PMID>21835902</PMID>
  </reference>
  <reference>
    <citation>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.</citation>
    <PMID>22241745</PMID>
  </reference>
  <verification_date>May 2023</verification_date>
  <study_first_submitted>January 7, 2019</study_first_submitted>
  <study_first_submitted_qc>February 7, 2019</study_first_submitted_qc>
  <study_first_posted type="Actual">February 11, 2019</study_first_posted>
  <last_update_submitted>May 23, 2023</last_update_submitted>
  <last_update_submitted_qc>May 23, 2023</last_update_submitted_qc>
  <last_update_posted type="Actual">May 24, 2023</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Pneumonia</mesh_term>
    <mesh_term>Pulmonary Fibrosis</mesh_term>
    <mesh_term>Idiopathic Pulmonary Fibrosis</mesh_term>
    <mesh_term>Lung Diseases, Interstitial</mesh_term>
    <mesh_term>Idiopathic Interstitial Pneumonias</mesh_term>
    <mesh_term>Hamman-Rich Syndrome</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03836417
org study id: 6156
nct id: NCT03836417
lead sponsor: 
has dmc: Yes
is fda regulated drug: No
is fda regulated device: No
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.
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:

        1. 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.

        2. Test the gene expression profiles of IPF and NSIP, respectively, as predictors of 3-year
           survival from the time of biopsy. .

        3. 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:

        1. 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.

        2. 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.

        3. Real time RT-PCR to measure the gene expression levels of 6 selected genes that may
           differentiate IPF from NSIP.

        4. Prospective follow-up of clinical course (3 years) to further validate diagnostic
           accuracy.

        5. 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.

        6. 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.
observational model: Cohort
time perspective: Prospective
measure: Reproducibility of gene expression profiles on surgical lung biopsies
time frame: February 2019-January 2022
description: Proportion of patients (% of the total) with reproducible predefined gene expression profiles of either IPF or NSIP on surgical lung biopsy.
measure: Prognostic impact of gene expression profiles of IPF and NSIP
time frame: February 2019-January 2025
description: Hazard ratios of IPF and NSIP gene expression profiles (categorical variables) towards 3-year survival from the time of biopsy
measure: Prognostic impact of selected genes expression levels
time frame: February 2019-January 2025
description: Hazard ratios of gene expression levels of 6 selected genes (continuous variables) towards 3-year survival from the time of biopsy.
arm group label: Idiopathic interstitial pneumonias
description: Patients with idiopathic interstitial pneumonias undergoing surgical lung biopsy
intervention type: Diagnostic Test
intervention name: Microarray analysis
description: Microarray analysis to identify gene expression profiles that distinguish IPF from NSIP
arm group label: Idiopathic interstitial pneumonias
Lung tissue biopsies
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: No
last name: Marco Mura, MD, PhD
role: Principal Investigator
affiliation: Western University
last name: Marco Mura, MD, PhD
phone: 5196676744
email: marco.mura@lhsc.on.ca
last name: Karishma Hosein, MSc
phone: 5196676744
email: karishma.hosein@lhsc.on.ca
facility: 
status: Recruiting
contact: 
contact backup: 
country: Canada
citation: 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.
PMID: 30111332
citation: 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.
PMID: 21835902
citation: 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.
PMID: 22241745
responsible party type: Sponsor
mesh term: Pneumonia
mesh term: Pulmonary Fibrosis
mesh term: Idiopathic Pulmonary Fibrosis
mesh term: Lung Diseases, Interstitial
mesh term: Idiopathic Interstitial Pneumonias
mesh term: Hamman-Rich Syndrome
sharing ipd: No