Cargando…
Transcriptional Profiling of Endobronchial Ultrasound-Guided Lymph Node Samples Aids Diagnosis of Mediastinal Lymphadenopathy
BACKGROUND: Endobronchial ultrasound (EBUS)-guided biopsy is the mainstay for investigation of mediastinal lymphadenopathy for laboratory diagnosis of malignancy, sarcoidosis, or TB. However, improved methods for discriminating between TB and sarcoidosis and excluding malignancy are still needed. We...
Autores principales: | , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American College of Chest Physicians
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4740456/ https://www.ncbi.nlm.nih.gov/pubmed/26270185 http://dx.doi.org/10.1378/chest.15-0647 |
_version_ | 1782413849812533248 |
---|---|
author | Tomlinson, Gillian S. Thomas, Niclas Chain, Benjamin M. Best, Katharine Simpson, Nandi Hardavella, Georgia Brown, James Bhowmik, Angshu Navani, Neal Janes, Samuel M. Miller, Robert F. Noursadeghi, Mahdad |
author_facet | Tomlinson, Gillian S. Thomas, Niclas Chain, Benjamin M. Best, Katharine Simpson, Nandi Hardavella, Georgia Brown, James Bhowmik, Angshu Navani, Neal Janes, Samuel M. Miller, Robert F. Noursadeghi, Mahdad |
author_sort | Tomlinson, Gillian S. |
collection | PubMed |
description | BACKGROUND: Endobronchial ultrasound (EBUS)-guided biopsy is the mainstay for investigation of mediastinal lymphadenopathy for laboratory diagnosis of malignancy, sarcoidosis, or TB. However, improved methods for discriminating between TB and sarcoidosis and excluding malignancy are still needed. We sought to evaluate the role of genomewide transcriptional profiling to aid diagnostic processes in this setting. METHODS: Mediastinal lymph node samples from 88 individuals were obtained by EBUS-guided aspiration for investigation of mediastinal lymphadenopathy and subjected to transcriptional profiling in addition to conventional laboratory assessments. Computational strategies were used to evaluate the potential for using the transcriptome to distinguish between diagnostic categories. RESULTS: Molecular signatures associated with granulomas or neoplastic and metastatic processes were clearly discernible in granulomatous and malignant lymph node samples, respectively. Support vector machine (SVM) learning using differentially expressed genes showed excellent sensitivity and specificity profiles in receiver operating characteristic curve analysis with area under curve values > 0.9 for discriminating between granulomatous and nongranulomatous disease, TB and sarcoidosis, and between cancer and reactive lymphadenopathy. A two-step decision tree using SVM to distinguish granulomatous and nongranulomatous disease, then between TB and sarcoidosis in granulomatous cases, and between cancer and reactive lymphadenopathy in nongranulomatous cases, achieved > 90% specificity for each diagnosis and afforded greater sensitivity than existing tests to detect TB and cancer. In some diagnostically ambiguous cases, computational classification predicted granulomatous disease or cancer before pathologic abnormalities were evident. CONCLUSIONS: Machine learning analysis of transcriptional profiling in mediastinal lymphadenopathy may significantly improve the clinical utility of EBUS-guided biopsies. |
format | Online Article Text |
id | pubmed-4740456 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | American College of Chest Physicians |
record_format | MEDLINE/PubMed |
spelling | pubmed-47404562016-02-29 Transcriptional Profiling of Endobronchial Ultrasound-Guided Lymph Node Samples Aids Diagnosis of Mediastinal Lymphadenopathy Tomlinson, Gillian S. Thomas, Niclas Chain, Benjamin M. Best, Katharine Simpson, Nandi Hardavella, Georgia Brown, James Bhowmik, Angshu Navani, Neal Janes, Samuel M. Miller, Robert F. Noursadeghi, Mahdad Chest Original Research: Pulmonary Procedures BACKGROUND: Endobronchial ultrasound (EBUS)-guided biopsy is the mainstay for investigation of mediastinal lymphadenopathy for laboratory diagnosis of malignancy, sarcoidosis, or TB. However, improved methods for discriminating between TB and sarcoidosis and excluding malignancy are still needed. We sought to evaluate the role of genomewide transcriptional profiling to aid diagnostic processes in this setting. METHODS: Mediastinal lymph node samples from 88 individuals were obtained by EBUS-guided aspiration for investigation of mediastinal lymphadenopathy and subjected to transcriptional profiling in addition to conventional laboratory assessments. Computational strategies were used to evaluate the potential for using the transcriptome to distinguish between diagnostic categories. RESULTS: Molecular signatures associated with granulomas or neoplastic and metastatic processes were clearly discernible in granulomatous and malignant lymph node samples, respectively. Support vector machine (SVM) learning using differentially expressed genes showed excellent sensitivity and specificity profiles in receiver operating characteristic curve analysis with area under curve values > 0.9 for discriminating between granulomatous and nongranulomatous disease, TB and sarcoidosis, and between cancer and reactive lymphadenopathy. A two-step decision tree using SVM to distinguish granulomatous and nongranulomatous disease, then between TB and sarcoidosis in granulomatous cases, and between cancer and reactive lymphadenopathy in nongranulomatous cases, achieved > 90% specificity for each diagnosis and afforded greater sensitivity than existing tests to detect TB and cancer. In some diagnostically ambiguous cases, computational classification predicted granulomatous disease or cancer before pathologic abnormalities were evident. CONCLUSIONS: Machine learning analysis of transcriptional profiling in mediastinal lymphadenopathy may significantly improve the clinical utility of EBUS-guided biopsies. American College of Chest Physicians 2016-02 2016-01-12 /pmc/articles/PMC4740456/ /pubmed/26270185 http://dx.doi.org/10.1378/chest.15-0647 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Original Research: Pulmonary Procedures Tomlinson, Gillian S. Thomas, Niclas Chain, Benjamin M. Best, Katharine Simpson, Nandi Hardavella, Georgia Brown, James Bhowmik, Angshu Navani, Neal Janes, Samuel M. Miller, Robert F. Noursadeghi, Mahdad Transcriptional Profiling of Endobronchial Ultrasound-Guided Lymph Node Samples Aids Diagnosis of Mediastinal Lymphadenopathy |
title | Transcriptional Profiling of Endobronchial Ultrasound-Guided Lymph Node Samples Aids Diagnosis of Mediastinal Lymphadenopathy |
title_full | Transcriptional Profiling of Endobronchial Ultrasound-Guided Lymph Node Samples Aids Diagnosis of Mediastinal Lymphadenopathy |
title_fullStr | Transcriptional Profiling of Endobronchial Ultrasound-Guided Lymph Node Samples Aids Diagnosis of Mediastinal Lymphadenopathy |
title_full_unstemmed | Transcriptional Profiling of Endobronchial Ultrasound-Guided Lymph Node Samples Aids Diagnosis of Mediastinal Lymphadenopathy |
title_short | Transcriptional Profiling of Endobronchial Ultrasound-Guided Lymph Node Samples Aids Diagnosis of Mediastinal Lymphadenopathy |
title_sort | transcriptional profiling of endobronchial ultrasound-guided lymph node samples aids diagnosis of mediastinal lymphadenopathy |
topic | Original Research: Pulmonary Procedures |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4740456/ https://www.ncbi.nlm.nih.gov/pubmed/26270185 http://dx.doi.org/10.1378/chest.15-0647 |
work_keys_str_mv | AT tomlinsongillians transcriptionalprofilingofendobronchialultrasoundguidedlymphnodesamplesaidsdiagnosisofmediastinallymphadenopathy AT thomasniclas transcriptionalprofilingofendobronchialultrasoundguidedlymphnodesamplesaidsdiagnosisofmediastinallymphadenopathy AT chainbenjaminm transcriptionalprofilingofendobronchialultrasoundguidedlymphnodesamplesaidsdiagnosisofmediastinallymphadenopathy AT bestkatharine transcriptionalprofilingofendobronchialultrasoundguidedlymphnodesamplesaidsdiagnosisofmediastinallymphadenopathy AT simpsonnandi transcriptionalprofilingofendobronchialultrasoundguidedlymphnodesamplesaidsdiagnosisofmediastinallymphadenopathy AT hardavellageorgia transcriptionalprofilingofendobronchialultrasoundguidedlymphnodesamplesaidsdiagnosisofmediastinallymphadenopathy AT brownjames transcriptionalprofilingofendobronchialultrasoundguidedlymphnodesamplesaidsdiagnosisofmediastinallymphadenopathy AT bhowmikangshu transcriptionalprofilingofendobronchialultrasoundguidedlymphnodesamplesaidsdiagnosisofmediastinallymphadenopathy AT navanineal transcriptionalprofilingofendobronchialultrasoundguidedlymphnodesamplesaidsdiagnosisofmediastinallymphadenopathy AT janessamuelm transcriptionalprofilingofendobronchialultrasoundguidedlymphnodesamplesaidsdiagnosisofmediastinallymphadenopathy AT millerrobertf transcriptionalprofilingofendobronchialultrasoundguidedlymphnodesamplesaidsdiagnosisofmediastinallymphadenopathy AT noursadeghimahdad transcriptionalprofilingofendobronchialultrasoundguidedlymphnodesamplesaidsdiagnosisofmediastinallymphadenopathy |