Evidence map›Paper›PMID 29463557›Full record

ReviewClinical cancer research : an official journal of the American Association for Cancer Research2018

The Airway Transcriptome as a Biomarker for Early Lung Cancer Detection.

Ehab Billatos, Jessica L Vick, Marc E Lenburg, Avrum E Spira

Open access · greenAbstract readReview
In one paragraph

Review in Clinical cancer research : an official journal of the American Association for Cancer Research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
3.8field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 49 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Ehab BillatosSection of Computational Biomedicine, Department of Medicine and BU-BMC Cancer Center, Boston University, Boston, Massachusetts.
Jessica L VickSection of Computational Biomedicine, Department of Medicine and BU-BMC Cancer Center, Boston University, Boston, Massachusetts.
Marc E LenburgSection of Computational Biomedicine, Department of Medicine and BU-BMC Cancer Center, Boston University, Boston, Massachusetts.
Avrum E SpiraSection of Computational Biomedicine, Department of Medicine and BU-BMC Cancer Center, Boston University, Boston, Massachusetts. aspira@bu.edu.
Boston Medical Center · US

Funding

BIOLOGY OF THE LUNG--MULTIDISCIPLINARY PROGRAMT32HL007035 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI Darrell N. Kotton, JOSEPH P MIZGERD · 1985 to 2026
$24.3M
Molecular and Imaging Biomarkers for Early Lung Cancer Detection in the Setting of Indeterminate Pulmonary NodulesR01CA210360 · NCI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI ABERLE, DENISE R., LENBURG, MARC ELLIOTT · 2016 to 2021
$3.1M
The Boston University-UCLA Lung Cancer Biomarker Development LabU01CA214182 · NCI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI ABERLE, DENISE R., DUBINETT, STEVEN M. · 2016 to 2021
$3.1M
NCI NIH HHS R01 CA210360NCI NIH HHS U01 CA214182NHLBI NIH HHS T32 HL007035
6 · The paper itself

Abstract

Lung cancer remains the leading cause of cancer-related death due to its advanced stage at diagnosis. Early detection of lung cancer can be improved by better defining who should be screened radiographically and determining which imaging-detected pulmonary nodules are malignant. Gene expression biomarkers measured in normal-appearing airway epithelium provide an opportunity to use lung cancer-associated molecular changes in this tissue for early detection of lung cancer. Molecular changes in the airway may result from an etiologic field of injury and/or field cancerization. The etiologic field of injury reflects the aberrant physiologic response to carcinogen exposure that creates a susceptible microenvironment for cancer initiation. In contrast, field cancerization reflects effects of "first-hit" mutations in a clone of cells from which the tumor ultimately arises or the effects of the tumor on the surrounding tissue. These fields might have value both for assessing lung cancer risk and diagnosis. Cancer-associated gene expression changes in the bronchial airway have recently been used to develop and validate a 23-gene classifier that improves the diagnostic yield of bronchoscopy for lung cancer among intermediate-risk patients. Recent studies have demonstrated that these lung cancer-related gene expression changes extend to nasal epithelial cells that can be sampled noninvasively. While the bronchial gene expression biomarker is being adopted clinically, further work is necessary to explore the potential clinical utility of gene expression profiling in the nasal epithelium for lung cancer diagnosis, lung cancer risk assessment, and precision medicine for lung cancer treatment and chemoprevention.

Indexed as

Biomarkers, TumorTranscriptomeCell Transformation, NeoplasticClinical Decision-MakingDisease ManagementEarly Detection of CancerGene Expression ProfilingGene Expression Regulation, NeoplasticHumansLung NeoplasmsMolecular Diagnostic TechniquesRespiratory MucosaRisk FactorsSmokingBiomarkers, Tumor

Identifiers

PMID29463557
PMCPMC7397497
OpenAlexW2789330799

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.