The Lung EArly Proteins project: A LEAP toward implementing biomarkers in lung cancer screening
Project Number5R01CA262164-03
Former Number1R01CA262164-01
Contact PI/Project LeaderROBBINS, HILARY A.
Awardee OrganizationINTERNATIONAL AGENCY FOR RES ON CANCER
Description
Abstract Text
Summary: The Lung EArly Proteins (LEAP) Project
Lung cancer is the most common cause of cancer death worldwide. Screening by low-dose CT can reduce
lung cancer mortality among current and former smokers, but the balance of benefits and harms could be
improved by leveraging novel tools to optimize decision making. Our objective is to translate a novel panel
of protein biomarkers to optimize the decision (1) to initiate screening and (2) to biopsy a nodule.
We developed the INTEGRAL panel within the Integrative Analysis of Lung Cancer Risk and Etiology U19
project. We identified proteins to include on the panel by analyzing pre-diagnostic samples collected up to 3
years before diagnosis among over 700 lung cancer case-control pairs in prospective cohort studies. The
proteins improved the AUC of a smoking-based model by 0.15, with improvements across histological
types. The Lung EArly Proteins (LEAP) project will carry out two late-stage translational studies to evaluate
the potential to implement this panel in two key contexts.
Aim 1 will determine whether repeated measurements of protein markers over time can better predict
development of lung cancer than a single measurement. A repeat-measures model for lung cancer will be
developed using blood samples (up to 5 per participant) from 546 lung cancer cases and 546 controls in
the Prostate, Lung, and Ovarian Cancer Screening Trial, and independently validated using samples from
539 cases and 539 controls from the Carotene and Retinol Efficacy Trial. We hypothesize that the AUC of
the model with repeat measurements will be higher than for a model with a single measurement.
Aim 2 will determine whether the protein markers can identify cancers among high-risk screen-detected
lung nodules. A biomarker-based prediction model for nodule malignancy will be developed using blood
samples from 685 participants (131 cancers) in the Pittsburgh Lung Screening Study, and then validated
among 830 participants (213 cancers) in the Multicentric Italian Lung Detection (bioMILD) trial and the St
Elizabeth Lung Cancer Screening program. We hypothesize that the AUC of the biomarker model will be
higher than for an established, validated nodule malignancy prediction model (the Brock model).
The LEAP project will clearly define the contexts in which the INTEGRAL panel is clinical useful. Our
mission is to reduce lung cancer mortality by optimizing a proven and effective screening intervention,
using novel tools to extend its benefits to all high-risk individuals and reduce screening harms.
Public Health Relevance Statement
Narrative: The Lung EArly Proteins (LEAP) Project
Lung cancer screening can reduce the risk of lung cancer mortality, but better tools are needed to target
participants who will benefit and to avoid harms in people undergoing screening. We have recently
developed a test that measures proteins in blood to predict development of lung cancer. Our project will
test whether this panel is useful in two specific settings: (1) to decide who should undergo lung cancer
screening by observing how protein measurements change within the same person over time, and (2) to
decide whether to perform a biopsy on high-risk nodules identified during screening.
NIH Spending Category
No NIH Spending Category available.
Project Terms
AddressAll-Trans-RetinolAmerican College of RadiologyBenignBiological AssayBiological MarkersBiopsyBloodBlood specimenCancer EtiologyCaroteneCessation of lifeClassificationClinicalDecision AidDecision MakingDetectionDevelopmentDiagnosisDiagnosticDiagnostic ProcedureEarly identificationEnsureEquilibriumFutureHarm ReductionHistologicInterventionLungLung noduleMalignant - descriptorMalignant NeoplasmsMalignant neoplasm of lungMalignant neoplasm of prostateMeasurementMeasuresMissionModelingNoduleParticipantPatientsPersonsPrimary CareProspective, cohort studyProteinsRiskRisk ReductionSamplingScanningSchemeScreening for Ovarian CancerSmokingTechnologyTestingTimeTranslatingValidationcancer riskcase controlclinical predictorsdesignearly detection biomarkersefficacy trialfollow-upformer smokerhigh riskhigh risk populationimprovedinnovationlow dose computed tomographylung cancer screeninglung developmentmodel developmentmortalitynovelpredictive modelingpredictive toolsprospectiveprotein biomarkersrisk predictionscreeningscreening programtooltranslational studytv watching
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