Performance of a multiplexed dual analyte immunoassay for the early detection of non-small cell lung cancer.

Victoria Doseeva,Vladimir Knezevic,Tracey Colpitts,Grace Gao,Juliana Woodcock

doi:10.1186/s12967-015-0419-y

Abstract

Objectives“PAULA’s” test (Protein Assays Utilizing Lung cancer Analytes) is a novel multiplex immunoassay blood test that incorporates both tumor antigens and autoantibodies to determine the risk that lung cancer (LC) is present in individuals from a high-risk population. The test’s performance characteristics were evaluated in a study using 380 retrospective clinical serum samples.MethodsPAULA’s test is performed on the Luminex xMAP technology platform, and detects a panel of 3 tumor antigens (CEA, CA-125, and CYFRA 21–1) and 1 autoantibody marker (NY-ESO-1). A training set (n = 230) consisting of 115 confirmed diagnoses of non-small cell lung carcinoma (NSCLC) cases and 115 age- and smoking history-matched controls was used to develop the LC predictive model. Data from an independent matched validation set (n = 150) was then used to evaluate the model developed, and determine the ability of the test to distinguish NSCLC cases from controls.ResultsThe 4-biomarker panel was able to discriminate NSCLC cases from controls with 74% sensitivity, 80% specificity, and 0.81 AUC in the training set and with 77% sensitivity, 80% specificity, and 0.85 AUC in the independent validation set. The use of NY-ESO-1 autoantibodies substantially increased the overall sensitivity of NSCLC detection as compared to the 3 tumor markers alone. Overall, the multiplexed 4-biomarker panel assay demonstrated comparable performance to a previously employed 8-biomarker non-multiplexed assay.ConclusionsThese studies confirm the value of using a mixed panel of tumor antigens and autoantibodies in the early detection of NSCLC in high-risk individuals. The results demonstrate that the performance of PAULA’s test makes it suitable for use as an aid to determine which high-risk patients need to be directed to appropriate noninvasive diagnostic follow-up testing, especially low-dose CT (LDCT).

Highlights

In the United States, lung cancer (LC) is the third most commonly diagnosed cancer, with approximately 224,210 new cases expected in 2014 [1]
Despite its Doseeva et al Journal of Translational Medicine (2015) 13:55 relatively good sensitivity for LC detection (93.8%) [7], CT has many drawbacks that suggest its applicability will be limited as a stand-alone detection methodology. These problems include a high false-positive rate; the high cost of testing; and the danger of cumulative diagnostic radiation exposure with repeated testing [8,9,10]. Another major drawback of lowdose computed tomography (LDCT) scanning is overdiagnosis, which has been estimated to be more than 18.5% for all LCs [11]
In 2010, Ostroff et al [24] reported results from a proprietary proteomic assay based on SOMAmers, in which a 12 protein non-small cell lung carcinoma (NSCLC) proteomic signature in serum was identified. This 12-protein panel discriminated NSCLC from controls with 89% sensitivity and 83% specificity in a blinded validation study (341 samples). Results from another multiplex Luminex-based assay for the detection of early stage NSCLC using protein biomarkers was reported by Bigbee et al in 2012 [28]

Summary

Introduction

In the United States, LC is the third most commonly diagnosed cancer, with approximately 224,210 new cases expected in 2014 [1]. Despite its Doseeva et al Journal of Translational Medicine (2015) 13:55 relatively good sensitivity for LC detection (93.8%) [7], CT has many drawbacks that suggest its applicability will be limited as a stand-alone detection methodology These problems include a high false-positive rate (including the inability to unambiguously distinguish benign nodules that can involve expensive invasive follow-up procedures); the high cost of testing; and the danger of cumulative diagnostic radiation exposure with repeated testing [8,9,10]. Another major drawback of lowdose computed tomography (LDCT) scanning is overdiagnosis, which has been estimated to be more than 18.5% for all LCs [11]

Objectives

Methods

Results