Current Readings: Blood-Based Biomarkers for Lung Cancer

Tsay, J.J.; DeCotiis, Christopher; Greenberg, Alissa K.; Rom, William N.

doi:10.1053/j.semtcvs.2013.11.001

Cited by 13 publications

(11 citation statements)

References 25 publications

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“…Moreover, a panel of assays for autoantibodies with various TAA specificities can effectively detect LC because of the heterogeneity of single antigen expression [ 15 ]. Two recent reviews [ 11 , 16 ] have reported that panels of autoantibodies could be used as blood biomarkers to diagnose early LC or distinguish benign from malignant nodules; however, no meta-analysis was performed to evaluate the diagnostic accuracy of multiplex autoantibodies in these analyses. Furthermore, many relevant studies in this field have been recently published.…”

Section: Introductionmentioning

confidence: 99%

Serum tumor-associated autoantibodies as diagnostic biomarkers for lung cancer: A systematic review and meta-analysis

et al. 2017

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ObjectiveWe performed a comprehensive review and meta-analysis to evaluate the diagnostic values of serum single and multiplex tumor-associated autoantibodies (TAAbs) in patients with lung cancer (LC).MethodsWe searched the MEDLINE and EMBASE databases for relevant studies investigating serum TAAbs for the diagnosis of LC. The primary outcomes included sensitivity, specificity and accuracy of the test.ResultsThe systematic review and meta-analysis included 31 articles with single autoantibody and 39 with multiplex autoantibodies. Enzyme-linked immunosorbent assay (ELISA) was the most common detection method. For the diagnosis of patients with all stages and early-stage LC, different single or combinations of TAAbs demonstrated different diagnostic values. Although individual TAAbs showed low diagnostic sensitivity, the combination of multiplex autoantibodies offered relatively high sensitivity. For the meta-analysis of a same panel of autoantibodies in patients at all stages of LC, the pooled results of the panel of 6 TAAbs (p53, NY-ESO-1, CAGE, GBU4-5, Annexin 1 and SOX2) were: sensitivity 38% (95% CI 0.35–0.40), specificity 89% (95% CI 0.86–0.91), diagnostic accuracy 65.9% (range 62.5–81.8%), AUC 0.52 (0.48–0.57), while the summary estimates of 7 TAAbs (p53, CAGE, NY-ESO-1, GBU4-5, SOX2, MAGE A4 and Hu-D) were: sensitivity 47% (95% CI 0.34–0.60), specificity 90% (95% CI 0.89–0.92), diagnostic accuracy 78.4% (range 67.5–88.8%), AUC 0.90 (0.87–0.93). For the meta-analysis of the same panel of autoantibodies in patients at early-stage of LC, the sensitivities of both panels of 7 TAAbs and 6 TAAbs were 40% and 29.7%, while their specificities were 91% and 87%, respectively.ConclusionsSerum single or combinations of multiplex autoantibodies can be used as a tool for the diagnosis of LC patients at all stages or early-stage, but the combination of multiplex autoantibodies shows a higher detection capacity; the diagnostic value of the panel of 7 TAAbs is higher than the panel of 6 TAAbs, which may be used as potential biomarkers for the early detection of LC.

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Section: Introductionmentioning

confidence: 99%

Serum tumor-associated autoantibodies as diagnostic biomarkers for lung cancer: A systematic review and meta-analysis

et al. 2017

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“…The literature reports a variety of approaches that have been pursued for nearly 2 decades to reach this end, including (1) proteomics-based methods, (2) characterization of genomic expression, (3) monitoring gene methylation, (4) detection of mitochondrial DNA mutations or chromosomal abnormalities, and (5) the detection of such blood-based biomarkers as tumor-derived proteins, microRNA, or autoantibodies arising from a patient’s immune response to tumor cells [ 12 - 14 ]. A number of recent review papers indicate blood-based biomarker detection is the most highly developed of these approaches and support the concept that these biomarkers can be used to detect early stage NSCLC and complement CT imaging [ 15 - 18 ].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2015

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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).

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“…Despite advances in technology and intensive research efforts, no molecular biomarker capable of identifying LC in the early stages has been found to be suitable for clinical use (Nolen et al, 2015;Zhang et al, 2015). Research efforts have been focused on identifying sensitive and specific blood-based biomarkers for early detection of LC, such as: identification of proteins, protein panels or antibodies to tumor-associated antigens; analysis of epigenetic changes such as methylation; microRNA profiling; and gene expression profiling (Tsay et al, 2013). That is, biomarkers derived from tumor tissue have been the main focus for establishing prognostic and predictive markers in LC (Xu-Welliver and Carbone, 2017).…”

Section: Discussionmentioning

confidence: 99%

Volatile organic compounds of biofluids for detecting lung cancer by an electronic nose based on artificial neural network

Mohamed¹,

Mohamed²,

Abdel-Mageed³

et al. 2019

JAB

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Lung cancer (LC) incidence represents 11.5% of all new cancers, resulting in 1.72 million deaths worldwide in 2015. With the aim to investigate the capability of the electronic nose (e-nose) technology for detecting and differentiating complex mixtures of volatile organic compounds in biofluids ex-vivo, we enrolled 50 patients with suspected LC and 50 matching controls. Tissue biopsy was taken from suspicious lung mass for histopathological evaluation and blood, exhaled breath, and urine samples were collected from all participants and qualitatively processed using e-nose. Odor-print patterns were further analysed using the principal component analysis (PCA) and artificial neural network (ANN) analysis. Adenocarcinoma, non-small cell LC and squamous cell carcinoma were the predominant pathological types among LC patients. PCA cluster-plots showed a clear distinction between LC patients and controls for all biological samples; where the overall success ratios of classification for principal components #1 and #2 were: 95.46, 82.01, and 91.66% for blood, breath and urine samples, respectively. Moreover, ANN showed a better discrimination between LC patients and controls with success ratios of 95.74, 91.67 and 100% for blood, breath and urine samples, respectively. The e-nose is an easy noninvasive tool, capable of identifying LC patients from controls with great precision.

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Current Readings: Blood-Based Biomarkers for Lung Cancer

Cited by 13 publications

References 25 publications

Serum tumor-associated autoantibodies as diagnostic biomarkers for lung cancer: A systematic review and meta-analysis

Serum tumor-associated autoantibodies as diagnostic biomarkers for lung cancer: A systematic review and meta-analysis

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

Volatile organic compounds of biofluids for detecting lung cancer by an electronic nose based on artificial neural network

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