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

Doseeva, Victoria; Colpitts, Tracey L.; Gao, Grace; Woodcock, Juliana B.; Knežević, Vladimir

doi:10.1186/s12967-015-0419-y

Cited by 97 publications

(69 citation statements)

References 71 publications

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“…In a validation set the panel discriminated NSCLC (with 67% early-stage) from healthy controls with a sensitivity of 77% and specificity of 80%. However its clinical applicability is limited since benign conditions were not included4. None of the cited studies pursued such a high sensitivity as we do, which would probably derive in a diminished specificity.…”

Section: Discussionmentioning

confidence: 87%

“…Here we provide an improved classification algorithm achieving a superior sensitivity for LC in the context of RDU. In this refined algorithm, besides the smoking status, the routinely used CEA was incorporated, corroborating its diagnostic capacity especially for late-stage tumours4242526. Briefly, our approach involves the measurement of EGF, sCD26, CAL and CEA to generate a classification score for each individual to predict LC.…”

Section: Discussionmentioning

confidence: 95%

“…Despite recent advances in treatment, this neoplasia carries an extremely poor prognosis, with an overall 5-year survival rate of 13% 2, consequence of the difficulty of detection at an early stage3. Therefore, early detection when surgery may be curative is the best way to reduce LC mortality24.…”

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confidence: 99%

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Highly Sensitive Marker Panel for Guidance in Lung Cancer Rapid Diagnostic Units

Blanco-Prieto

Chiara

Rodríguez-Girondo

et al. 2017

Sci Rep

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While evidence for lung cancer screening implementation in Europe is awaited, Rapid Diagnostic Units have been established in many hospitals to accelerate the early diagnosis of lung cancer. We seek to develop an algorithm to detect lung cancer in a symptomatic population attending such unit, based on a sensitive serum marker panel. Serum concentrations of Epidermal Growth Factor, sCD26, Calprotectin, Matrix Metalloproteinases −1, −7, −9, CEA and CYFRA 21.1 were determined in 140 patients with respiratory symptoms (lung cancer and controls with/without benign pathology). Logistic Lasso regression was performed to derive a lung cancer prediction model, and the resulting algorithm was tested in a validation set. A classification rule based on EGF, sCD26, Calprotectin and CEA was established, able to reasonably discriminate lung cancer with 97% sensitivity and 43% specificity in the training set, and 91.7% sensitivity and 45.4% specificity in the validation set. Overall, the panel identified with high sensitivity stage I non-small cell lung cancer (94.7%) and 100% small-cell lung cancers. Our study provides a sensitive 4-marker classification algorithm for lung cancer detection to aid in the management of suspicious lung cancer patients in the context of Rapid Diagnostic Units.

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Section: Discussionmentioning

confidence: 87%

Section: Discussionmentioning

confidence: 95%

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Highly Sensitive Marker Panel for Guidance in Lung Cancer Rapid Diagnostic Units

Blanco-Prieto

Chiara

Rodríguez-Girondo

et al. 2017

Sci Rep

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“…Other TAAbs were excluded from the review because relevant data were available from fewer than 3 articles . Five of the included studies examined only small-cell lung cancer (SCLC) [45,50,52,58,67], and eight included only non-small cell lung cancer (NSCLC) [28,47,54,55,57,59,64,109]. A total of 50 articles were based on serum specimens, while the remaining 3 were based on plasma samples.…”

Section: Basic Information About the Included Studiesmentioning

confidence: 99%

Diagnostic Value of Autoantibodies in Lung Cancer: a Systematic Review and Meta-Analysis

Qin¹,

Zeng²,

Yang³

et al. 2018

Cell Physiol Biochem

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Background/Aims: Recently, many studies have demonstrated that various tumor-associated autoantibodies have been detected in early stages of lung cancer. Therefore, we conducted a meta-analysis to comprehensively evaluate available evidence on the diagnostic value of autoantibodies against tumor-associated antigens in lung cancer. Methods: We systematically searched PubMed, Scopus, Web of Science and other databases through 23 March 2018. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2. We used the bivariate mixed-effect models to calculate pooled values of sensitivity, specificity, positive likelihood ratios, negative likelihood ratios, diagnostic odds ratios and associated 95% confidence intervals. Summary receiver operating characteristic (SROC) curves were used to summarize overall test performance. Deek’s funnel plot was used to detect publication bias. Results: Review of 468 candidate articles identified fifty-three articles with a total of 11,515 patients for qualitative review and meta-analysis. Pooled sensitivity, specificity and area under the SROC curve were as follows for tumor-associated autoantibodies against the following proteins: p53, 0.19, 0.98, 0.82; NY-ESO-1, 0.17, 0.98, 0.90; Survivin, 0.19, 0.99, 0.96; c-myc, 0.14, 0.98, 0.45; Cyclin B1, 0.18, 0.98, 0.91; GBU4-5, 0.07, 0.98, 0.91; CAGE, 0.14, 0.98, 0.90; p16, 0.08, 0.97, 0.91; SOX2, 0.14, 0.99, 0.93; and HuD, 0.17, 0.99, 0.82. Conclusion: Each tumor-associated autoantibody on its own showed excellent diagnostic specificity for lung cancer but inadequate sensitivity. Our results suggest that combinations or panels of tumor-associated autoantibodies may provide better sensitivity for diagnosing lung cancer, and the diagnostic accuracy of tumor-associated autoantibodies should be validated in more studies.

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“…Other groups have explored the utility of blood and nonblood‐based biomarkers for lung cancer screening. A representative list include using gene expression of peripheral blood mononuclear cells, serum proteins, microRNAs, immunoassay, methylation, exhaled volatile organic compounds and urine protein biomarkers . Unlike other blood‐based lung cancer detection methods, the FPR1 ratio has been demonstrated to detect both NSCLC and SCLC.…”

Section: Discussionmentioning

confidence: 99%

Whole blood FPR1 mRNA expression predicts both non‐small cell and small cell lung cancer

Morris¹,

Vachani

Pass

et al. 2018

Intl Journal of Cancer

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While long‐term survival rates for early‐stage lung cancer are high, most cases are diagnosed in later stages that can negatively impact survival rates. We aim to design a simple, single biomarker blood test for early‐stage lung cancer that is robust to preclinical variables and can be readily implemented in the clinic. Whole blood was collected in PAXgene tubes from a training set of 29 patients, and a validation set of 260 patients, of which samples from 58 patients were prospectively collected in a clinical trial specifically for our study. After RNA was extracted, the expressions of FPR1 and a reference gene were quantified by an automated one‐step Taqman RT‐PCR assay. Elevated levels of FPR1 mRNA in whole blood predicted lung cancer status with a sensitivity of 55% and a specificity of 87% on all validation specimens. The prospectively collected specimens had a significantly higher 68% sensitivity and 89% specificity. Results from patients with benign nodules were similar to healthy volunteers. No meaningful correlation was present between our test results and any clinical characteristic other than lung cancer diagnosis. FPR1 mRNA levels in whole blood can predict the presence of lung cancer. Using this as a reflex test for positive lung cancer screening computed tomography scans has the potential to increase the positive predictive value. This marker can be easily measured in an automated process utilizing off‐the‐shelf equipment and reagents. Further work is justified to explain the source of this biomarker.

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

Cited by 97 publications

References 71 publications

Highly Sensitive Marker Panel for Guidance in Lung Cancer Rapid Diagnostic Units

Highly Sensitive Marker Panel for Guidance in Lung Cancer Rapid Diagnostic Units

Diagnostic Value of Autoantibodies in Lung Cancer: a Systematic Review and Meta-Analysis

Whole blood FPR1 mRNA expression predicts both non‐small cell and small cell lung cancer

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