Method validation of protein biomarkers in support of drug development or clinical diagnosis/prognosis☆

Lee, Jean W.; Hall, Michael

doi:10.1016/j.jchromb.2008.11.022

Cited by 84 publications

(60 citation statements)

References 89 publications

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“…The strengths of MAAAs are the incorporation of multiple informative data points as well as these are typically undertaken by a single dedicated facility (Lee & Hall 2009). …”

Section: Discussionmentioning

confidence: 99%

A multianalyte PCR blood test outperforms single analyte ELISAs (chromogranin A, pancreastatin, neurokinin A) for neuroendocrine tumor detection

Modlin

Drozdov

Alaimo

et al. 2014

Endocrine-Related Cancer

103

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A critical requirement in neuroendocrine tumor (NET) management is a sensitive, specific and reproducible blood biomarker test. We evaluated a PCR-based 51 transcript signature (NETest) and compared it to chromogranin A (CgA), pancreastatin (PST) and neurokinin A (NKA). The multigene signature was evaluated in two groups: i) a validation set of 40 NETs and controls and ii) a prospectively collected group of NETs (nZ41, 61% small intestinal, 50% metastatic, 44% currently treated and 41 age-sex matched controls). Samples were analyzed by a two-step PCR (51 marker genes) protocol and ELISAs for CgA, PST and NKA. Sensitivity comparisons included c 2 , non-parametric measurements, ROC curves and predictive feature importance (PFAI) analyses. NETest identified 38 of 41 NETs. Performance metrics were: sensitivity 92.8%, specificity 92.8%, positive predictive value 92.8% and negative predictive value 92.8%. Single analyte ELISA metrics were: CgA 76, 59, 65, and 71%; PST 63, 56, 59, and 61% and NKA 39, 93, 84, and 60%. The AUCs (ROC analysis) were: NETest: 0.96G0.025, CgA: 0.67G0.06, PST 0.56G0.06, NKA: 0.66G0.06. NETest significantly outperformed single analyte tests (area differences: 0.284-0.403, Z-statistic 4.85-5.9, P!0.0001). PFAI analysis determined NETest had most value (69%) in diagnosis (CgA (13%), PST (9%), and NKA (9%)). Test data were consistent with the validation set (NETest O95% sensitivity and specificity, AUC Z0.98 vs single analytes: 59-67% sensitivity, AUCs: 0.58-0.63). The NETest is significantly more sensitive and efficient (O93%) than single analyte assays (CgA, PST or NKA) in NET diagnosis. Blood-based multigene analytic measurement will facilitate early detection of disease recurrence and can predict therapeutic efficacy.

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“…The strengths of MAAAs are the incorporation of multiple informative data points as well as these are typically undertaken by a single dedicated facility (Lee & Hall 2009). …”

Section: Discussionmentioning

confidence: 99%

A multianalyte PCR blood test outperforms single analyte ELISAs (chromogranin A, pancreastatin, neurokinin A) for neuroendocrine tumor detection

Modlin

Drozdov

Alaimo

et al. 2014

Endocrine-Related Cancer

103

View full text Add to dashboard Cite

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“…This makes the specificity an inherent problem for all LBAs. The goal of most LBA specificity tests is not to demonstrate absolute assay specificity, but rather to provide information regarding what is being measured to fulfill the purpose of the intended application [13].…”

Section: Parallelism and Specificitymentioning

confidence: 99%

“…They also suggested using a tiered approach to validate both exploratory and advanced methods [6]. Since then, parallelism experiments for biomarker assays have been heatedly discussed and have been mentioned in numerous reviews and white papers [7,[12][13][14][15][16][17][18][19][20][21][22][23][24]. Valentin et al pointed out parallelism should be the most critical element for biomarker LBAs starting from the feasibility phase.…”

mentioning

confidence: 99%

Parallelism Experiments to Evaluate Matrix Effects, Selectivity and Sensitivity in Ligand-Binding Assay Method Development: Pros and Cons

Bennett

2017

Bioanalysis

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Parallelism is an essential experiment characterizing relative accuracy for a ligandbinding assay (LBA). By assessing the effects of dilution on the quantitation of endogenous analyte(s) in matrix, selectivity, matrix effects, minimum required dilution, endogenous levels of healthy and diseased populations and the LLOQ are assessed in a single experiment. This review compares and discusses all available approaches that can be used to assess key assay parameters for pharmacokinetic and biomarker LBAs, as well as the advantages and disadvantages of each approach. This review also summarizes a systematic approach that can apply to guide endogenous LBA method development and optimization with a suggested way to interpret parallelism data.

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“…The generated prototype assay needs careful validation. Basic analytical characteristics to be examined include assay dose-response curve, measuring range, limits of detection and quantification, accuracy, imprecision, and analytical specificity (34 ). Adhering to federal regulations that govern human diagnostic testing, known as the Clinical Laboratory Improvement Amendments, during analytical assay validation could increase the reliability and quality of the data (35 ).…”

Section: Assaymentioning

confidence: 99%

The Long Journey of Cancer Biomarkers from the Bench to the Clinic

2013

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BACKGROUND Protein cancer biomarkers serve multiple clinical purposes, both early and late, during disease progression. The search for new and better biomarkers has become an integral component of contemporary cancer research. However, the number of new biomarkers cleared by the US Food and Drug Administration has declined substantially over the last 10 years, raising concerns regarding the efficiency of the biomarker-development pipeline. CONTENT We describe different clinical uses of cancer biomarkers and their performance requirements. We also present examples of protein cancer biomarkers currently in clinical use and their limitations. The major barriers that candidate biomarkers need to overcome to reach the clinic are addressed. Finally, the long and arduous journey of a protein cancer biomarker from the bench to the clinic is outlined with an example. SUMMARY The journey of a protein biomarker from the bench to the clinic is long and challenging. Every step needs to be meticulously planned and executed to succeed. The history of clinically useful biomarkers suggests that at least a decade is required for the transition of a marker from the bench to the bedside. Therefore, it may be too early to expect that the new technological advances will catalyze the anticipated biomarker revolution any time soon.

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Method validation of protein biomarkers in support of drug development or clinical diagnosis/prognosis☆

Cited by 84 publications

References 89 publications

A multianalyte PCR blood test outperforms single analyte ELISAs (chromogranin A, pancreastatin, neurokinin A) for neuroendocrine tumor detection

A multianalyte PCR blood test outperforms single analyte ELISAs (chromogranin A, pancreastatin, neurokinin A) for neuroendocrine tumor detection

Parallelism Experiments to Evaluate Matrix Effects, Selectivity and Sensitivity in Ligand-Binding Assay Method Development: Pros and Cons

The Long Journey of Cancer Biomarkers from the Bench to the Clinic

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