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Toward rapid, high-sensitivity, volume-constrained biomarker quantification and validation using backscattering interferometry.

Olmsted IR, Hassanein M, Kussrow A, Hoeksema M, Li M, Massion PP, Bornhop DJ - Anal. Chem. (2014)

Bottom Line: The two techniques correlated well, ranging from 3-29% difference for Cyfra 21-1 in a blinded patient sample analysis.The label-free and free-solution operation of BSI allowed for a significant improvement in analysis speed, with greater ease, improved LOQ values, and excellent day-to-day reproducibility.The results indicate that the BSI platform can enable rapid, sensitive analytical validation of serum biomarkers and should significantly impact the validation bottleneck of biomarkers.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemistry and the Vanderbilt Institute of Chemical Biology, Vanderbilt University , 4226 Stevenson Center, Nashville, Tennessee 37235, United States.

ABSTRACT
Realizing personalized medicine, which promises to enable early disease detection, efficient diagnostic staging, and therapeutic efficacy monitoring, hinges on biomarker quantification in patient samples. Yet, the lack of a sensitive technology and assay methodology to rapidly validate biomarker candidates continues to be a bottleneck for clinical translation. In our first direct and quantitative comparison of backscattering interferometry (BSI) to fluorescence sensing by ELISA, we show that BSI could aid in overcoming this limitation. The analytical validation study was performed against ELISA for two biomarkers for lung cancer detection: Cyfra 21-1 and Galectin-7. Spiked serum was used for calibration and comparison of analytical figures of merit, followed by analysis of blinded patient samples. Using the ELISA antibody as the probe chemistry in a mix-and-read assay, BSI provided significantly lower detection limits for spiked serum samples with each of the biomarkers. The limit of quantification (LOQ) for Cyrfa-21-1 was measured to be 230 pg/mL for BSI versus 4000 pg/mL for ELISA, and for Galectin-7, it was 13 pg/mL versus 500 pg/mL. The coefficient of variation for 5 day, triplicate determinations was <15% for BSI and <10% for ELISA. The two techniques correlated well, ranging from 3-29% difference for Cyfra 21-1 in a blinded patient sample analysis. The label-free and free-solution operation of BSI allowed for a significant improvement in analysis speed, with greater ease, improved LOQ values, and excellent day-to-day reproducibility. In this unoptimized format, BSI required 5.5-fold less sample quantity needed for ELISA (a 10 point calibration curve measured in triplicate required 36 μL of serum for BSI vs 200 μL for ELISA). The results indicate that the BSI platform can enable rapid, sensitive analytical validation of serum biomarkers and should significantly impact the validation bottleneck of biomarkers.

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(A) Calibration curvesfor BSI with Cyfra 21-1 spiked into serum(red triangles) and for ELISA in spiked serum (green circles). (B)Calibration curves for Galectin-7 spiked serum show that the BSI LOQ(blue diamonds) is better than for ELISA (green circles) and is improvedby using both the detection and capture antibodies in the assay (redtriangles). Error bars on both plots represent the standard deviationfor repeat triplicate determinations over a 5 day period.
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fig2: (A) Calibration curvesfor BSI with Cyfra 21-1 spiked into serum(red triangles) and for ELISA in spiked serum (green circles). (B)Calibration curves for Galectin-7 spiked serum show that the BSI LOQ(blue diamonds) is better than for ELISA (green circles) and is improvedby using both the detection and capture antibodies in the assay (redtriangles). Error bars on both plots represent the standard deviationfor repeat triplicate determinations over a 5 day period.

Mentions: In our proof-of-concept experiment, we comparedthe performanceof BSI and ELISA with analysis of human serum and plasma spiked withthe protein biomarkers of interest. In all of the studies reportedhere, we used the probe chemistry (antibody[s]) from the ELISA kitfor the BSI assay. Using our free-solution, mix-and-read approach,we achieved excellent sensitivity and reproducibility by spiking humanserum with Cyfra 21-1. For example, Figure 2A presents the calibration curves for BSI and ELISA, showing a morethan a 17.3-fold increase in sensitivity. The plot also shows thatthe assay was highly reproducible over a 5 day period.


Toward rapid, high-sensitivity, volume-constrained biomarker quantification and validation using backscattering interferometry.

Olmsted IR, Hassanein M, Kussrow A, Hoeksema M, Li M, Massion PP, Bornhop DJ - Anal. Chem. (2014)

(A) Calibration curvesfor BSI with Cyfra 21-1 spiked into serum(red triangles) and for ELISA in spiked serum (green circles). (B)Calibration curves for Galectin-7 spiked serum show that the BSI LOQ(blue diamonds) is better than for ELISA (green circles) and is improvedby using both the detection and capture antibodies in the assay (redtriangles). Error bars on both plots represent the standard deviationfor repeat triplicate determinations over a 5 day period.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4215853&req=5

fig2: (A) Calibration curvesfor BSI with Cyfra 21-1 spiked into serum(red triangles) and for ELISA in spiked serum (green circles). (B)Calibration curves for Galectin-7 spiked serum show that the BSI LOQ(blue diamonds) is better than for ELISA (green circles) and is improvedby using both the detection and capture antibodies in the assay (redtriangles). Error bars on both plots represent the standard deviationfor repeat triplicate determinations over a 5 day period.
Mentions: In our proof-of-concept experiment, we comparedthe performanceof BSI and ELISA with analysis of human serum and plasma spiked withthe protein biomarkers of interest. In all of the studies reportedhere, we used the probe chemistry (antibody[s]) from the ELISA kitfor the BSI assay. Using our free-solution, mix-and-read approach,we achieved excellent sensitivity and reproducibility by spiking humanserum with Cyfra 21-1. For example, Figure 2A presents the calibration curves for BSI and ELISA, showing a morethan a 17.3-fold increase in sensitivity. The plot also shows thatthe assay was highly reproducible over a 5 day period.

Bottom Line: The two techniques correlated well, ranging from 3-29% difference for Cyfra 21-1 in a blinded patient sample analysis.The label-free and free-solution operation of BSI allowed for a significant improvement in analysis speed, with greater ease, improved LOQ values, and excellent day-to-day reproducibility.The results indicate that the BSI platform can enable rapid, sensitive analytical validation of serum biomarkers and should significantly impact the validation bottleneck of biomarkers.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemistry and the Vanderbilt Institute of Chemical Biology, Vanderbilt University , 4226 Stevenson Center, Nashville, Tennessee 37235, United States.

ABSTRACT
Realizing personalized medicine, which promises to enable early disease detection, efficient diagnostic staging, and therapeutic efficacy monitoring, hinges on biomarker quantification in patient samples. Yet, the lack of a sensitive technology and assay methodology to rapidly validate biomarker candidates continues to be a bottleneck for clinical translation. In our first direct and quantitative comparison of backscattering interferometry (BSI) to fluorescence sensing by ELISA, we show that BSI could aid in overcoming this limitation. The analytical validation study was performed against ELISA for two biomarkers for lung cancer detection: Cyfra 21-1 and Galectin-7. Spiked serum was used for calibration and comparison of analytical figures of merit, followed by analysis of blinded patient samples. Using the ELISA antibody as the probe chemistry in a mix-and-read assay, BSI provided significantly lower detection limits for spiked serum samples with each of the biomarkers. The limit of quantification (LOQ) for Cyrfa-21-1 was measured to be 230 pg/mL for BSI versus 4000 pg/mL for ELISA, and for Galectin-7, it was 13 pg/mL versus 500 pg/mL. The coefficient of variation for 5 day, triplicate determinations was <15% for BSI and <10% for ELISA. The two techniques correlated well, ranging from 3-29% difference for Cyfra 21-1 in a blinded patient sample analysis. The label-free and free-solution operation of BSI allowed for a significant improvement in analysis speed, with greater ease, improved LOQ values, and excellent day-to-day reproducibility. In this unoptimized format, BSI required 5.5-fold less sample quantity needed for ELISA (a 10 point calibration curve measured in triplicate required 36 μL of serum for BSI vs 200 μL for ELISA). The results indicate that the BSI platform can enable rapid, sensitive analytical validation of serum biomarkers and should significantly impact the validation bottleneck of biomarkers.

Show MeSH
Related in: MedlinePlus