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Fractal circuit sensors enable rapid quantification of biomarkers for donor lung assessment for transplantation.

Sage AT, Besant JD, Mahmoudian L, Poudineh M, Bai X, Zamel R, Hsin M, Sargent EH, Cypel M, Liu M, Keshavjee S, Kelley SO - Sci Adv (2015)

Bottom Line: Using fractal circuit sensors (FraCS), three-dimensional metal structures with large surface areas, we were able to rapidly (<20 min) and reproducibly quantify small differences in the expression of interleukin-6 (IL-6), IL-10, and ATP11B mRNA in donor lung biopsies.A proof-of-concept study using 52 human donor lungs was performed to develop a model that was used to predict, with excellent sensitivity (74%) and specificity (91%), the incidence of PGD for a donor lung.This work provides an important step toward bringing rapid diagnostic mRNA profiling to clinical application in lung transplantation.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, Ontario M5S 3M2, Canada.

ABSTRACT
Biomarker profiling is being rapidly incorporated in many areas of modern medical practice to improve the precision of clinical decision-making. This potential improvement, however, has not been transferred to the practice of organ assessment and transplantation because previously developed gene-profiling techniques require an extended period of time to perform, making them unsuitable in the time-sensitive organ assessment process. We sought to develop a novel class of chip-based sensors that would enable rapid analysis of tissue levels of preimplantation mRNA markers that correlate with the development of primary graft dysfunction (PGD) in recipients after transplant. Using fractal circuit sensors (FraCS), three-dimensional metal structures with large surface areas, we were able to rapidly (<20 min) and reproducibly quantify small differences in the expression of interleukin-6 (IL-6), IL-10, and ATP11B mRNA in donor lung biopsies. A proof-of-concept study using 52 human donor lungs was performed to develop a model that was used to predict, with excellent sensitivity (74%) and specificity (91%), the incidence of PGD for a donor lung. Thus, the FraCS-based approach delivers a key predictive value test that could be applied to enhance transplant patient outcomes. This work provides an important step toward bringing rapid diagnostic mRNA profiling to clinical application in lung transplantation.

No MeSH data available.


Related in: MedlinePlus

Lung assessment chip and analysis of lung tissue.(A) A multiplexed chip that could accommodate the parallel analysis of the five markers tested as proof of principle was prepared. (B) Correlation of signals obtained from purified RNA from a lung biopsy versus unpurified lysate of the same biopsy (r indicates Pearson’s correlation coefficient). (C) Representative data obtained from a good-outcome lung. (D) Representative data obtained from a poor-outcome lung. The signals are normalized to GAPDH controls, and the nonspecific D. melanogaster signal is shown as a dashed line. Data represent n = 15 different sensors. Columns represent mean, and error bars correspond to SEM. (E to G) Comparison of the FraCS assay response (left y axis) to qPCR expression levels (right y axis) of the same biopsy [PGD0/I (n = 9 to 11), PGDIII+ (n = 9 to 12)] run on both platforms for (E) IL-6, (F) IL-10, and (G) ATP11B.
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Figure 4: Lung assessment chip and analysis of lung tissue.(A) A multiplexed chip that could accommodate the parallel analysis of the five markers tested as proof of principle was prepared. (B) Correlation of signals obtained from purified RNA from a lung biopsy versus unpurified lysate of the same biopsy (r indicates Pearson’s correlation coefficient). (C) Representative data obtained from a good-outcome lung. (D) Representative data obtained from a poor-outcome lung. The signals are normalized to GAPDH controls, and the nonspecific D. melanogaster signal is shown as a dashed line. Data represent n = 15 different sensors. Columns represent mean, and error bars correspond to SEM. (E to G) Comparison of the FraCS assay response (left y axis) to qPCR expression levels (right y axis) of the same biopsy [PGD0/I (n = 9 to 11), PGDIII+ (n = 9 to 12)] run on both platforms for (E) IL-6, (F) IL-10, and (G) ATP11B.

Mentions: Multiplexed chips that allowed parallel analysis of the lung assessment markers were created. Each chip contained up to five sets of FraCS that could be individually functionalized with probes against the marker set of interest (Fig. 4A). Critical to minimizing turnaround time and complexity of the LTx assay is the ability to perform quantitative analysis on human lung tissue biopsies without an mRNA purification step. To achieve this, we developed a rapid (~5 min) chemical lysis method based on non-ionic detergents that were effective in lysing the lung tissue while remaining compatible with FraCS and the electrochemical reporter system. To ensure consistency for signals obtained using unpurified lysate and total RNA from the same donor lung sample, we compared the FraCS response of both types of samples (Fig. 4B). There was a strong, positive correlation of the biomarker responses for both the pure RNA and the unpurified lysate—which indicates that the assay can accommodate a notable increase in the complexity of the sample matrix.


Fractal circuit sensors enable rapid quantification of biomarkers for donor lung assessment for transplantation.

Sage AT, Besant JD, Mahmoudian L, Poudineh M, Bai X, Zamel R, Hsin M, Sargent EH, Cypel M, Liu M, Keshavjee S, Kelley SO - Sci Adv (2015)

Lung assessment chip and analysis of lung tissue.(A) A multiplexed chip that could accommodate the parallel analysis of the five markers tested as proof of principle was prepared. (B) Correlation of signals obtained from purified RNA from a lung biopsy versus unpurified lysate of the same biopsy (r indicates Pearson’s correlation coefficient). (C) Representative data obtained from a good-outcome lung. (D) Representative data obtained from a poor-outcome lung. The signals are normalized to GAPDH controls, and the nonspecific D. melanogaster signal is shown as a dashed line. Data represent n = 15 different sensors. Columns represent mean, and error bars correspond to SEM. (E to G) Comparison of the FraCS assay response (left y axis) to qPCR expression levels (right y axis) of the same biopsy [PGD0/I (n = 9 to 11), PGDIII+ (n = 9 to 12)] run on both platforms for (E) IL-6, (F) IL-10, and (G) ATP11B.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4643795&req=5

Figure 4: Lung assessment chip and analysis of lung tissue.(A) A multiplexed chip that could accommodate the parallel analysis of the five markers tested as proof of principle was prepared. (B) Correlation of signals obtained from purified RNA from a lung biopsy versus unpurified lysate of the same biopsy (r indicates Pearson’s correlation coefficient). (C) Representative data obtained from a good-outcome lung. (D) Representative data obtained from a poor-outcome lung. The signals are normalized to GAPDH controls, and the nonspecific D. melanogaster signal is shown as a dashed line. Data represent n = 15 different sensors. Columns represent mean, and error bars correspond to SEM. (E to G) Comparison of the FraCS assay response (left y axis) to qPCR expression levels (right y axis) of the same biopsy [PGD0/I (n = 9 to 11), PGDIII+ (n = 9 to 12)] run on both platforms for (E) IL-6, (F) IL-10, and (G) ATP11B.
Mentions: Multiplexed chips that allowed parallel analysis of the lung assessment markers were created. Each chip contained up to five sets of FraCS that could be individually functionalized with probes against the marker set of interest (Fig. 4A). Critical to minimizing turnaround time and complexity of the LTx assay is the ability to perform quantitative analysis on human lung tissue biopsies without an mRNA purification step. To achieve this, we developed a rapid (~5 min) chemical lysis method based on non-ionic detergents that were effective in lysing the lung tissue while remaining compatible with FraCS and the electrochemical reporter system. To ensure consistency for signals obtained using unpurified lysate and total RNA from the same donor lung sample, we compared the FraCS response of both types of samples (Fig. 4B). There was a strong, positive correlation of the biomarker responses for both the pure RNA and the unpurified lysate—which indicates that the assay can accommodate a notable increase in the complexity of the sample matrix.

Bottom Line: Using fractal circuit sensors (FraCS), three-dimensional metal structures with large surface areas, we were able to rapidly (<20 min) and reproducibly quantify small differences in the expression of interleukin-6 (IL-6), IL-10, and ATP11B mRNA in donor lung biopsies.A proof-of-concept study using 52 human donor lungs was performed to develop a model that was used to predict, with excellent sensitivity (74%) and specificity (91%), the incidence of PGD for a donor lung.This work provides an important step toward bringing rapid diagnostic mRNA profiling to clinical application in lung transplantation.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, Ontario M5S 3M2, Canada.

ABSTRACT
Biomarker profiling is being rapidly incorporated in many areas of modern medical practice to improve the precision of clinical decision-making. This potential improvement, however, has not been transferred to the practice of organ assessment and transplantation because previously developed gene-profiling techniques require an extended period of time to perform, making them unsuitable in the time-sensitive organ assessment process. We sought to develop a novel class of chip-based sensors that would enable rapid analysis of tissue levels of preimplantation mRNA markers that correlate with the development of primary graft dysfunction (PGD) in recipients after transplant. Using fractal circuit sensors (FraCS), three-dimensional metal structures with large surface areas, we were able to rapidly (<20 min) and reproducibly quantify small differences in the expression of interleukin-6 (IL-6), IL-10, and ATP11B mRNA in donor lung biopsies. A proof-of-concept study using 52 human donor lungs was performed to develop a model that was used to predict, with excellent sensitivity (74%) and specificity (91%), the incidence of PGD for a donor lung. Thus, the FraCS-based approach delivers a key predictive value test that could be applied to enhance transplant patient outcomes. This work provides an important step toward bringing rapid diagnostic mRNA profiling to clinical application in lung transplantation.

No MeSH data available.


Related in: MedlinePlus