Comparative studies of two generations of NanoString nCounter System


Autoři: Lianbo Yu aff001;  Sagar Bhayana aff002;  Naduparambil K. Jacob aff002;  Paolo Fadda aff003
Působiště autorů: Center for Biostatistics, Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio, United States of America aff001;  Department of Radiation Oncology, The Ohio State University, Columbus, Ohio, United States of America aff002;  Genomics Shared Resource, Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio, United States of America aff003
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
doi: 10.1371/journal.pone.0225505

Souhrn

The NanoString nCounter System has been widely used in basic science and translational science research for the past decade. The System consists of two instruments: the PrepStation and the Digital Analyzer, and both have been continuously improved with evolving technologies. A great amount of research data have been generated at multiple research laboratories with the employment of different generations of the System. With the need of integrating multiple datasets, researchers are interested to know whether signals are comparable between different generations of the System. Toward this end, we designed a profiling study to compare performance of two generations of the NanoString nCounter System using a common set of biological samples. Using graphical tools and statistical models, we found that two different generations of NanoString nCounter System produced equivalent signals and signal deviations are in the range of random background noises for the medium-high expression levels.

Klíčová slova:

Analysis of variance – Bionanotechnology – Curve fitting – Experimental design – Hierarchical clustering – MicroRNAs – Nanotechnology – RNA isolation


Zdroje

1. Malkov VA, Serikawa KA, Balantac N, Watters J, Geiss G, Mashadi-Hossein A, Fare T (2009) Multiplexed measurements of gene signatures in different analytes using the Nanostring nCounter Assay System. BMC Res Notes, 2:80. doi: 10.1186/1756-0500-2-80 19426535

2. Kolbert CP, Feddersen RM, Rakhshan F, Grill DE, Simon G, Middha S, Jang JS, Simon V, Schultz DA, Zschunke M, Lingle W, Carr JM, Thompson EA, Oberg AL, Eckloff BW, Wieben ED, Li P, Yang P, Jen J (2013) Multi-platform analysis of microRNA expression measurements in RNA from fresh frozen and FFPE tissues. PLoS One, 8(1):e52517. doi: 10.1371/journal.pone.0052517 23382819

3. Lee J, Sohn I, Do IG, Kim KM, Park SH, Park JO, Park YS, Lim HY, Sohn TS, Bae JM, Choi MG, Lim DH, Min BH, Lee JH, Rhee PL, Kim JJ, Choi DI, Tan IB, Das K, Tan P, Jung SH, Kang WK, Kim S (2014) Nanostring-based multigene assay to predict recurrence for gastric cancer patients after surgery. PLoS One, 9(3):e90133. doi: 10.1371/journal.pone.0090133 24598828

4. Mazumder S, Datta S, Ray JG, Chaudhuri K, Chatterjee R (2019) Liquid biopsy: miRNA as a potential biomarker in oral cancer. Cancer Epidemiol., 58:137–145. doi: 10.1016/j.canep.2018.12.008 30579238

5. Balakrishnan N (2014). Methods and Applications of Statistics in Clinical Trials. Wiley Series in Methods and Applications of Statistics.

6. Montgomery DC (2001). Design and Analysis of Experiments. Wiley.

7. Cleveland WS (1979). Robust Locally Weighted Regression and Smoothing Scatterplots. JASA, 74(368):829–836.

8. Cleveland WS and Devlin SJ (1988) Locally-Weighted Regression: An Approach to Regression Analysis by Local Fitting. JASA, 83(403):596–610.

9. Kulkarni MM. Digital multiplexed gene expression analysis using the NanoString nCounter system. Curr Protoc Mol Biol. 2011 Apr;Chapter 25:Unit25B.10.

10. Veldman-Jones MH, Lai Z, Wappett M, Harbron CG, Barrett JC, Harrington EA, Thress KS. Reproducible, Quantitative, and Flexible Molecular Subtyping of Clinical DLBCL Samples Using the NanoString nCounter System. Clin Cancer Res. 2015 May 15;21(10):2367–78. doi: 10.1158/1078-0432.CCR-14-0357 25301847

11. Veldman-Jones MH, Brant R, Rooney C, Geh C, Emery H, Harbron CG, Wappett M, Sharpe A, Dymond M, Barrett JC, Harrington EA, Marshall G. Evaluating Robustness and Sensitivity of the NanoString Technologies nCounter Platform to Enable Multiplexed Gene Expression Analysis of Clinical Samples. Cancer Res. 2015 Jul 1;75(13):2587–93. doi: 10.1158/0008-5472.CAN-15-0262 26069246


Článek vyšel v časopise

PLOS One


2019 Číslo 11