Improved reproducibility of reverse-phase protein microarrays using array microenvironment normalization - PubMed (original) (raw)

Improved reproducibility of reverse-phase protein microarrays using array microenvironment normalization

Troy Anderson et al. Proteomics. 2009 Dec.

Abstract

We introduce a novel experimental methodology for the reverse-phase protein microarray platform which reduces the typical measurement CV as much as 70%. The methodology, referred to as array microenvironment normalization, increases the statistical power of the platform. In the experiment, it enabled the detection of a 1.1-fold shift in prostate specific antigen concentration using approximately six technical replicates rather than the 37 replicates previously required. The improved reproducibility and statistical power should facilitate clinical implementation of the platform.

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Conflict of interest statement

Conflict of interest: Authors (excluding Dr. Raimond Winslow) have affiliation with Theranostic Health Inc. which is commercializing the RPMA technology.

Figures

Figure 1

Figure 1

RPMA with AMN experimental design. Top is the array 1 total protein stain. Bottom is a rendering of the “checkerboard” control layout used to carry out AMN for each sample spot.

Figure 2

Figure 2

Linearity and reproducibility improvement with AMN demonstrated for array 1. (A) Scatter plot of TPN relative intensity (no AMN) for each sample of array 1 versus the known PSA concentration. (B) Scatter plot of AMN relative intensity for each sample of array 1 versus the known PSA concentration. (C) Scatter plot of the AMN relative intensity versus TPN relative intensity for samples of array 1 which differed in PSA concentration by 1.4-fold. (D) Same as (C) except displays samples differing in PSA concentration by 1.1-fold for array 1. The spread in the data is always much greater before AMN is implemented.

Figure 3

Figure 3

AMN improves the average coefficient of variance by 72% which results in an increased power to detect shifts in expression with fewer replicates. (A) Bar plots of measured coefficient of variance for the 32 replicates of each sample containing the specified amount of PSA for arrays 1, 2 and 3 both with and without AMN. (B) Power curve displaying the minimum number of technical replicates needed to detect the fold change specified in the _x_-axis with p<0.05 and power >0.80 using a _t_-test when the CV=5 or 15% (representative of the CV with and without AMN).

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