Figure 1.
Scatter plot for normalized intensity of 174marker antibody arrays.
Panel A (left) shows strong intra-assay correlation (same sample assayed on the same glass slide, tested on the same day); Panel B (middle) shows strong inter-assay correlation (same sample assayed on different glass slides, tested on different days); Panel C (right) shows poor correlation between cancer and normal samples assayed on the same glass slides, tested on the same day.
Figure 2.
Representative results for 174-marker antibody arrays.
Panel A (left) shows representative fluorescent signal images for array G6; Panel B (middle) shows representative fluorescent signal images for array G7; Panel C (right) shows representative fluorescent signal images for array G8.
Figure 3.
Artificial neural network analysis of 174-marker antibody array results in ovarian cancers and healthy controls.
3a. Artificial neural network analysis of 174-marker antibody array results comparing ovarian cancers and healthy controls. Samples representing both the training set and prediction set are depicted in the graph.
3b. The top 8 markers with the greatest impact in artificial neural network analysis of 174-marker antibody arrays in ovarian cancers and healthy controls are presented.
Figure 4.
Hierarchical cluster analysis of 174-marker antibody arrays in ovarian cancers and healthy controls.
Figure 5.
Split-Point Score Analysis of 5 serum markers in ovarian cancer and healthy controls.
Panel A (top left): Dot histogram plot with 5-analyte split-point score classification of sera from healthy control (N) and ovarian cancer (CA). Correctly classified normal serum samples should have a score of 0 to 2, whereas samples from ovarian cancer patients should have a score of 3 to 5; Panel B (top right): The ROC curve for 5-marker panel of split-score analysis of ovarian cancer vs. healthy controls. The ROC is the curve plotted of sensitivity (true positive) against 1-specificity (false positive) values; Panel C (bottom right): Table using five-marker split-point score to classify ovarian cancer patients. A cut-off score of 3 was used.
Figure 6.
Correlation analysis between ELISA and antibody array assays.
Levels of two protein markers (MSP-alpha and TIMP-4) identified as being differentially expressed in ovarian cancer samples using antibody arrays were confirmed with ELISA. The antibody array data were completely concordant with the ELISA data in classifying sera from ovarian cancer patients and healthy controls. Antibody array data are shown as median array signal intensity (FI), and ELISA data are shown as mean protein concentration (ng/ml).