Fig. 2

Aptamer-based proteomic screening of bladder cancer urine uncovers several clusters of up- and downregulated proteins. A A volcano plot representation of the results of the aptamer-based screening of 1317 proteins analyzed in 42 urine samples (15 UC, BC (Ta-Tis) = 9, BC (T1) = 9, BC (T2–T4) = 9). Data was log-transformed and analyzed as detailed in the “Methods” section. Of the 330 proteins that were differentially expressed between the groups, 93 proteins were elevated at fold change > 2 in BC when compared to UC. Each dot represents one of the 1317 proteins. The x-axis plots the log₂ transform of the fold change. The y-axis displays the − log₁₀ transform of the p-value. B A 2D PCA plot of all subjects, using the 119 proteins that were differentially expressed after multiple testing corrections (BC vs UC, Mann–Whitney q-value < 0.05). Bladder cancer is represented by a red circle while urology control is represented by a green circle. The first three principal components are displayed on each axis of the plot. C A heatmap representation of the results of the aptamer-based screen displaying the top 93 proteins (BC vs UC, Mann–Whitney p-value < 0.05, fold change > 2) elevated in BC urine. Hierarchical clustering was performed. Each row corresponds to the creatinine-normalized protein level measured, and each column represents a patient sample (UC = 15, BC Ta = 5, BC Tis = 4, BC T1 = 9, BC T2 = 4, BC T3 = 3, BC T4 = 2). Proteins that are above the mean value for each biomarker and shaded yellow. Those below the mean are shaded blue. Proteins comparable to the mean are shaded black. D Correlation plot displaying the expression profiles of the upregulated proteins in BC across the entire cohort. Pearson’s and Spearman’s correlation coefficients were determined for each pair. The proteins were ordered based on hierarchical clustering. Each circle represents the correlation for a protein pair. Blue corresponds to a positive correlation while red corresponds to a negative correlation. E Random forest analysis using the top 93 proteins (BC vs UC, Mann–Whitney p-value < 0.05, fold change > 2) identified the 10 most discriminatory urine proteins with the greatest impact on distinguishing BC subjects from urology controls. These 10 proteins are ordered by their GINI coefficient (importance in discrimination)