Androgen deprivation therapy promotes an obesity-like microenvironment in periprostatic fat

Figures

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  Figure 1. Probabilistic Bayesian inference model. The parameter α represents the rates of change of each cell type category along the biological conditions. The parameter π represents the matrix of proportions for each cell type category and sample. The parameters σ, φ and δ define the noise model. The point estimate and credible intervals for both cell type proportions and trends of change are calculated from the posterior distribution.

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  Figure 2. (A) Heatmap of the top differentially regulated genes, with unsupervised hierarchical clustering for samples and genes. (B) Multidimensional scaling (MDS) plot of the treated and naïve cohorts before and after removal of the unwanted variation (K = 1). (C) Smear plot indicating the differentially transcribed genes in red. (D) Recurrent functional groups within the differentially transcribed genes.

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  Figure 3. Differential tissue composition analysis. (A) Polar plot representing the overall cell type abundance (i.e. radius dimension) and the significant associations with androgen deprivation therapy (i.e. white for non-significant associations). Cell types are labelled if more abundant than 1%. CI = 95% credible interval of the association. (B) Boxplots of the inferred cell type proportions by our Bayesian probabilistic model and Cibersort, for the cell types that correspond or are part of significantly differentially abundant cell type categories (e.g. the differentially abundant category ‘granulocytes’ include eosinophils and neutrophils) between the two treatment categories (i.e., treated and naïve) according to our model. FDR = false discovery rate linked to an association being different non null.

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  Figure 4. GSEA enrichment plot showing the significant enrichment of the obesity signature among the most differentially transcribed genes.