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. 2021 Oct 14;13(20):5143.
doi: 10.3390/cancers13205143.

A Systems Approach to Interrogate Gene Expression Patterns in African American Men Presenting with Clinically Localized Prostate Cancer

Gary Hardiman  1   2 , Stephen J Savage  3   4   5 , E Starr Hazard  6 , Willian A da Silveira  2 , Rebecca Morgan  2 , Adam Harris  2 , Melanie S Jefferson  7 , Robert C Wilson  8 , Susan Caulder  4 , Linda Ambrose  4 , Lewis Frey  9   10 , Bethany Wolf  10 , Sebastiano Gattoni-Celli  4   5 , Chanita Hughes Halbert  7   11   12   13
Affiliations

A Systems Approach to Interrogate Gene Expression Patterns in African American Men Presenting with Clinically Localized Prostate Cancer

Gary Hardiman et al. Cancers (Basel). .

Abstract

An emerging theory about racial differences in cancer risk and outcomes is that psychological and social stressors influence cellular stress responses; however, limited empirical data are available on racial differences in cellular stress responses among men who are at risk for adverse prostate cancer outcomes. In this study, we undertook a systems approach to examine molecular profiles and cellular stress responses in an important segment of African American (AA) and European American (EA) men: men undergoing prostate biopsy. We assessed the prostate transcriptome with a single biopsy core via high throughput RNA sequencing (RNA-Seq). Transcriptomic analyses uncovered impacted biological pathways including PI3K-Akt signaling pathway, Neuroactive ligand-receptor interaction pathway, and ECM-receptor interaction. Additionally, 187 genes mapping to the Gene Ontology (GO) terms RNA binding, structural constituent of ribosome, SRP-dependent co-translational protein targeting to membrane and the biological pathways, translation, L13a-mediated translational silencing of Ceruloplasmin expression were differentially expressed (DE) between EA and AA. This signature allowed separation of AA and EA patients, and AA patients with the most severe clinical characteristics. AA patients with elevated expression levels of this genomic signature presented with higher Gleason scores, a greater number of positive core biopsies, elevated dehydroepiandrosterone sulfate levels and serum vitamin D deficiency. Protein-protein interaction (PPI) network analysis revealed a high degree of connectivity between these 187 proteins.

Keywords: African American; RNA-Seq; health disparities; precision medicine; prostate; stress; transcriptomics; vitamin D.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
Power analysis plots with power as a function of the co-efficient of variation (CV), using (A): 27 and (B): 32 replicates respectively to detect FC values ranging from 2.0 to 3.0. Type I error rate is conservatively fixed at α = 2.5 × 10−6 (α = 0.05 after Bonferroni Correction). (C) MA Plot examining differential gene expression between EA and AA men. The plot visualizes the differences between measurements taken in two samples, by transforming the data onto M (log ratio) and A (mean average) scale. M (Y-axis) is plots differential gene expression (log2 (EA/AA). A (X-axis) plots transcript abundance (0.5 log2 AA + 0.5 log2 EA). significant transcripts (q < 0.1) are highlighted in red. (D) Volcano plot depicting the DE genes in the contrast between AA and EA men. The horizontal axis is the log fold change, and the vertical axis is the negative base-10 logarithm of the adj p-value or q-value. The red-dotted lines represent the threshold. The up-regulated genes (positive log fold change) are shown in red, while the down-regulated genes are blue. AA: African–American; EA: European–American.
Figure 2
Figure 2
Heat map of gene expression changes by race. Red and blue boxes depict relative over- and under-expression with regard to a reference set as the mid-point between all patients. Only significant transcripts (q < 0.1) are shown. AA: African–American; EA: European–American.
Figure 3
Figure 3
PI3K-Akt signaling pathway (KEGG: 04151) pathway genes showing gene regulation based on EA vs. AA prostate DE analysis (EA is control, AA is test). RED: upregulated, BLUE: downregulated.
Figure 4
Figure 4
Neuroactive ligand-receptor interaction pathway (KEGG: 04080) showing gene regulation based on EA vs. AA prostate DE analysis (EA is control, AA is test). RED: upregulated, BLUE: downregulated.
Figure 5
Figure 5
ECM-receptor interaction (KEGG: 04512) DE pathway genes based on EA vs. AA prostate DE analysis (EA is control, AA is test). RED: upregulated, BLUE: downregulated.
Figure 6
Figure 6
Heat map of gene expression changes in EA men compared with AA men for transcripts that map to the co-expression signature ‘Genes up-regulated in prostate cancer samples’. Red and blue boxes depict relative over- and under-expression with regard to a reference set as the mid-point all patients. Only significant transcripts (q < 0.1) are shown.
Figure 7
Figure 7
Heatmap of the 187 shared gene signatures derived from the GO terms RNA binding, structural constituent of ribosome, SRP-dependent co-translational protein targeting to membrane and the biological pathways translation, L13a-mediated translational silencing of Ceruloplasmin expression. Red and blue boxes depict relative over- and under-expression with regard to a reference set as the mid-point between all patients. Only significant transcripts (q < 0.1) are shown. A cluster of five AA patients is visible at the extreme left of the heatmap.
Figure 8
Figure 8
Interaction network of 187 signature genes using The Search Tool for Retrieval of Interacting Genes/Proteins (STRING) Protein-protein interaction (PPI) database. A node represents an individual protein and the edge connecting two nodes represents the relationship between them, i.e., they represent interacting proteins. Nodes with significantly higher degree than other nodes within a system are hub nodes. The nodal color reflects direction and size of regulation in AA men compared to EA men as defined by fold-change values from the experiment. Nodes with no interactions are excluded from the visualization.
Figure 9
Figure 9
Sparse principal component analysis. Scatter plots of principal component 1 by component 2 from the sparse principal component analysis. (A) denotes values of these components by cancer status (red = cancer, black = benign). (B) denotes the 5 extreme patients identified by the heat map (Figure 7) in red versus all others in black. The blue rectangle in both plots highlights these five patients.
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