Comparative Genomics Reveals Distinct Immune-oncologic Pathways in African American Men with Prostate Cancer

Abstract

Purpose: The role of immune-oncologic mechanisms of racial disparities in prostate cancer remains understudied. Limited research exists to evaluate the molecular underpinnings of immune differences in African American men (AAM) and European American men (EAM) prostate tumor microenvironment (TME).

Experimental design: A total of 1,173 radiation-naïve radical prostatectomy samples with whole transcriptome data from the Decipher GRID registry were used. Transcriptomic expressions of 1,260 immune-specific genes were selected to assess immune-oncologic differences between AAM and EAM prostate tumors. Race-specific differential expression of genes was assessed using a rank test, and intergene correlational matrix and gene set enrichment was used for pathway analysis.

Results: AAM prostate tumors have significant enrichment of major immune-oncologic pathways, including proinflammatory cytokines, IFNα, IFNγ, TNFα signaling, ILs, and epithelial-mesenchymal transition. AAM TME has higher total immune content score (ICSHIGH) compared with 0 (37.8% vs. 21.9%, P = 0.003). AAM tumors also have lower DNA damage repair and are genomically radiosensitive as compared with EAM. IFITM3 (IFN-inducible transmembrane protein 3) was one of the major proinflammatory genes overexpressed in AAM that predicted increased risk of biochemical recurrence selectively for AAM in both discovery [HRAAM = 2.30; 95% confidence interval (CI), 1.21-4.34; P = 0.01] and validation (HRAAM = 2.42; 95% CI, 1.52-3.86; P = 0.0001) but not in EAM.

Conclusions: Prostate tumors of AAM manifest a unique immune repertoire and have significant enrichment of proinflammatory immune pathways that are associated with poorer outcomes. Observed immune-oncologic differences can aid in a genomically adaptive approach to treating prostate cancer in AAM.

©2020 American Association for Cancer Research.

Figures

Figure 1.

CONSORT diagram of genomic exploration within discovery, validation (DVAHS), and TCGA datasets.

Figure 2.

A, Heatmap of the intergene correlation of 38 validated genes in discovery and DVAHS validation datasets. Using hierarchical clustering, a correlation cluster of the genes was consistently observed for AAM in both the datasets (highlighted in red). B, GSEA on 38 validated genes using Reactome and Hallmark cancer pathways. C, Expression box plot for 26 genes enriched within major immune-oncologic pathways from discovery dataset. For DVAHS validation and TCGA datasets, only significance value is shown. Direction of the genes was consistently preserved across all the datasets. Significance value ****, P < 0.0001; ***, P < 0.001; **, P < 0.01; *, P < 0.05.

Figure 3.

Survival analysis. A, Estimates of HRs and 95% CI for the risk of BCR by linear expression of IFITM3, IFI6, ANPEP, CD38, MT2A, and IFI44L in discovery dataset within AAM and EAM. Higher expression of IFITM3 (indicated in bold and italics) selectively associated with the risk of BCR only among AAM. HR estimates were derived from the Cox model using the CAPRA-S matched discovery dataset and did not include other covariates in the model. B, Estimates of HRs and 95% CI for the risk of BCR by linear expression of IFITM3, IFI6, ANPEP, CD38, MT2A, and IFI44L in DVAHS validation dataset within AAM and EAM. Higher expression of IFITM3 (indicated in bold and italics) selectively associated with the risk of BCR only among AAM. HR estimates were derived from CAPRA-S adjusted Cox model, to account for the underlying risk differences between race groups, using the DVAHS validation data.

Figure 4.

Differences in genomic signatures within AAM and EAM in discovery dataset. For DVAHS validation, only significance value is shown. For comparison, all the genomic signatures were uniformly scaled to positive values by adding a constant integer. Significance value ****, P < 0.0001; ***, P < 0.001; **, P < 0.01; *, P < 0.05; NS, not significant.

Figure 5.

Correlation of postoperative radiotherapy outcomes score (PORTOS, A), radiation sensitivity index (RSI, B), CD4+ (C), and Hallmark IFNγ (D) expression with hallmark DNA repair in discovery dataset.