Alterations in the Epigenetic Machinery Associated with Prostate Cancer Health Disparities

Abstract

Prostate cancer is driven by acquired genetic alterations, including those impacting the epigenetic machinery. With African ancestry as a significant risk factor for aggressive disease, we hypothesize that dysregulation among the roughly 656 epigenetic genes may contribute to prostate cancer health disparities. Investigating prostate tumor genomic data from 109 men of southern African and 56 men of European Australian ancestry, we found that African-derived tumors present with a longer tail of epigenetic driver gene candidates (72 versus 10). Biased towards African-specific drivers (63 versus 9 shared), many are novel to prostate cancer (18/63), including several putative therapeutic targets (CHD7, DPF3, POLR1B, SETD1B, UBTF, and VPS72). Through clustering of all variant types and copy number alterations, we describe two epigenetic PCa taxonomies capable of differentiating patients by ancestry and predicted clinical outcomes. We identified the top genes in African- and European-derived tumors representing a multifunctional "generic machinery", the alteration of which may be instrumental in epigenetic dysregulation and prostate tumorigenesis. In conclusion, numerous somatic alterations in the epigenetic machinery drive prostate carcinogenesis, but African-derived tumors appear to achieve this state with greater diversity among such alterations. The greater novelty observed in African-derived tumors illustrates the significant clinical benefit to be derived from a much needed African-tailored approach to prostate cancer healthcare aimed at reducing prostate cancer health disparities.

Keywords: African ancestry; epigenetic machinery; epigenomics; health disparity; prostate cancer; somatic alteration; southern Africa.

Figure 1

Somatic alteration landscape for each epigenetic process group. The top bar graph shows the number of non-synonymous variants and copy number alterations per tumor. The middle gene panel reports synonymous and non-synonymous variants in a maximum of 20 top altered genes. The bottom panels annotate sample ancestries and ISUP grades. The right-hand bar plots display European and African mutation frequencies, respectively. The left-hand panel indicates whether top genes identified in the oncoplot overlap with candidate cancer mutational drivers identified by the Pan Cancer Analysis of Whole Genomes and if so, whether the gene was identified as a candidate driver in prostate adenocarcinoma. Finally, the left-hand panel also indicates whether genes displayed in the oncoplot contain damaging variants, based on functional impact prediction, as described in Table 2. Yellow tiles indicate ‘yes’, grey tiles indicate ‘no’. Due to the hypermutated nature of these genes and their indirect epigenetic involvement in chromatin state regulation, the TP53, SPOP, and FOXA1 genes were excluded from the oncoplots. (A) Epigenetic process group 1; (B) epigenetic process group 2; (C) epigenetic process group 3; (D) epigenetic process group 4; (E) epigenetic process group 5. A, African; E, European; FS_Del, frameshift deletion; FS_Ins, frameshift insertion; In_Frame_Del, in-frame deletion; ISUP, International Society of Urologic Pathologists; PCAWG, Pan Cancer Analysis of Whole Genomes; Prost-AdenoCA, prostate adenocarcinoma.

Figure 1

Somatic alteration landscape for each epigenetic process group. The top bar graph shows the number of non-synonymous variants and copy number alterations per tumor. The middle gene panel reports synonymous and non-synonymous variants in a maximum of 20 top altered genes. The bottom panels annotate sample ancestries and ISUP grades. The right-hand bar plots display European and African mutation frequencies, respectively. The left-hand panel indicates whether top genes identified in the oncoplot overlap with candidate cancer mutational drivers identified by the Pan Cancer Analysis of Whole Genomes and if so, whether the gene was identified as a candidate driver in prostate adenocarcinoma. Finally, the left-hand panel also indicates whether genes displayed in the oncoplot contain damaging variants, based on functional impact prediction, as described in Table 2. Yellow tiles indicate ‘yes’, grey tiles indicate ‘no’. Due to the hypermutated nature of these genes and their indirect epigenetic involvement in chromatin state regulation, the TP53, SPOP, and FOXA1 genes were excluded from the oncoplots. (A) Epigenetic process group 1; (B) epigenetic process group 2; (C) epigenetic process group 3; (D) epigenetic process group 4; (E) epigenetic process group 5. A, African; E, European; FS_Del, frameshift deletion; FS_Ins, frameshift insertion; In_Frame_Del, in-frame deletion; ISUP, International Society of Urologic Pathologists; PCAWG, Pan Cancer Analysis of Whole Genomes; Prost-AdenoCA, prostate adenocarcinoma.

Figure 2

(A) Consensus clustering heatmap, based on 10 multi-omics integrative clustering algorithms, for somatic data (small variants, structural variation, and copy number alterations) spanning epigenetic machinery genes in 105 African- and 53 European-derived prostate tumors. For each variant data, the top five features are listed. Feature selection identifies complex cross-talk between different variant data, which may allude to biological significance driving cancer heterogeneity. (B) Hierarchical clustering heatmap, based only on somatic copy number alteration data spanning epigenetic machinery genes, for 105 African- and 53 European-derived prostate tumors. ECS, epigenetic cancer subtype; EcnCS, epigenetic copy number cancer subtype; GMS, global mutational subtype; ISUP, International Society of Urologic Pathologists; NA, not available.

Figure 3

Kaplan–Meier curves of consensus clustering results for European patients. The probability estimates, 95% confidence intervals, and p-values (log-rank test) are indicated. (A) Kaplan–Meier curve of biochemical relapse (BCR)-free probability for ECS1 (n = 34) and ECS3 (n = 13) tumors. (B) Kaplan–Meier curve of the cancer survival probability for ECS1 (n = 34) and ECS2 (n = 3) tumors. (C) Kaplan–Meier curve of BCR-free probability for EcnCS1 (n = 41) and EcnCS3 (n = 9) tumors. (D) Kaplan–Meier curve of BCR-free probability for EcnCS1 (n = 2) and EcnCS3 (n = 9) tumors allocated to GMS-C. BCR, biochemical relapse; ECS, epigenetic cancer subtype; EcnCS, epigenetic copy number cancer subtype; GMS, global mutational subtype.

Figure 4

Top epigenetic machinery genes in African and European-derived tumors, somatically altered per epigenetic process group, that may be instrumental in epigenetic dysregulation and consequent prostate cancer oncogenesis. The total number of genes in each epigenetic process group is also displayed. Top genes were selected based on iClusterBayes feature selection, with a posterior probability > 0.5, as well as the presence of potentially damaging variants based on functional impact prediction and/or recurrence. No top genes were identified for epigenetic process group 3. EPG, epigenetic process group.