The impact of telomere length on prostate cancer aggressiveness, genomic instability and health disparities.

The telomere repetitive TTAGGG motif at the ends of chromosomes, serves to preserve genomic integrity and chromosomal stability. In turn, genomic instability is a hallmark of cancer-implicating telomere disturbance. Prostate cancer (PCa) shows significant ancestral disparities, with men of African ancestry at the greatest risk for aggressive disease and associated genomic instability. Yet, no study has explored the role of telomere length (TL) with respect to ancestrally driven PCa health disparities. Patient- and technically-matched tumour-blood whole genome sequencing data for 179 ancestrally defined treatment naïve PCa patients (117 African, 62 European), we assessed for TL (blood and tumour) associations. We found shortened tumour TL to be associated with aggressive PCa presentation and elevated genomic instabilities, including percentage of genome alteration and copy number gains, in men of African ancestry. For European patients, tumour TL showed significant associations with PCa driver genes PTEN, TP53, MSH2, SETBP1 and DDX11L1, while shorter blood TL (< 3200 base pairs) and tumour TL (< 2861 base pairs) were correlated with higher risk for biochemical recurrence. Concurring with previous studies linking TL to PCa diagnosis and/or prognosis, for the first time we correlated TL differences with patient ancestry with important implications for future treatments targeting telomere dysfunction.

Prostate cancer genetic risk and associated aggressive disease in men of African ancestry.

African ancestry is a significant risk factor for prostate cancer and advanced disease. Yet, genetic studies have largely been conducted outside the context of Sub-Saharan Africa, identifying 278 common risk variants contributing to a multiethnic polygenic risk score, with rare variants focused on a panel of roughly 20 pathogenic genes. Based on this knowledge, we are unable to determine polygenic risk or differentiate prostate cancer status interrogating whole genome data for 113 Black South African men. To further assess for potentially functional common and rare variant associations, here we interrogate 247,780 exomic variants for 798 Black South African men using a case versus control or aggressive versus non-aggressive study design. Notable genes of interest include HCP5, RFX6 and H3C1 for risk, and MKI67 and KLF5 for aggressive disease. Our study highlights the need for further inclusion across the African diaspora to establish African-relevant risk models aimed at reducing prostate cancer health disparities.

Linking African ancestral substructure to prostate cancer health disparities.

Prostate cancer (PCa) is a significant health burden in Sub-Saharan Africa, with mortality rates loosely linked to African ancestry. Yet studies aimed at identifying contributing risk factors are lacking within the continent and as such exclude for significant ancestral diversity. Here, we investigate a series of epidemiological demographic and lifestyle risk factors for 1387 men recruited as part of the multi-ethnic Southern African Prostate Cancer Study (SAPCS). We found poverty to be a decisive factor for disease grade and age at diagnosis, with other notably significant PCa associated risk factors including sexually transmitted diseases, erectile dysfunction, gynaecomastia, and vertex or complete pattern balding. Aligned with African American data, Black ethnicity showed significant risk for PCa diagnosis (OR = 1.44, 95% CI 1.05-2.00), and aggressive disease presentation (ISUP ≥ 4: OR = 2.25, 95% CI 1.49-3.40). New to this study, we demonstrate African ancestral population substructure associated PCa disparity, observing increased risk for advanced disease for the southern African Tsonga people (ISUP ≥ 4: OR = 3.43, 95% CI 1.62-7.27). Conversely, South African Coloured were less likely to be diagnosed with aggressive disease overall (ISUP ≥ 3: OR = 0.38, 95% 0.17-0.85). Understanding the basis for PCa health disparities calls for African inclusion, however, lack of available data has limited the power to begin discussions. Here, focusing on arguably the largest study of its kind for the African continent, we draw attention to the contribution of within African ancestral diversity as a contributing factor to PCa health disparities within the genetically diverse region of southern Africa.

ANO7 African-ancestral genomic diversity and advanced prostate cancer.

BACKGROUND: Prostate cancer (PCa) is a significant health burden for African men, with mortality rates more than double global averages. The prostate specific Anoctamin 7 (ANO7) gene linked with poor patient outcomes has recently been identified as the target for an African-specific protein-truncating PCa-risk allele. METHODS: Here we determined the role of ANO7 in a study of 889 men from southern Africa, leveraging exomic genotyping array PCa case-control data (n = 780, 17 ANO7 alleles) and deep sequenced whole genome data for germline and tumour ANO7 interrogation (n = 109), while providing clinicopathologically matched European-derived sequence data comparative analyses (n = 57). Associated predicted deleterious variants (PDVs) were further assessed for impact using computational protein structure analysis. RESULTS: Notably rare in European patients, we found the common African PDV p.Ile740Leu (rs74804606) to be associated with PCa risk in our case-control analysis (Wilcoxon rank-sum test, false discovery rate/FDR = 0.03), while sequencing revealed co-occurrence with the recently reported African-specific deleterious risk variant p.Ser914* (rs60985508). Additional findings included a novel protein-truncating African-specific frameshift variant p.Asp789Leu, African-relevant PDVs associated with altered protein structure at Ca2+ binding sites, early-onset PCa associated with PDVs and germline structural variants in Africans (Linear regression models, -6.42 years, 95% CI = -10.68 to -2.16, P-value = 0.003) and ANO7 as an inter-chromosomal PCa-related gene fusion partner in African derived tumours. CONCLUSIONS: Here we provide not only validation for ANO7 as an African-relevant protein-altering PCa-risk locus, but additional evidence for a role of inherited and acquired ANO7 variance in the observed phenotypic heterogeneity and African-ancestral health disparity.

Alterations in the Epigenetic Machinery Associated with Prostate Cancer Health Disparities.

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.

The Australasian dingo archetype: de novo chromosome-length genome assembly, DNA methylome, and cranial morphology.

BACKGROUND: One difficulty in testing the hypothesis that the Australasian dingo is a functional intermediate between wild wolves and domesticated breed dogs is that there is no reference specimen. Here we link a high-quality de novo long-read chromosomal assembly with epigenetic footprints and morphology to describe the Alpine dingo female named Cooinda. It was critical to establish an Alpine dingo reference because this ecotype occurs throughout coastal eastern Australia where the first drawings and descriptions were completed. FINDINGS: We generated a high-quality chromosome-level reference genome assembly (Canfam_ADS) using a combination of Pacific Bioscience, Oxford Nanopore, 10X Genomics, Bionano, and Hi-C technologies. Compared to the previously published Desert dingo assembly, there are large structural rearrangements on chromosomes 11, 16, 25, and 26. Phylogenetic analyses of chromosomal data from Cooinda the Alpine dingo and 9 previously published de novo canine assemblies show dingoes are monophyletic and basal to domestic dogs. Network analyses show that the mitochondrial DNA genome clusters within the southeastern lineage, as expected for an Alpine dingo. Comparison of regulatory regions identified 2 differentially methylated regions within glucagon receptor GCGR and histone deacetylase HDAC4 genes that are unmethylated in the Alpine dingo genome but hypermethylated in the Desert dingo. Morphologic data, comprising geometric morphometric assessment of cranial morphology, place dingo Cooinda within population-level variation for Alpine dingoes. Magnetic resonance imaging of brain tissue shows she had a larger cranial capacity than a similar-sized domestic dog. CONCLUSIONS: These combined data support the hypothesis that the dingo Cooinda fits the spectrum of genetic and morphologic characteristics typical of the Alpine ecotype. We propose that she be considered the archetype specimen for future research investigating the evolutionary history, morphology, physiology, and ecology of dingoes. The female has been taxidermically prepared and is now at the Australian Museum, Sydney.

Evaluating Germline Testing Panels in Southern African Males With Advanced Prostate Cancer.

BACKGROUND: Germline testing for prostate cancer is on the increase, with clinical implications for risk assessment, treatment, and management. Regardless of family history, NCCN recommends germline testing for patients with metastatic, regional, very-high-risk localized, and high-risk localized prostate cancer. Although African ancestry is a significant risk factor for aggressive prostate cancer, due to a lack of available data no testing criteria have been established for ethnic minorities. PATIENTS AND METHODS: Through deep sequencing, we interrogated the 20 most common germline testing panel genes in 113 Black South African males presenting with largely advanced prostate cancer. Bioinformatic tools were then used to identify the pathogenicity of the variants. RESULTS: After we identified 39 predicted deleterious variants (16 genes), further computational annotation classified 17 variants as potentially oncogenic (12 genes; 17.7% of patients). Rare pathogenic variants included CHEK2 Arg95Ter, BRCA2 Trp31Arg, ATM Arg3047Ter (2 patients), and TP53 Arg282Trp. Notable oncogenic variants of unknown pathogenicity included novel BRCA2 Leu3038Ile in a patient with early-onset disease, whereas patients with FANCA Arg504Cys and RAD51C Arg260Gln reported a family history of prostate cancer. Overall, rare pathogenic and early-onset or familial-associated oncogenic variants were identified in 6.9% (5/72) and 9.2% (8/87) of patients presenting with a Gleason score ≥8 or ≥4 + 3 prostate cancer, respectively. CONCLUSIONS: In this first-of-its-kind study of southern African males, we provide support of African inclusion for advanced, early-onset, and familial prostate cancer genetic testing, indicating clinical value for 30% of current gene panels. Recognizing current panel limitations highlights an urgent need to establish testing guidelines for men of African ancestry. We provide a rationale for considering lowering the pathologic diagnostic inclusion criteria and call for further genome-wide interrogation to ensure the best possible African-relevant prostate cancer gene panel.

A review and comparative study of cancer detection using machine learning: SBERT and SimCSE application.

BACKGROUND: Using visual, biological, and electronic health records data as the sole input source, pretrained convolutional neural networks and conventional machine learning methods have been heavily employed for the identification of various malignancies. Initially, a series of preprocessing steps and image segmentation steps are performed to extract region of interest features from noisy features. Then, the extracted features are applied to several machine learning and deep learning methods for the detection of cancer. METHODS: In this work, a review of all the methods that have been applied to develop machine learning algorithms that detect cancer is provided. With more than 100 types of cancer, this study only examines research on the four most common and prevalent cancers worldwide: lung, breast, prostate, and colorectal cancer. Next, by using state-of-the-art sentence transformers namely: SBERT (2019) and the unsupervised SimCSE (2021), this study proposes a new methodology for detecting cancer. This method requires raw DNA sequences of matched tumor/normal pair as the only input. The learnt DNA representations retrieved from SBERT and SimCSE will then be sent to machine learning algorithms (XGBoost, Random Forest, LightGBM, and CNNs) for classification. As far as we are aware, SBERT and SimCSE transformers have not been applied to represent DNA sequences in cancer detection settings. RESULTS: The XGBoost model, which had the highest overall accuracy of 73 ± 0.13 % using SBERT embeddings and 75 ± 0.12 % using SimCSE embeddings, was the best performing classifier. In light of these findings, it can be concluded that incorporating sentence representations from SimCSE's sentence transformer only marginally improved the performance of machine learning models.

The Australasian dingo archetype: De novo chromosome-length genome assembly, DNA methylome, and cranial morphology.

Background: One difficulty in testing the hypothesis that the Australasian dingo is a functional intermediate between wild wolves and domesticated breed dogs is that there is no reference specimen. Here we link a high-quality de novo long read chromosomal assembly with epigenetic footprints and morphology to describe the Alpine dingo female named Cooinda. It was critical to establish an Alpine dingo reference because this ecotype occurs throughout coastal eastern Australia where the first drawings and descriptions were completed. Findings: We generated a high-quality chromosome-level reference genome assembly (Canfam_ADS) using a combination of Pacific Bioscience, Oxford Nanopore, 10X Genomics, Bionano, and Hi-C technologies. Compared to the previously published Desert dingo assembly, there are large structural rearrangements on Chromosomes 11, 16, 25 and 26. Phylogenetic analyses of chromosomal data from Cooinda the Alpine dingo and nine previously published de novo canine assemblies show dingoes are monophyletic and basal to domestic dogs. Network analyses show that the mtDNA genome clusters within the southeastern lineage, as expected for an Alpine dingo. Comparison of regulatory regions identified two differentially methylated regions within glucagon receptor GCGR and histone deacetylase HDAC4 genes that are unmethylated in the Alpine dingo genome but hypermethylated in the Desert dingo. Morphological data, comprising geometric morphometric assessment of cranial morphology place dingo Cooinda within population-level variation for Alpine dingoes. Magnetic resonance imaging of brain tissue show she had a larger cranial capacity than a similar-sized domestic dog. Conclusions: These combined data support the hypothesis that the dingo Cooinda fits the spectrum of genetic and morphological characteristics typical of the Alpine ecotype. We propose that she be considered the archetype specimen for future research investigating the evolutionary history, morphology, physiology, and ecology of dingoes. The female has been taxidermically prepared and is now at the Australian Museum, Sydney.

African-specific molecular taxonomy of prostate cancer.

Prostate cancer is characterized by considerable geo-ethnic disparity. African ancestry is a significant risk factor, with mortality rates across sub-Saharan Africa of 2.7-fold higher than global averages1. The contributing genetic and non-genetic factors, and associated mutational processes, are unknown2,3. Here, through whole-genome sequencing of treatment-naive prostate cancer samples from 183 ancestrally (African versus European) and globally distinct patients, we generate a large cancer genomics resource for sub-Saharan Africa, identifying around 2 million somatic variants. Significant African-ancestry-specific findings include an elevated tumour mutational burden, increased percentage of genome alteration, a greater number of predicted damaging mutations and a higher total of mutational signatures, and the driver genes NCOA2, STK19, DDX11L1, PCAT1 and SETBP1. Examining all somatic mutational types, we describe a molecular taxonomy for prostate cancer differentiated by ancestry and defined as global mutational subtypes (GMS). By further including Chinese Asian data, we confirm that GMS-B (copy-number gain) and GMS-D (mutationally noisy) are specific to African populations, GMS-A (mutationally quiet) is universal (all ethnicities) and the African-European-restricted subtype GMS-C (copy-number losses) predicts poor clinical outcomes. In addition to the clinical benefit of including individuals of African ancestry, our GMS subtypes reveal different evolutionary trajectories and mutational processes suggesting that both common genetic and environmental factors contribute to the disparity between ethnicities. Analogous to gene-environment interaction-defined here as a different effect of an environmental surrounding in people with different ancestries or vice versa-we anticipate that GMS subtypes act as a proxy for intrinsic and extrinsic mutational processes in cancers, promoting global inclusion in landmark studies.

Genome-wide interrogation of structural variation reveals novel African-specific prostate cancer oncogenic drivers.

BACKGROUND: African ancestry is a significant risk factor for advanced prostate cancer (PCa). Mortality rates in sub-Saharan Africa are 2.5-fold greater than global averages. However, the region has largely been excluded from the benefits of whole genome interrogation studies. Additionally, while structural variation (SV) is highly prevalent, PCa genomic studies are still biased towards small variant interrogation. METHODS: Using whole genome sequencing and best practice workflows, we performed a comprehensive analysis of SVs for 180 (predominantly Gleason score ≥ 8) prostate tumours derived from 115 African, 61 European and four ancestrally admixed patients. We investigated the landscape and relationship of somatic SVs in driving ethnic disparity (African versus European), with a focus on African men from southern Africa. RESULTS: Duplication events showed the greatest ethnic disparity, with a 1.6- (relative frequency) to 2.5-fold (count) increase in African-derived tumours. Furthermore, we found duplication events to be associated with CDK12 inactivation and MYC copy number gain, and deletion events associated with SPOP mutation. Overall, African-derived tumours were 2-fold more likely to present with a hyper-SV subtype. In addition to hyper-duplication and deletion subtypes, we describe a new hyper-translocation subtype. While we confirm a lower TMPRSS2-ERG fusion-positive rate in tumours from African cases (10% versus 33%), novel African-specific PCa ETS family member and TMPRSS2 fusion partners were identified, including LINC01525, FBXO7, GTF3C2, NTNG1 and YPEL5. Notably, we found 74 somatic SV hotspots impacting 18 new candidate driver genes, with CADM2, LSAMP, PTPRD, PDE4D and PACRG having therapeutic implications for African patients. CONCLUSIONS: In this first African-inclusive SV study for high-risk PCa, we demonstrate the power of SV interrogation for the identification of novel subtypes, oncogenic drivers and therapeutic targets. Identifying a novel spectrum of SVs in tumours derived from African patients provides a mechanism that may contribute, at least in part, to the observed ethnic disparity in advanced PCa presentation in men of African ancestry.

Rare Germline Variants Are Associated with Rapid Biochemical Recurrence After Radical Prostate Cancer Treatment: A Pan Prostate Cancer Group Study.

BACKGROUND: Germline variants explain more than a third of prostate cancer (PrCa) risk, but very few associations have been identified between heritable factors and clinical progression. OBJECTIVE: To find rare germline variants that predict time to biochemical recurrence (BCR) after radical treatment in men with PrCa and understand the genetic factors associated with such progression. DESIGN, SETTING, AND PARTICIPANTS: Whole-genome sequencing data from blood DNA were analysed for 850 PrCa patients with radical treatment from the Pan Prostate Cancer Group (PPCG) consortium from the UK, Canada, Germany, Australia, and France. Findings were validated using 383 patients from The Cancer Genome Atlas (TCGA) dataset. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: A total of 15,822 rare (MAF <1%) predicted-deleterious coding germline mutations were identified. Optimal multifactor and univariate Cox regression models were built to predict time to BCR after radical treatment, using germline variants grouped by functionally annotated gene sets. Models were tested for robustness using bootstrap resampling. RESULTS AND LIMITATIONS: Optimal Cox regression multifactor models showed that rare predicted-deleterious germline variants in "Hallmark" gene sets were consistently associated with altered time to BCR. Three gene sets had a statistically significant association with risk-elevated outcome when modelling all samples: PI3K/AKT/mTOR, Inflammatory response, and KRAS signalling (up). PI3K/AKT/mTOR and KRAS signalling (up) were also associated among patients with higher-grade cancer, as were Pancreas-beta cells, TNFA signalling via NKFB, and Hypoxia, the latter of which was validated in the independent TCGA dataset. CONCLUSIONS: We demonstrate for the first time that rare deleterious coding germline variants robustly associate with time to BCR after radical treatment, including cohort-independent validation. Our findings suggest that germline testing at diagnosis could aid clinical decisions by stratifying patients for differential clinical management. PATIENT SUMMARY: Prostate cancer patients with particular genetic mutations have a higher chance of relapsing after initial radical treatment, potentially providing opportunities to identify patients who might need additional treatments earlier.

Discriminatory Gleason grade group signatures of prostate cancer: An application of machine learning methods.

One of the most precise methods to detect prostate cancer is by evaluation of a stained biopsy by a pathologist under a microscope. Regions of the tissue are assessed and graded according to the observed histological pattern. However, this is not only laborious, but also relies on the experience of the pathologist and tends to suffer from the lack of reproducibility of biopsy outcomes across pathologists. As a result, computational approaches are being sought and machine learning has been gaining momentum in the prediction of the Gleason grade group. To date, machine learning literature has addressed this problem by using features from magnetic resonance imaging images, whole slide images, tissue microarrays, gene expression data, and clinical features. However, there is a gap with regards to predicting the Gleason grade group using DNA sequences as the only input source to the machine learning models. In this work, using whole genome sequence data from South African prostate cancer patients, an application of machine learning and biological experiments were combined to understand the challenges that are associated with the prediction of the Gleason grade group. A series of machine learning binary classifiers (XGBoost, LSTM, GRU, LR, RF) were created only relying on DNA sequences input features. All the models were not able to adequately discriminate between the DNA sequences of the studied Gleason grade groups (Gleason grade group 1 and 5). However, the models were further evaluated in the prediction of tumor DNA sequences from matched-normal DNA sequences, given DNA sequences as the only input source. In this new problem, the models performed acceptably better than before with the XGBoost model achieving the highest accuracy of 74 ± 01, F1 score of 79 ± 01, recall of 99 ± 0.0, and precision of 66 ± 0.1.

DNA methylation profiles unique to Kalahari KhoeSan individuals.

Genomes of KhoeSan individuals of the Kalahari Desert provide the greatest understanding of single nucleotide diversity in the human genome. Compared with individuals in industrialized environments, the KhoeSan have a unique foraging and hunting lifestyle. Given these dramatic environmental differences, and the responsiveness of the methylome to environmental exposures of many types, we hypothesized that DNA methylation patterns would differ between KhoeSan and neighbouring agropastoral and/or industrial Bantu. We analysed Illumina HumanMethylation 450 k array data generated from blood samples from 38 KhoeSan and 42 Bantu, and 6 Europeans. After removing CpG positions associated with annotated and novel polymorphisms and controlling for white blood cell composition, sex, age and technical variation we identified 816 differentially methylated CpG loci, out of which 133 had an absolute beta-value difference of at least 0.05. Notably SLC39A4/ZIP4, which plays a role in zinc transport, was one of the most differentially methylated loci. Although the chronological ages of the KhoeSan are not formally recorded, we compared historically estimated ages to methylation-based calculations. This study demonstrates that the epigenetic profile of KhoeSan individuals reveals differences from other populations, and along with extensive genetic diversity, this community brings increased accessibility and understanding to the diversity of the human genome.

Detection of somatic structural variants from short-read next-generation sequencing data.

Somatic structural variants (SVs), which are variants that typically impact >50 nucleotides, play a significant role in cancer development and evolution but are notoriously more difficult to detect than small variants from short-read next-generation sequencing (NGS) data. This is due to a combination of challenges attributed to the purity of tumour samples, tumour heterogeneity, limitations of short-read information from NGS and sequence alignment ambiguities. In spite of active development of SV detection tools (callers) over the past few years, each method has inherent advantages and limitations. In this review, we highlight some of the important factors affecting somatic SV detection and compared the performance of seven commonly used SV callers. In particular, we focus on the extent of change in sensitivity and precision for detecting different SV types and size ranges from samples with differing variant allele frequencies and sequencing depths of coverage. We highlight the reasons for why some SV callers perform well in some settings but not others, allowing our evaluation findings to be extended beyond the seven SV callers examined in this paper. As the importance of large SVs become increasingly recognized in cancer genomics, this paper provides a timely review on some of the most impactful factors influencing somatic SV detection that should be considered when choosing SV callers.

Shiny-SoSV: A web-based performance calculator for somatic structural variant detection.

Somatic structural variants are an important contributor to cancer development and evolution. Accurate detection of these complex variants from whole genome sequencing data is influenced by a multitude of parameters. However, there are currently no tools for guiding study design nor are there applications that could predict the performance of somatic structural variant detection. To address this gap, we developed Shiny-SoSV, a user-friendly web-based calculator for determining the impact of common variables on the sensitivity, precision and F1 score of somatic structural variant detection, including choice of variant detection tool, sequencing depth of coverage, variant allele fraction, and variant breakpoint resolution. Using simulation studies, we determined singular and combinatoric effects of these variables, modelled the results using a generalised additive model, allowing structural variant detection performance to be predicted for any combination of predictors. Shiny-SoSV provides an interactive and visual platform for users to easily compare individual and combined impact of different parameters. It predicts the performance of a proposed study design, on somatic structural variant detection, prior to the commencement of benchwork. Shiny-SoSV is freely available at https://hcpcg.shinyapps.io/Shiny-SoSV with accompanying user's guide and example use-cases.