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All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been o

Normal tissues adjacent to the tumor (NATs) may harbor early breast carcinogenesis events driven by field cancerization. Although previous studies have characterized copy-number (CN) and transcriptomic alterations, the evolutionary history of NATs in breast cancer (BC) remains poorly characterized. Utilizing whole-genome sequencing (WGS), methylation profiling, and RNA sequencing (RNA-seq), we analyzed paired germline, NATs, and tumor samples from 43 individuals with BC in Hong Kong (HK). We found that single-nucleotide variants (SNVs) were common in NATs, with one-third of NAT samples exhibiting SNVs in driver genes, many of which were present in paired tumor samples. The most frequently mutated genes in both tumor and NAT samples were PIK3CA, TP53, GATA3, and AKT1. In contrast, large-scale aberrations such as somatic CN alterations (SCNAs) and structural variants (SVs) were rarely detected in NAT samples. We generated phylogenetic trees to investigate the evolutionary history of paired NAT and tumor samples. They could be categorized into tumor only, shared, and multiple-tree groups, the last of which is concordant with non-genetic field cancerization. These groups exhibited distinct genomic and epigenomic characteristics in both NAT and tumor samples. Specifically, NAT samples in the shared-tree group showed higher number of mutations, while NAT samples belonging to the multiple-tree group showed a less inflammatory tumor microenvironment (TME), characterized by a higher proportion of regulatory T cells (Tregs) and lower presence of CD14 cell populations. In summary, our findings highlight the diverse evolutionary history in BC NAT/tumor pairs and the impact of field cancerization and TME in shaping the genomic evolutionary history of tumors., Competing Interests: Declaration of interests Authors have no competing interests to disclose., (Published by Elsevier Inc.)

Testicular germ cell tumours (TGCT), which comprise seminoma and non-seminoma subtypes, are the most common cancers in young men. In this study, we present a comprehensive whole genome sequencing analysis of adult TGCTs. Leveraging samples from participants recruited via the UK National Health Service and data from the Genomics England 100,000 Genomes Project, our results provide an extended description of genomic elements underlying TGCT pathogenesis. This catalogue offers a comprehensive, high-resolution map of copy number alterations, structural variation, and key global genome features, including mutational signatures and analysis of extrachromosomal DNA amplification. This study establishes correlations between genomic alterations and histological diversification, revealing divergent evolutionary trajectories among TGCT subtypes. By reconstructing the chronological order of driver events, we identify a subgroup of adult TGCTs undergoing relatively late whole genome duplication. Additionally, we present evidence that human leukocyte antigen loss is a more prevalent mechanism of immune disruption in seminomas. Collectively, our findings provide valuable insights into the developmental and immune modulatory processes implicated in TGCT pathogenesis and progression., (© 2024. The Author(s).)

Colorectal carcinoma (CRC) is a common cause of mortality 1 , but a comprehensive description of its genomic landscape is lacking 2-9 . Here we perform whole-genome sequencing of 2,023 CRC samples from participants in the UK 100,000 Genomes Project, thereby providing a highly detailed somatic mutational landscape of this cancer. Integrated analyses identify more than 250 putative CRC driver genes, many not previously implicated in CRC or other cancers, including several recurrent changes outside the coding genome. We extend the molecular pathways involved in CRC development, define four new common subgroups of microsatellite-stable CRC based on genomic features and show that these groups have independent prognostic associations. We also characterize several rare molecular CRC subgroups, some with potential clinical relevance, including cancers with both microsatellite and chromosomal instability. We demonstrate a spectrum of mutational profiles across the colorectum, which reflect aetiological differences. These include the role of Escherichia coli pks+ colibactin in rectal cancers 10 and the importance of the SBS93 signature 11-13 , which suggests that diet or smoking is a risk factor. Immune-escape driver mutations 14 are near-ubiquitous in hypermutant tumours and occur in about half of microsatellite-stable CRCs, often in the form of HLA copy number changes. Many driver mutations are actionable, including those associated with rare subgroups (for example, BRCA1 and IDH1), highlighting the role of whole-genome sequencing in optimizing patient care., (© 2024. The Author(s).)

Subclonal reconstruction algorithms use bulk DNA sequencing data to quantify parameters of tumor evolution, allowing an assessment of how cancers initiate, progress and respond to selective pressures. We launched the ICGC-TCGA (International Cancer Genome Consortium-The Cancer Genome Atlas) DREAM Somatic Mutation Calling Tumor Heterogeneity and Evolution Challenge to benchmark existing subclonal reconstruction algorithms. This 7-year community effort used cloud computing to benchmark 31 subclonal reconstruction algorithms on 51 simulated tumors. Algorithms were scored on seven independent tasks, leading to 12,061 total runs. Algorithm choice influenced performance substantially more than tumor features but purity-adjusted read depth, copy-number state and read mappability were associated with the performance of most algorithms on most tasks. No single algorithm was a top performer for all seven tasks and existing ensemble strategies were unable to outperform the best individual methods, highlighting a key research need. All containerized methods, evaluation code and datasets are available to support further assessment of the determinants of subclonal reconstruction accuracy and development of improved methods to understand tumor evolution., (© 2024. The Author(s).)

Motivation: Few methods exist for timing individual amplification events in regions of focal amplification. Current methods are also limited in the copy number states that they are able to time. Here we introduce AmplificationTimeR, a method for timing higher level copy number gains and inferring the most parsimonious order of events for regions that have undergone both single gains and whole genome duplication. Our method is an extension of established approaches for timing genomic gains., Results: We can time more copy number states, and in states covered by other methods our results are comparable to previously published methods., Availability and Implementation: AmplificationTimer is freely available as an R package hosted at https://github.com/Wedge-lab/AmplificationTimeR., (© The Author(s) 2024. Published by Oxford University Press.)

Myeloid cells are highly prevalent in glioblastoma (GBM), existing in a spectrum of phenotypic and activation states. We now have limited knowledge of the tumor microenvironment (TME) determinants that influence the localization and the functions of the diverse myeloid cell populations in GBM. Here, we have utilized orthogonal imaging mass cytometry with single-cell and spatial transcriptomic approaches to identify and map the various myeloid populations in the human GBM tumor microenvironment (TME). Our results show that different myeloid populations have distinct and reproducible compartmentalization patterns in the GBM TME that is driven by tissue hypoxia, regional chemokine signaling, and varied homotypic and heterotypic cellular interactions. We subsequently identified specific tumor subregions in GBM, based on composition of identified myeloid cell populations, that were linked to patient survival. Our results provide insight into the spatial organization of myeloid cell subpopulations in GBM, and how this is predictive of clinical outcome.

The development of cancer is an evolutionary process involving the sequential acquisition of genetic alterations that disrupt normal biological processes, enabling tumor cells to rapidly proliferate and eventually invade and metastasize to other tissues. We investigated the genomic evolution of prostate cancer through the application of three separate classification methods, each designed to investigate a different aspect of tumor evolution. Integrating the results revealed the existence of two distinct types of prostate cancer that arise from divergent evolutionary trajectories, designated as the Canonical and Alternative evolutionary disease types. We therefore propose the evotype model for prostate cancer evolution wherein Alternative-evotype tumors diverge from those of the Canonical-evotype through the stochastic accumulation of genetic alterations associated with disruptions to androgen receptor DNA binding. Our model unifies many previous molecular observations, providing a powerful new framework to investigate prostate cancer disease progression., Competing Interests: Declaration of interests An international patent related to this work has been published under international publication no. WO 2023/047140 A1. R.A.E. has the following conflicts of interest to declare: she has received honoraria from GU-ASCO, Janssen, The University of Chicago, and Dana-Farber Cancer Institute USA as a speaker and educational honorarium from Bayer and Ipsen and is a member of the external expert committee to Astra Zeneca UK. She undertakes private practice as a sole trader at The Royal Marsden NHS Foundation Trust and 90 Sloane Street SW1X 9PQ and 280 Kings Road SW3 4NX, London, UK., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Extension of prostate cancer beyond the primary site by local invasion or nodal metastasis is associated with poor prognosis. Despite significant research on tumour evolution in prostate cancer metastasis, the emergence and evolution of cancer clones at this early stage of expansion and spread are poorly understood. We aimed to delineate the routes of evolution and cancer spread within the prostate and to seminal vesicles and lymph nodes, linking these to histological features that are used in diagnostic risk stratification., Methods: We performed whole-genome sequencing on 42 prostate cancer samples from the prostate, seminal vesicles and lymph nodes of five treatment-naive patients with locally advanced disease. We spatially mapped the clonal composition of cancer across the prostate and the routes of spread of cancer cells within the prostate and to seminal vesicles and lymph nodes in each individual by analysing a total of > 19,000 copy number corrected single nucleotide variants., Results: In each patient, we identified sample locations corresponding to the earliest part of the malignancy. In patient 10, we mapped the spread of cancer from the apex of the prostate to the seminal vesicles and identified specific genomic changes associated with the transformation of adenocarcinoma to amphicrine morphology during this spread. Furthermore, we show that the lymph node metastases in this patient arose from specific cancer clones found at the base of the prostate and the seminal vesicles. In patient 15, we observed increased mutational burden, altered mutational signatures and histological changes associated with whole genome duplication. In all patients in whom histological heterogeneity was observed (4/5), we found that the distinct morphologies were located on separate branches of their respective evolutionary trees., Conclusions: Our results link histological transformation with specific genomic alterations and phylogenetic branching. These findings have implications for diagnosis and risk stratification, in addition to providing a rationale for further studies to characterise the genetic changes causally linked to morphological transformation. Our study demonstrates the value of integrating multi-region sequencing with histopathological data to understand tumour evolution and identify mechanisms of prostate cancer spread., (© 2024. The Author(s).)

Background: Prostate cancer (PrCa) genomic heterogeneity causes resistance to therapies such as androgen deprivation. Such heterogeneity can be deciphered in the context of evolutionary principles, but current clinical trials do not include evolution as an essential feature. Whether or not analysis of genomic data in an evolutionary context in primary prostate cancer can provide unique added value in the research and clinical domains remains an open question., Methods: We used novel processing techniques to obtain whole genome data together with 3D anatomic and histomorphologic analysis in two men (GP5 and GP12) with high-risk PrCa undergoing radical prostatectomy. A total of 22 whole genome-sequenced sites (16 primary cancer foci and 6 lymph node metastatic) were analyzed using evolutionary reconstruction tools and spatio-evolutionary models. Probability models were used to trace spatial and chronological origins of the primary tumor and metastases, chart their genetic drivers, and distinguish metastatic and non-metastatic subclones., Results: In patient GP5, CDK12 inactivation was among the first mutations, leading to a PrCa tandem duplicator phenotype and initiating the cancer around age 50, followed by rapid cancer evolution after age 57, and metastasis around age 59, 5 years prior to prostatectomy. In patient GP12, accelerated cancer progression was detected after age 54, and metastasis occurred around age 56, 3 years prior to prostatectomy. Multiple metastasis-originating events were identified in each patient and tracked anatomically. Metastasis from prostate to lymph nodes occurred strictly ipsilaterally in all 12 detected events. In this pilot, metastatic subclone content analysis appears to substantially enhance the identification of key drivers. Evolutionary analysis' potential impact on therapy selection appears positive in these pilot cases., Conclusions: PrCa evolutionary analysis allows tracking of anatomic site of origin, timing of cancer origin and spread, and distinction of metastatic-capable from non-metastatic subclones. This enables better identification of actionable targets for therapy. If extended to larger cohorts, it appears likely that similar analyses could add substantial biological insight and clinically relevant value., (© 2023. BioMed Central Ltd., part of Springer Nature.)

The hallmark signatures based on gene expression capture core cancer processes. Through a pan-cancer analysis, we describe the overview of hallmark signatures across tumor types/subtypes and reveal significant relationships between these signatures and genetic alterations. TP53 mutation exerts diverse changes, including increased proliferation and glycolysis, which are closely mimicked by widespread copy-number alterations. Hallmark signature and copy-number clustering identify a cluster of squamous tumors and basal-like breast and bladder cancers with elevated proliferation signatures, frequent TP53 mutation, and high aneuploidy. In these basal-like/squamous TP53 -mutated tumors, a specific and consistent spectrum of copy-number alterations is preferentially selected prior to whole-genome duplication. Within Trp53- null breast cancer mouse models, these copy-number alterations spontaneously occur and recapitulate the hallmark signature changes observed in the human condition. Together, our analysis reveals intertumor and intratumor heterogeneity of the hallmark signatures, uncovering an oncogenic program induced by TP53 mutation and select aneuploidy events to drive a worsened prognosis., Significance: Our data demonstrate that TP53 mutation and a resultant selected pattern of aneuploidies cause an aggressive transcriptional program including upregulation of glycolysis signature with prognostic implications. Importantly, basal-like breast cancer demonstrates genetic and/or phenotypic changes closely related to squamous tumors including 5q deletion that reveal alterations that could offer therapeutic options across tumor types regardless of tissue of origin., (© 2023 The Authors; Published by the American Association for Cancer Research.)

Mutational signature analysis is commonly performed in cancer genomic studies. Here, we present SigProfilerExtractor, an automated tool for de novo extraction of mutational signatures, and benchmark it against another 13 bioinformatics tools by using 34 scenarios encompassing 2,500 simulated signatures found in 60,000 synthetic genomes and 20,000 synthetic exomes. For simulations with 5% noise, reflecting high-quality datasets, SigProfilerExtractor outperforms other approaches by elucidating between 20% and 50% more true-positive signatures while yielding 5-fold less false-positive signatures. Applying SigProfilerExtractor to 4,643 whole-genome- and 19,184 whole-exome-sequenced cancers reveals four novel signatures. Two of the signatures are confirmed in independent cohorts, and one of these signatures is associated with tobacco smoking. In summary, this report provides a reference tool for analysis of mutational signatures, a comprehensive benchmarking of bioinformatics tools for extracting signatures, and several novel mutational signatures, including one putatively attributed to direct tobacco smoking mutagenesis in bladder tissues., Competing Interests: M.V. is an employee of NVIDIA corporation. L.B.A. is a compensated consultant and has equity interest in io9, LLC. His spouse is an employee of Biotheranostics, Inc. L.B.A. and B.S.A. are inventors of a US patent 10,776,718. E.N.B. and L.B.A. declare US provisional applications with serial numbers 63/289,601 and 63/269,033. L.B.A. and A.A. declare US provisional patent applications with serial numbers 63/366,392 and 63/367,846. All other authors declare no competing interests., (© 2022 The Author(s).)

Background: Up to 80% of cases of prostate cancer present with multifocal independent tumour lesions leading to the concept of a field effect present in the normal prostate predisposing to cancer development. In the present study we applied Whole Genome DNA Sequencing (WGS) to a group of morphologically normal tissue (n = 51), including benign prostatic hyperplasia (BPH) and non-BPH samples, from men with and men without prostate cancer. We assess whether the observed genetic changes in morphologically normal tissue are linked to the development of cancer in the prostate., Results: Single nucleotide variants (P = 7.0 × 10 -03 , Wilcoxon rank sum test) and small insertions and deletions (indels, P = 8.7 × 10 -06 ) were significantly higher in morphologically normal samples, including BPH, from men with prostate cancer compared to those without. The presence of subclonal expansions under selective pressure, supported by a high level of mutations, were significantly associated with samples from men with prostate cancer (P = 0.035, Fisher exact test). The clonal cell fraction of normal clones was always higher than the proportion of the prostate estimated as epithelial (P = 5.94 × 10 -05 , paired Wilcoxon signed rank test) which, along with analysis of primary fibroblasts prepared from BPH specimens, suggests a stromal origin. Constructed phylogenies revealed lineages associated with benign tissue that were completely distinct from adjacent tumour clones, but a common lineage between BPH and non-BPH morphologically normal tissues was often observed. Compared to tumours, normal samples have significantly less single nucleotide variants (P = 3.72 × 10 -09 , paired Wilcoxon signed rank test), have very few rearrangements and a complete lack of copy number alterations., Conclusions: Cells within regions of morphologically normal tissue (both BPH and non-BPH) can expand under selective pressure by mechanisms that are distinct from those occurring in adjacent cancer, but that are allied to the presence of cancer. Expansions, which are probably stromal in origin, are characterised by lack of recurrent driver mutations, by almost complete absence of structural variants/copy number alterations, and mutational processes similar to malignant tissue. Our findings have implications for treatment (focal therapy) and early detection approaches., (© 2022. The Author(s).)

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 averages 1 . The contributing genetic and non-genetic factors, and associated mutational processes, are unknown 2,3 . 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., (© 2022. Crown.)

Germ cell tumours (GCTs) are a collection of benign and malignant neoplasms derived from primordial germ cells. They are uniquely able to recapitulate embryonic and extraembryonic tissues, which carries prognostic and therapeutic significance. The developmental pathways underpinning GCT initiation and histogenesis are incompletely understood. Here, we study the relationship of histogenesis and clonal diversification in GCTs by analysing the genomes and transcriptomes of 547 microdissected histological units. We find no correlation between genomic and histological heterogeneity. However, we identify unifying features including the retention of fetal developmental transcripts across tissues, expression changes on chromosome 12p, and a conserved somatic evolutionary sequence of whole genome duplication followed by clonal diversification. While this pattern is preserved across all GCTs, the developmental timing of the duplication varies between prepubertal and postpubertal cases. In addition, tumours of younger children exhibit distinct substitution signatures which may lend themselves as potential biomarkers for risk stratification. Our findings portray the extensive diversification of GCT tissues and genetic subclones as randomly distributed, while identifying overarching transcriptional and genomic features., (© 2022. Crown.)

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., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Bacteria play a suspected role in the development of several cancer types, and associations between the presence of particular bacteria and prostate cancer have been reported., Objective: To provide improved characterisation of the prostate and urine microbiome and to investigate the prognostic potential of the bacteria present., Design, Setting, and Participants: Microbiome profiles were interrogated in sample collections of patient urine (sediment microscopy: n = 318, 16S ribosomal amplicon sequencing: n = 46; and extracellular vesicle RNA-seq: n = 40) and cancer tissue (n = 204)., Outcome Measurements and Statistical Analysis: Microbiomes were assessed using anaerobic culture, population-level 16S analysis, RNA-seq, and whole genome DNA sequencing., Results and Limitations: We demonstrate an association between the presence of bacteria in urine sediments and higher D'Amico risk prostate cancer (discovery, n = 215 patients, p < 0.001; validation, n = 103, p < 0.001, χ 2 test for trend). Characterisation of the bacterial community led to the (1) identification of four novel bacteria (Porphyromonas sp. nov., Varibaculum sp. nov., Peptoniphilus sp. nov., and Fenollaria sp. nov.) that were frequently found in patient urine, and (2) definition of a patient subgroup associated with metastasis development (p = 0.015, log-rank test). The presence of five specific anaerobic genera, which includes three of the novel isolates, was associated with cancer risk group, in urine sediment (p = 0.045, log-rank test), urine extracellular vesicles (p = 0.039), and cancer tissue (p = 0.035), with a meta-analysis hazard ratio for disease progression of 2.60 (95% confidence interval: 1.39-4.85; p = 0.003; Cox regression). A limitation is that functional links to cancer development are not yet established., Conclusions: This study characterises prostate and urine microbiomes, and indicates that specific anaerobic bacteria genera have prognostic potential., Patient Summary: In this study, we investigated the presence of bacteria in patient urine and the prostate. We identified four novel bacteria and suggest a potential prognostic utility for the microbiome in prostate cancer., (Copyright © 2022. Published by Elsevier B.V.)