Punctuated evolution of prostate cancer genomes.

The analysis of exonic DNA from prostate cancers has identified recurrently mutated genes, but the spectrum of genome-wide alterations has not been profiled extensively in this disease. We sequenced the genomes of 57 prostate tumors and matched normal tissues to characterize somatic alterations and to study how they accumulate during oncogenesis and progression. By modeling the genesis of genomic rearrangements, we identified abundant DNA translocations and deletions that arise in a highly interdependent manner. This phenomenon, which we term "chromoplexy," frequently accounts for the dysregulation of prostate cancer genes and appears to disrupt multiple cancer genes coordinately. Our modeling suggests that chromoplexy may induce considerable genomic derangement over relatively few events in prostate cancer and other neoplasms, supporting a model of punctuated cancer evolution. By characterizing the clonal hierarchy of genomic lesions in prostate tumors, we charted a path of oncogenic events along which chromoplexy may drive prostate carcinogenesis.

Comparative genomics of primary prostate cancer and paired metastases: insights from 12 molecular case studies.

Primary prostate cancer (PCa) can show marked molecular heterogeneity. However, systematic analyses comparing primary PCa and matched metastases in individual patients are lacking. We aimed to address the molecular aspects of metastatic progression while accounting for the heterogeneity of primary PCa. In this pilot study, we collected 12 radical prostatectomy (RP) specimens from men who subsequently developed metastatic castration-resistant prostate cancer (mCRPC). We used histomorphology (Gleason grade, focus size, stage) and immunohistochemistry (IHC) (ERG and p53) to identify independent tumors and/or distinct subclones of primary PCa. We then compared molecular profiles of these primary PCa areas to matched metastatic samples using whole-exome sequencing (WES) and amplicon-based DNA and RNA sequencing. Based on combined pathology and molecular analysis, seven (58%) RP specimens harbored monoclonal and topographically continuous disease, albeit with some degree of intratumor heterogeneity; four (33%) specimens showed true multifocal disease; and one displayed monoclonal disease with discontinuous topography. Early (truncal) events in primary PCa included SPOP p.F133V (one patient), BRAF p.K601E (one patient), and TMPRSS2:ETS rearrangements (eight patients). Activating AR alterations were seen in nine (75%) mCRPC patients, but not in matched primary PCa. Hotspot TP53 mutations, found in metastases from three patients, were readily present in matched primary disease. Alterations in genes encoding epigenetic modifiers were observed in several patients (either shared between primary foci and metastases or in metastatic samples only). WES-based phylogenetic reconstruction and/or clonality scores were consistent with the index focus designated by pathology review in six out of nine (67%) cases. The three instances of discordance pertained to monoclonal, topographically continuous tumors, which would have been considered as unique disease in routine practice. Overall, our results emphasize pathologic and molecular heterogeneity of primary PCa, and suggest that comprehensive IHC-assisted pathology review and genomic analysis are highly concordant in nominating the 'index' primary PCa area. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Proteomic and genomic signatures of repeat instability in cancer and adjacent normal tissues.

Repetitive sequences are hotspots of evolution at multiple levels. However, due to difficulties involved in their assembly and analysis, the role of repeats in tumor evolution is poorly understood. We developed a rigorous motif-based methodology to quantify variations in the repeat content, beyond microsatellites, in proteomes and genomes directly from proteomic and genomic raw data. This method was applied to a wide range of tumors and normal tissues. We identify high similarity between repeat instability patterns in tumors and their patient-matched adjacent normal tissues. Nonetheless, tumor-specific signatures both in protein expression and in the genome strongly correlate with cancer progression and robustly predict the tumorigenic state. In a patient, the hierarchy of genomic repeat instability signatures accurately reconstructs tumor evolution, with primary tumors differentiated from metastases. We observe an inverse relationship between repeat instability and point mutation load within and across patients independent of other somatic aberrations. Thus, repeat instability is a distinct, transient, and compensatory adaptive mechanism in tumor evolution and a potential signal for early detection.

Genomic correlates of clinical outcome in advanced prostate cancer.

Heterogeneity in the genomic landscape of metastatic prostate cancer has become apparent through several comprehensive profiling efforts, but little is known about the impact of this heterogeneity on clinical outcome. Here, we report comprehensive genomic and transcriptomic analysis of 429 patients with metastatic castration-resistant prostate cancer (mCRPC) linked with longitudinal clinical outcomes, integrating findings from whole-exome, transcriptome, and histologic analysis. For 128 patients treated with a first-line next-generation androgen receptor signaling inhibitor (ARSI; abiraterone or enzalutamide), we examined the association of 18 recurrent DNA- and RNA-based genomic alterations, including androgen receptor (AR) variant expression, AR transcriptional output, and neuroendocrine expression signatures, with clinical outcomes. Of these, only RB1 alteration was significantly associated with poor survival, whereas alterations in RB1, AR, and TP53 were associated with shorter time on treatment with an ARSI. This large analysis integrating mCRPC genomics with histology and clinical outcomes identifies RB1 genomic alteration as a potent predictor of poor outcome, and is a community resource for further interrogation of clinical and molecular associations.

TPES: tumor purity estimation from SNVs.

MOTIVATION: Tumor purity (TP) is the proportion of cancer cells in a tumor sample. TP impacts on the accurate assessment of molecular and genomics features as assayed with NGS approaches. State-of-the-art tools mainly rely on somatic copy-number alterations (SCNA) to quantify TP and therefore fail when a tumor genome is nearly euploid, i.e. 'non-aberrant' in terms of identifiable SCNAs. RESULTS: We introduce a computational method, tumor purity estimation from single-nucleotide variants (SNVs), which derives TP from the allelic fraction distribution of SNVs. On more than 7800 whole-exome sequencing data of TCGA tumor samples, it showed high concordance with a range of TP tools (Spearman's correlation between 0.68 and 0.82; >9 SNVs) and rescued TP estimates of 1, 194 samples (15%) pan-cancer. AVAILABILITY AND IMPLEMENTATION: TPES is available as an R package on CRAN and at https://bitbucket.org/l0ka/tpes.git. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

GPU computing for systems biology.

The development of detailed, coherent, models of complex biological systems is recognized as a key requirement for integrating the increasing amount of experimental data. In addition, in-silico simulation of bio-chemical models provides an easy way to test different experimental conditions, helping in the discovery of the dynamics that regulate biological systems. However, the computational power required by these simulations often exceeds that available on common desktop computers and thus expensive high performance computing solutions are required. An emerging alternative is represented by general-purpose scientific computing on graphics processing units (GPGPU), which offers the power of a small computer cluster at a cost of approximately $400. Computing with a GPU requires the development of specific algorithms, since the programming paradigm substantially differs from traditional CPU-based computing. In this paper, we review some recent efforts in exploiting the processing power of GPUs for the simulation of biological systems.

Allele-specific genomic data elucidate the role of somatic gain and copy-number neutral loss of heterozygosity in cancer.

Pan-cancer studies sketched the genomic landscape of the tumor types spectrum. We delineated the purity- and ploidy-adjusted allele-specific profiles of 4,950 patients across 27 tumor types from the Cancer Genome Atlas (TCGA). Leveraging allele-specific data, we reclassified as loss of heterozygosity (LOH) 9% and 7% of apparent copy-number wild-type and gain calls, respectively, and overall observed more than 18 million allelic imbalance somatic events at the gene level. Reclassification of copy-number events revealed associations between driver mutations and LOH, pointing out the timings between the occurrence of point mutations and copy-number events. Integrating allele-specific genomics and matched transcriptomics, we observed that allele-specific gene status is relevant in the regulation of TP53 and its targets. Further, we disclosed the role of copy-neutral LOH in the impairment of tumor suppressor genes and in disease progression. Our results highlight the role of LOH in cancer and contribute to the understanding of tumor progression.

Taming the complexity of biological pathways through parallel computing.

Biological systems are characterised by a large number of interacting entities whose dynamics is described by a number of reaction equations. Mathematical methods for modelling biological systems are mostly based on a centralised solution approach: the modelled system is described as a whole and the solution technique, normally the integration of a system of ordinary differential equations (ODEs) or the simulation of a stochastic model, is commonly computed in a centralised fashion. In recent times, research efforts moved towards the definition of parallel/distributed algorithms as a means to tackle the complexity of biological models analysis. In this article, we present a survey on the progresses of such parallelisation efforts describing the most promising results so far obtained.

Tumor subtype defines distinct pathways of molecular and clinical progression in primary prostate cancer.

BACKGROUNDMolecular characterization of prostate cancer (PCa) has revealed distinct subclasses based on underlying genomic alterations occurring early in the natural history of the disease. However, how these early alterations influence subsequent molecular events and the course of the disease over its long natural history remains unclear.METHODSWe explored the molecular and clinical progression of different genomic subtypes of PCa using distinct tumor lineage models based on human genomic and transcriptomic data. We developed transcriptional classifiers, and defined "early" and "late" categories of molecular subclasses from 8,158 PCa patients. Molecular subclasses were correlated with clinical outcomes and pathologic characteristics using Kaplan-Meier and logistic regression analyses.RESULTSWe identified PTEN and CHD1 alterations as subtype-specific late progression events specifically in ERG-overexpressing (ERG+) and SPOP-mutant tumors, respectively, and 2 distinct progression models consisting of ERG/PTEN (normal to ERG+ to PTEN-deleted) and SPOP/CHD1 (normal to SPOP-mutated to CHD1-deleted) with shared early tumorigenesis but distinct pathways toward progression. We found that within ERG+ and SPOP-mutant subtypes, late events were associated with worse prognosis. Importantly, the clinical and pathologic features associated with distinct late events at radical prostatectomy were strikingly different; PTEN deletions were associated with increased locoregional stage, while CHD1 deletions were only associated with increased grade, despite equivalent metastatic potential.CONCLUSIONThese findings suggest a paradigm in which specific subtypes of PCa follow distinct pathways of progression, at both the molecular and clinical levels. Therefore, the interpretation of common clinical parameters such as locoregional tumor stage may be influenced by the underlying tumor lineage, and potentially influence management decisions.FUNDINGProstate Cancer Foundation, National Cancer Institute, Urology Care Foundation, Damon Runyon Cancer Research Foundation, US Department of Defense, and the AIRC Foundation.

Systematic Assessment of Tumor Purity and Its Clinical Implications.

PURPOSE: The tumor microenvironment is complex, comprising heterogeneous cellular populations. As molecular profiles are frequently generated using bulk tissue sections, they represent an admixture of multiple cell types (including immune, stromal, and cancer cells) interacting with each other. Therefore, these molecular profiles are confounded by signals emanating from many cell types. Accurate assessment of residual cancer cell fraction is crucial for parameterization and interpretation of genomic analyses, as well as for accurately interpreting the clinical properties of the tumor. MATERIALS AND METHODS: To benchmark cancer cell fraction estimation methods, 10 estimators were applied to a clinical cohort of 333 patients with prostate cancer. These methods include gold-standard multiobserver pathology estimates, as well as estimates inferred from genome, epigenome, and transcriptome data. In addition, two methods based on genomic and transcriptomic profiles were used to quantify tumor purity in 4,497 tumors across 12 cancer types. Bulk mRNA and microRNA profiles were subject to in silico deconvolution to estimate cancer cell-specific mRNA and microRNA profiles. RESULTS: We present a systematic comparison of 10 tumor purity estimation methods on a cohort of 333 prostate tumors. We quantify variation among purity estimation methods and demonstrate how this influences interpretation of clinico-genomic analyses. Our data show poor concordance between pathologic and molecular purity estimates, necessitating caution when interpreting molecular results. Limited concordance between DNA- and mRNA-derived purity estimates remained a general pan-cancer phenomenon when tested in an additional 4,497 tumors spanning 12 cancer types. CONCLUSION: The choice of tumor purity estimation method may have a profound impact on the interpretation of genomic assays. Taken together, these data highlight the need for improved assessment of tumor purity and quantitation of its influences on the molecular hallmarks of cancers.

Role of specialized composition of SWI/SNF complexes in prostate cancer lineage plasticity.

Advanced prostate cancer initially responds to hormonal treatment, but ultimately becomes resistant and requires more potent therapies. One mechanism of resistance observed in around 10-20% of these patients is lineage plasticity, which manifests in a partial or complete small cell or neuroendocrine prostate cancer (NEPC) phenotype. Here, we investigate the role of the mammalian SWI/SNF (mSWI/SNF) chromatin remodeling complex in NEPC. Using large patient datasets, patient-derived organoids and cancer cell lines, we identify mSWI/SNF subunits that are deregulated in NEPC and demonstrate that SMARCA4 (BRG1) overexpression is associated with aggressive disease. We also show that SWI/SNF complexes interact with different lineage-specific factors in NEPC compared to prostate adenocarcinoma. These data point to a role for mSWI/SNF complexes in therapy-related lineage plasticity, which may also be relevant for other solid tumors.

Ploidy- and Purity-Adjusted Allele-Specific DNA Analysis Using CLONETv2.

High-throughput DNA sequencing technology provides base-level and statistically rich information about the genomic content of a sample. In the contexts of cancer research and precision oncology, thousands of genomes from paired tumor and matched normal samples are profiled and processed to determine somatic copy-number changes and single-nucleotide variations. Higher-order informative analyses, in the form of allele-specific copy-number assessments or subclonality quantification, require reliable estimates of tumor DNA ploidy and tumor cellularity. CLONETv2 provides a complete set of functions to process matched normal and tumor pairs using patient-specific genotype data, is independent of low-level tools (e.g., aligner, segmentation algorithm, mutation caller) and offers high-level functions to compute allele-specific copy number from segmented data and to identify subclonal population in the input sample. CLONETv2 is applicable to whole-genome, whole-exome and targeted sequencing data generated either from tissue or from liquid biopsy samples. © 2019 The Authors.

A Phase II Trial of the Aurora Kinase A Inhibitor Alisertib for Patients with Castration-resistant and Neuroendocrine Prostate Cancer: Efficacy and Biomarkers.

PURPOSE: Neuroendocrine prostate cancer (NEPC) is an aggressive variant of prostate cancer that may develop de novo or as a mechanism of treatment resistance. N-myc is capable of driving NEPC progression. Alisertib inhibits the interaction between N-myc and its stabilizing factor Aurora-A, inhibiting N-myc signaling, and suppressing tumor growth. PATIENTS AND METHODS: Sixty men were treated with alisertib 50 mg twice daily for 7 days every 21 days. Eligibility included metastatic prostate cancer and at least one: small-cell neuroendocrine morphology; ≥50% neuroendocrine marker expression; new liver metastases without PSA progression; or elevated serum neuroendocrine markers. The primary endpoint was 6-month radiographic progression-free survival (rPFS). Pretreatment biopsies were evaluated by whole exome and RNA-seq and patient-derived organoids were developed. RESULTS: Median PSA was 1.13 ng/mL (0.01-514.2), number of prior therapies was 3, and 68% had visceral metastases. Genomic alterations involved RB1 (55%), TP53 (46%), PTEN (29%), BRCA2 (29%), and AR (27%), and there was a range of androgen receptor signaling and NEPC marker expression. Six-month rPFS was 13.4% and median overall survival was 9.5 months (7.3-13). Exceptional responders were identified, including complete resolution of liver metastases and prolonged stable disease, with tumors suggestive of N-myc and Aurora-A overactivity. Patient organoids exhibited concordant responses to alisertib and allowed for the dynamic testing of Aurora-N-myc complex disruption. CONCLUSIONS: Although the study did not meet its primary endpoint, a subset of patients with advanced prostate cancer and molecular features supporting Aurora-A and N-myc activation achieved significant clinical benefit from single-agent alisertib.

A highly specific SpCas9 variant is identified by in vivo screening in yeast.

Despite the utility of CRISPR-Cas9 nucleases for genome editing, the potential for off-target activity limits their application, especially for therapeutic purposes. We developed a yeast-based assay to identify optimized Streptococcus pyogenes Cas9 (SpCas9) variants that enables simultaneous evaluation of on- and off-target activity. We screened a library of SpCas9 variants carrying random mutations in the REC3 domain and identified mutations that increased editing accuracy while maintaining editing efficiency. We combined four beneficial mutations to generate evoCas9, a variant that has fidelity exceeding both wild-type (79-fold improvement) and rationally designed Cas9 variants (fourfold average improvement), while maintaining near wild-type on-target editing efficiency (90% median residual activity). Evaluating evoCas9 on endogenous genomic loci, we demonstrated a substantially improved specificity and observed no off-target sites for four of the eight single guide RNAs (sgRNAs) tested. Finally, we showed that following long-term expression (40 d), evoCas9 strongly limited the nonspecific cleavage of a difficult-to-discriminate off-target site and fully abrogated the cleavage of two additional off-target sites.

Patient derived organoids to model rare prostate cancer phenotypes.

A major hurdle in the study of rare tumors is a lack of existing preclinical models. Neuroendocrine prostate cancer is an uncommon and aggressive histologic variant of prostate cancer that may arise de novo or as a mechanism of treatment resistance in patients with pre-existing castration-resistant prostate cancer. There are few available models to study neuroendocrine prostate cancer. Here, we report the generation and characterization of tumor organoids derived from needle biopsies of metastatic lesions from four patients. We demonstrate genomic, transcriptomic, and epigenomic concordance between organoids and their corresponding patient tumors. We utilize these organoids to understand the biologic role of the epigenetic modifier EZH2 in driving molecular programs associated with neuroendocrine prostate cancer progression. High-throughput organoid drug screening nominated single agents and drug combinations suggesting repurposing opportunities. This proof of principle study represents a strategy for the study of rare cancer phenotypes.

Hit and go CAS9 delivered through a lentiviral based self-limiting circuit.

In vivo application of the CRISPR-Cas9 technology is still limited by unwanted Cas9 genomic cleavages. Long-term expression of Cas9 increases the number of genomic loci non-specifically cleaved by the nuclease. Here we develop a Self-Limiting Cas9 circuit for Enhanced Safety and specificity (SLiCES) which consists of an expression unit for Streptococcus pyogenes Cas9 (SpCas9), a self-targeting sgRNA and a second sgRNA targeting a chosen genomic locus. The self-limiting circuit results in increased genome editing specificity by controlling Cas9 levels. For its in vivo utilization, we next integrate SLiCES into a lentiviral delivery system (lentiSLiCES) via circuit inhibition to achieve viral particle production. Upon delivery into target cells, the lentiSLiCES circuit switches on to edit the intended genomic locus while simultaneously stepping up its own neutralization through SpCas9 inactivation. By preserving target cells from residual nuclease activity, our hit and go system increases safety margins for genome editing.

Personalized In Vitro and In Vivo Cancer Models to Guide Precision Medicine.

Precision medicine is an approach that takes into account the influence of individuals' genes, environment, and lifestyle exposures to tailor interventions. Here, we describe the development of a robust precision cancer care platform that integrates whole-exome sequencing with a living biobank that enables high-throughput drug screens on patient-derived tumor organoids. To date, 56 tumor-derived organoid cultures and 19 patient-derived xenograft (PDX) models have been established from the 769 patients enrolled in an Institutional Review Board-approved clinical trial. Because genomics alone was insufficient to identify therapeutic options for the majority of patients with advanced disease, we used high-throughput drug screening to discover effective treatment strategies. Analysis of tumor-derived cells from four cases, two uterine malignancies and two colon cancers, identified effective drugs and drug combinations that were subsequently validated using 3-D cultures and PDX models. This platform thereby promotes the discovery of novel therapeutic approaches that can be assessed in clinical trials and provides personalized therapeutic options for individual patients where standard clinical options have been exhausted.Significance: Integration of genomic data with drug screening from personalized in vitro and in vivo cancer models guides precision cancer care and fuels next-generation research. Cancer Discov; 7(5); 462-77. ©2017 AACR.See related commentary by Picco and Garnett, p. 456This article is highlighted in the In This Issue feature, p. 443.

SOX2 promotes lineage plasticity and antiandrogen resistance in TP53- and RB1-deficient prostate cancer.

Some cancers evade targeted therapies through a mechanism known as lineage plasticity, whereby tumor cells acquire phenotypic characteristics of a cell lineage whose survival no longer depends on the drug target. We use in vitro and in vivo human prostate cancer models to show that these tumors can develop resistance to the antiandrogen drug enzalutamide by a phenotypic shift from androgen receptor (AR)-dependent luminal epithelial cells to AR-independent basal-like cells. This lineage plasticity is enabled by the loss of TP53 and RB1 function, is mediated by increased expression of the reprogramming transcription factor SOX2, and can be reversed by restoring TP53 and RB1 function or by inhibiting SOX2 expression. Thus, mutations in tumor suppressor genes can create a state of increased cellular plasticity that, when challenged with antiandrogen therapy, promotes resistance through lineage switching.

Next-Generation Rapid Autopsies Enable Tumor Evolution Tracking and Generation of Preclinical Models.

PURPOSE: Patients with cancer who graciously consent for autopsy represent an invaluable resource for the study of cancer biology. To advance the study of tumor evolution, metastases, and resistance to treatment, we developed a next-generation rapid autopsy program integrated within a broader precision medicine clinical trial that interrogates pre- and postmortem tissue samples for patients of all ages and cancer types. MATERIALS AND METHODS: One hundred twenty-three (22%) of 554 patients who consented to the clinical trial also consented for rapid autopsy. This report comprises the first 15 autopsies, including patients with metastatic carcinoma (n = 10), melanoma (n = 1), and glioma (n = 4). Whole-exome sequencing (WES) was performed on frozen autopsy tumor samples from multiple anatomic sites and on non-neoplastic tissue. RNA sequencing (RNA-Seq) was performed on a subset of frozen samples. Tissue was also used for the development of preclinical models, including tumor organoids and patient-derived xenografts. RESULTS: Three hundred forty-six frozen samples were procured in total. WES was performed on 113 samples and RNA-Seq on 72 samples. Successful cell strain, tumor organoid, and/or patient-derived xenograft development was achieved in four samples, including an inoperable pediatric glioma. WES data were used to assess clonal evolution and molecular heterogeneity of tumors in individual patients. Mutational profiles of primary tumors and metastases yielded candidate mediators of metastatic spread and organotropism including CUL9 and PIGM in metastatic ependymoma and ANKRD52 in metastatic melanoma to the lung. RNA-Seq data identified novel gene fusion candidates. CONCLUSION: A next-generation sequencing-based autopsy program in conjunction with a pre-mortem precision medicine pipeline for diverse tumors affords a valuable window into clonal evolution, metastasis, and alterations underlying treatment. Moreover, such an autopsy program yields robust preclinical models of disease.

Clonal evolution of chemotherapy-resistant urothelial carcinoma.

Chemotherapy-resistant urothelial carcinoma has no uniformly curative therapy. Understanding how selective pressure from chemotherapy directs the evolution of urothelial carcinoma and shapes its clonal architecture is a central biological question with clinical implications. To address this question, we performed whole-exome sequencing and clonality analysis of 72 urothelial carcinoma samples, including 16 matched sets of primary and advanced tumors prospectively collected before and after chemotherapy. Our analysis provided several insights: (i) chemotherapy-treated urothelial carcinoma is characterized by intra-patient mutational heterogeneity, and the majority of mutations are not shared; (ii) both branching evolution and metastatic spread are very early events in the natural history of urothelial carcinoma; (iii) chemotherapy-treated urothelial carcinoma is enriched with clonal mutations involving L1 cell adhesion molecule (L1CAM) and integrin signaling pathways; and (iv) APOBEC-induced mutagenesis is clonally enriched in chemotherapy-treated urothelial carcinoma and continues to shape the evolution of urothelial carcinoma throughout its lifetime.