Sterile inflammation via TRPM8 RNA-dependent TLR3-NF-kB/IRF3 activation promotes antitumor immunity in prostate cancer.

Inflammation is a common condition of prostate tissue, whose impact on carcinogenesis is highly debated. Microbial colonization is a well-documented cause of a small percentage of prostatitis cases, but it remains unclear what underlies the majority of sterile inflammation reported. Here, androgen- independent fluctuations of PSA expression in prostate cells have lead us to identify a prominent function of the Transient Receptor Potential Cation Channel Subfamily M Member 8 (TRPM8) gene in sterile inflammation. Prostate cells secret TRPM8 RNA into extracellular vesicles (EVs), which primes TLR3/NF-kB-mediated inflammatory signaling after EV endocytosis by epithelial cancer cells. Furthermore, prostate cancer xenografts expressing a translation-defective form of TRPM8 RNA contain less collagen type I in the extracellular matrix, significantly more infiltrating NK cells, and larger necrotic areas as compared to control xenografts. These findings imply sustained, androgen-independent expression of TRPM8 constitutes as a promoter of anticancer innate immunity, which may constitute a clinically relevant condition affecting prostate cancer prognosis.

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.

Mutation-selection balance and compensatory mechanisms in tumour evolution.

Intratumour heterogeneity and phenotypic plasticity, sustained by a range of somatic aberrations, as well as epigenetic and metabolic adaptations, are the principal mechanisms that enable cancers to resist treatment and survive under environmental stress. A comprehensive picture of the interplay between different somatic aberrations, from point mutations to whole-genome duplications, in tumour initiation and progression is lacking. We posit that different genomic aberrations generally exhibit a temporal order, shaped by a balance between the levels of mutations and selective pressures. Repeat instability emerges first, followed by larger aberrations, with compensatory effects leading to robust tumour fitness maintained throughout the tumour progression. A better understanding of the interplay between genetic aberrations, the microenvironment, and epigenetic and metabolic cellular states is essential for early detection and prevention of cancer as well as development of efficient therapeutic strategies.

MIMESIS: minimal DNA-methylation signatures to quantify and classify tumor signals in tissue and cell-free DNA samples.

DNA-methylation alterations are common in cancer and display unique characteristics that make them ideal markers for tumor quantification and classification. Here we present MIMESIS, a computational framework exploiting minimal DNA-methylation signatures composed by a few dozen informative DNA-methylation sites to quantify and classify tumor signals in tissue and cell-free DNA samples. Extensive analyses of multiple independent and heterogenous datasets including >7200 samples demonstrate the capability of MIMESIS to provide precise estimations of tumor content and to enable accurate classification of tumor type and molecular subtype. To assess our framework for clinical applications, we designed a MIMESIS-informed assay incorporating the minimal signatures for breast cancer. Using both artificial samples and clinical serial cell-free DNA samples from patients with metastatic breast cancer, we show that our approach provides accurate estimations of tumor content, sensitive detection of tumor signal and the ability to capture clinically relevant molecular subtype in patients' circulation. This study provides evidence that our extremely parsimonious approach can be used to develop cost-effective and highly scalable DNA-methylation assays that could support and facilitate the implementation of precision oncology in clinical practice.

CHD8 suppression impacts on histone H3 lysine 36 trimethylation and alters RNA alternative splicing.

Disruptive mutations in the chromodomain helicase DNA-binding protein 8 gene (CHD8) have been recurrently associated with autism spectrum disorders (ASDs). Here we investigated how chromatin reacts to CHD8 suppression by analyzing a panel of histone modifications in induced pluripotent stem cell-derived neural progenitors. CHD8 suppression led to significant reduction (47.82%) in histone H3K36me3 peaks at gene bodies, particularly impacting on transcriptional elongation chromatin states. H3K36me3 reduction specifically affects highly expressed, CHD8-bound genes and correlates with altered alternative splicing patterns of 462 genes implicated in 'regulation of RNA splicing' and 'mRNA catabolic process'. Mass spectrometry analysis uncovered a novel interaction between CHD8 and the splicing regulator heterogeneous nuclear ribonucleoprotein L (hnRNPL), providing the first mechanistic insights to explain the CHD8 suppression-derived splicing phenotype, partly implicating SETD2, a H3K36me3 methyltransferase. In summary, our results point toward broad molecular consequences of CHD8 suppression, entailing altered histone deposition/maintenance and RNA processing regulation as important regulatory processes in ASD.

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.

Plasma tumor DNA is associated with increased risk of venous thromboembolism in metastatic castration-resistant cancer patients.

Cancer is a risk factor for venous thromboembolism (VTE). Plasma tumor DNA (ptDNA) is an independent predictor of outcome in metastatic castration-resistant prostate cancer (mCRPC). We aimed to investigate the association between ptDNA and VTE in mCRPC. This prospective biomarker study included 180 mCRPC patients treated with abiraterone and enzalutamide from April 2013 to December 2018. We excluded patients with a previous VTE history and/or ongoing anticoagulation therapy. Targeted next-generation sequencing was performed to determine ptDNA fraction from pretreatment plasma samples. VTE risk based on survival analysis was performed using cumulative incidence function and estimating sub-distributional hazard ratio (SHR). At a median follow-up of 58 months (range 0.5-111.0), we observed 21 patients who experienced VTE with a cumulative incidence at 12 months of 17.1% (95% confidence interval [CI] 10.3-23.9). Elevated ptDNA, visceral metastasis, prior chemotherapy and lactate dehydrogenase (LDH) were significantly associated with higher VTE incidence compared to patients with no thrombosis (12-month estimate, 18.6% vs 3.5%, P = .0003; 44.4% vs 14.8%, P = .015; 24.7% vs 4.5%, P = .006; and 30.0% vs 13.5%, P = .05, respectively). In the multivariate analysis including ptDNA level, visceral metastases, number of lesions and serum LDH, high ptDNA fraction was the only independent factor associated with the risk of thrombosis (HR 5.78, 95% CI 1.63-20.44, P = .006). These results first suggest that baseline ptDNA fraction in mCRPC patients treated with abiraterone or enzalutamide may be associated with increased VTE risk. These patients may be followed-up more closely for the VTE risk, and the need for a primary thromboprophylaxis should be taken into account in mCRPC with elevated ptDNA.

Role of non-coding sequence variants in cancer.

Patients with cancer carry somatic sequence variants in their tumour in addition to the germline variants in their inherited genome. Although variants in protein-coding regions have received the most attention, numerous studies have noted the importance of non-coding variants in cancer. Moreover, the overwhelming majority of variants, both somatic and germline, occur in non-coding portions of the genome. We review the current understanding of non-coding variants in cancer, including the great diversity of the mutation types--from single nucleotide variants to large genomic rearrangements--and the wide range of mechanisms by which they affect gene expression to promote tumorigenesis, such as disrupting transcription factor-binding sites or functions of non-coding RNAs. We highlight specific case studies of somatic and germline variants, and discuss how non-coding variants can be interpreted on a large-scale through computational and experimental methods.

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.

ABEMUS: platform-specific and data-informed detection of somatic SNVs in cfDNA.

MOTIVATION: The use of liquid biopsies for cancer patients enables the non-invasive tracking of treatment response and tumor dynamics through single or serial blood drawn tests. Next-generation sequencing assays allow for the simultaneous interrogation of extended sets of somatic single-nucleotide variants (SNVs) in circulating cell-free DNA (cfDNA), a mixture of DNA molecules originating both from normal and tumor tissue cells. However, low circulating tumor DNA (ctDNA) fractions together with sequencing background noise and potential tumor heterogeneity challenge the ability to confidently call SNVs. RESULTS: We present a computational methodology, called Adaptive Base Error Model in Ultra-deep Sequencing data (ABEMUS), which combines platform-specific genetic knowledge and empirical signal to readily detect and quantify somatic SNVs in cfDNA. We tested the capability of our method to analyze data generated using different platforms with distinct sequencing error properties and we compared ABEMUS performances with other popular SNV callers on both synthetic and real cancer patients sequencing data. Results show that ABEMUS performs better in most of the tested conditions proving its reliability in calling low variant allele frequencies somatic SNVs in low ctDNA levels plasma samples. AVAILABILITY AND IMPLEMENTATION: ABEMUS is cross-platform and can be installed as R package. The source code is maintained on Github at http://github.com/cibiobcg/abemus, and it is also available at CRAN official R repository. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Investigation of the anaerobic digestion of cosmetic industrial wastes: Feasibility and perspectives.

This study assessed the anaerobic digestion (AD) of wastes deriving from cosmetics production: sludge from onsite wastewater treatment plant (sWWTP), residues of shampoo/conditioner (RSC) and sludge from mascara production (MS), considered as single substrates and as mixture according to the produced amounts (54 %-wt sWWTP, 31 %-wt RSC, 13 %-wt MS, plus 2 %-wt food waste from the canteen, FW). Total COD (CODT) was 624-1436 g O2/kg VS, while soluble COD was 5-23 %-wt of CODT. AD tests at 35 °C achieved the following biogas yields: 0.10 Nm3/kgvs (70 %-v/v methane) for sWWTP; 0.07 Nm3/kgvs (62 %-v/v methane) for RSC; 0.04 Nm3/kgvs (67 %-v/v methane) for MS. The mixed substrates underwent physico-chemical pre-treatments (thermo-alkaline, TA: 120 min at 50 °C; thermo-alkaline-sonication, TAS: 15 min at 40 kHz and 80 °C, both based on the addition of 0.08 g NaOH per each g of total solid in the substrate), reaching 64-66% disintegration rate, and AD tests (5 %-wt dry substance) at 35 and 52 °C. Biogas yields were (for TA and TAS respectively): 0.22 and 0.20 Nm3/kgVS (62-70% methane); 0.21 and 0.19 Nm3/kgVS (66-66% methane) at 52 °C. At both temperatures, methane yields considerably improved (+71-100%), compared to mixed untreated substrates, and 5-8 %-wt total solids reductions were observed. A technical-economic scale-up assessment completed the research. The energy analysis highlighted the crucial role of TA pre-treatment in achieving the process energetic sustainability. The economic analysis showed that the AD of the considered cosmetic waste could be sustainable anyway, thanks to the savings related to the disposal of the digestate compared to current waste management costs.

Plasma tumour DNA as an early indicator of treatment response in metastatic castration-resistant prostate cancer.

BACKGROUND: Plasma tumour DNA (ptDNA) levels on treatment are associated with response in a variety of cancers. However, the role of ptDNA in prostate cancer monitoring remains largely unexplored. Here we characterised on-treatment ptDNA dynamics and evaluated its potential for early assessment of therapy efficacy for metastatic castration-resistant prostate cancer (mCRPC). METHODS: Between 2011 and 2016, 114 sequential plasma samples from 43 mCRPC abiraterone-treated patients were collected. Targeted next-generation sequencing was performed to determine ptDNA fraction. ptDNA progressive disease was defined as a rise in the fraction compared to the pre-treatment. RESULTS: A ptDNA rise in the first on-treatment sample (interquartile range (IQR) 2.6-3.7 months) was significantly associated with increased risk of early radiographic or any prostate-specific antigen (PSA) rise (odds ratio (OR) = 15.8, 95% confidence interval (CI) 3.5-60.2, p = 0.0002 and OR = 6.0, 95% CI 1.6-20.0, p = 0.01, respectively). We also identified exemplar cases that had a rise in PSA or pseudoprogression secondary to bone flare but no rise in ptDNA. In an exploratory analysis, initial ptDNA change was found to associate with the duration of response to prior androgen deprivation therapy (p < 0.0001) but not to prior taxanes (p = 0.32). CONCLUSIONS: We found that ptDNA assessment for therapy monitoring in mCRPC is feasible and provides data relevant to the clinical setting. Prospective evaluation of these findings is now merited.

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.

PaCBAM: fast and scalable processing of whole exome and targeted sequencing data.

BACKGROUND: Interrogation of whole exome and targeted sequencing NGS data is rapidly becoming a preferred approach for the exploration of large cohorts in the research setting and importantly in the context of precision medicine. Single-base and genomic region level data retrieval and processing still constitute major bottlenecks in NGS data analysis. Fast and scalable tools are hence needed. RESULTS: PaCBAM is a command line tool written in C and designed for the characterization of genomic regions and single nucleotide positions from whole exome and targeted sequencing data. PaCBAM computes depth of coverage and allele-specific pileup statistics, implements a fast and scalable multi-core computational engine, introduces an innovative and efficient on-the-fly read duplicates filtering strategy and provides comprehensive text output files and visual reports. We demonstrate that PaCBAM exploits parallel computation resources better than existing tools, resulting in important reductions of processing time and memory usage, hence enabling an efficient and fast exploration of large datasets. CONCLUSIONS: PaCBAM is a fast and scalable tool designed to process genomic regions from NGS data files and generate coverage and pileup comprehensive statistics for downstream analysis. The tool can be easily integrated in NGS processing pipelines and is available from Bitbucket and Docker/Singularity hubs.

Tumor purity quantification by clonal DNA methylation signatures.

Motivation: Controlling for tumor purity in molecular analyses is essential to allow for reliable genomic aberration calls, for inter-sample comparison and to monitor heterogeneity of cancer cell populations. In genome wide screening studies, the assessment of tumor purity is typically performed by means of computational methods that exploit somatic copy number aberrations. Results: We present a strategy, called Purity Assessment from clonal MEthylation Sites (PAMES), which uses the methylation level of a few dozen, highly clonal, tumor type specific CpG sites to estimate the purity of tumor samples, without the need of a matched benign control. We trained and validated our method in more than 6000 samples from different datasets. Purity estimates by PAMES were highly concordant with other state-of-the-art tools and its evaluation in a cancer cell line dataset highlights its reliability to accurately estimate tumor admixtures. We extended the capability of PAMES to the analysis of CpG islands instead of the more platform-specific CpG sites and demonstrated its accuracy in a set of advanced tumors profiled by high throughput DNA methylation sequencing. These analyses show that PAMES is a valuable tool to assess the purity of tumor samples in the settings of clinical research and diagnostics. Availability and implementation: https://github.com/cgplab/PAMES. Contact: matteo.benelli@uslcentro.toscana.it or f.demichelis@unitn.it. Supplementary information: Supplementary data are available at Bioinformatics online.

The Genomics of Prostate Cancer: emerging understanding with technologic advances.

With the advent of next-generation sequencing technologies and large whole-exome and genome studies in prostate and other cancers, our understanding of the landscape of genomic alterations has dramatically been refined. In additional to well-known alterations in genomic regions involving 8p, 8q, 10q23, common ETS translocations and androgen receptor amplifications, newer technology have uncovered recurrent mutations in SPOP, FOXA1, MED12, IDH and complex large scale genomic alterations (eg, chromoplexy). This review surveys the enhanced landscape of genomic alterations in clinically localized and advanced prostate cancer.

EthSEQ: ethnicity annotation from whole exome sequencing data.

SUMMARY: Whole exome sequencing (WES) is widely utilized both in translational cancer genomics studies and in the setting of precision medicine. Stratification of individual's ethnicity is fundamental for the correct interpretation of personal genomic variation impact. We implemented EthSEQ to provide reliable and rapid ethnicity annotation from whole exome sequencing individual's data, validated it on 1000 Genome Project and TCGA data (2700 samples) demonstrating high precision, and finally assessed computational performances compared to other tools. EthSEQ can be integrated into any WES based processing pipeline and exploits multi-core capabilities. AVAILABILITY AND IMPLEMENTATION: R package available at github.com/aromanel/EthSEQ and CRAN repository. CONTACT: alessandro.romanel@unitn.it or f.demichelis@unitn.it. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.