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.

Synggen: fast and data-driven generation of synthetic heterogeneous NGS cancer data.

SUMMARY: Whole-exome and targeted sequencing are widely utilized both in translational cancer genomics and in the setting of precision medicine. The benchmarking of computational methods and tools that are in continuous development is fundamental for the correct interpretation of somatic genomic profiling results. To this aim we developed synggen, a tool for the fast generation of large-scale realistic and heterogeneous cancer whole-exome and targeted sequencing synthetic datasets, which enables the incorporation of phased germline single nucleotide polymorphisms and complex allele-specific somatic genomic events. Synggen performances and effectiveness in generating synthetic cancer data are shown across different scenarios and considering different platforms with distinct characteristics. AVAILABILITY AND IMPLEMENTATION: synggen is freely available at https://bitbucket.org/CibioBCG/synggen/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Transient rapamycin treatment during developmental stage extends lifespan in Mus musculus and Drosophila melanogaster.

Lifespan is determined by complex and tangled mechanisms that are largely unknown. The early postnatal stage has been proposed to play a role in lifespan, but its contribution is still controversial. Here, we show that a short rapamycin treatment during early life can prolong lifespan in Mus musculus and Drosophila melanogaster. Notably, the same treatment at later time points has no effect on lifespan, suggesting that a specific time window is involved in lifespan regulation. We also find that sulfotransferases are upregulated during early rapamycin treatment both in newborn mice and in Drosophila larvae, and transient dST1 overexpression in Drosophila larvae extends lifespan. Our findings unveil a novel link between early-life treatments and long-term effects on lifespan.

Intra-epithelial non-canonical Activin A signaling safeguards prostate progenitor quiescence.

The healthy prostate is a relatively quiescent tissue. Yet, prostate epithelium overgrowth is a common condition during aging, associated with urinary dysfunction and tumorigenesis. For over thirty years, TGF-ß ligands have been known to induce cytostasis in a variety of epithelia, but the intracellular pathway mediating this signal in the prostate, and its relevance for quiescence, have remained elusive. Here, using mouse prostate organoids to model epithelial progenitors, we find that intra-epithelial non-canonical Activin A signaling inhibits cell proliferation in a Smad-independent manner. Mechanistically, Activin A triggers Tak1 and p38 ΜAPK activity, leading to p16 and p21 nuclear import. Spontaneous evasion from this quiescent state occurs upon prolonged culture, due to reduced Activin A secretion, a condition associated with DNA replication stress and aneuploidy. Organoids capable to escape quiescence in vitro are also able to implant with increased frequency into immunocompetent mice. This study demonstrates that non-canonical Activin A signaling safeguards epithelial quiescence in the healthy prostate, with potential implications for the understanding of cancer initiation, and the development of therapies targeting quiescent tumor progenitors.

Polympact: exploring functional relations among common human genetic variants.

In the last years, many studies were able to identify associations between common genetic variants and complex diseases. However, the mechanistic biological links explaining these associations are still mostly unknown. Common variants are usually associated with a relatively small effect size, suggesting that interactions among multiple variants might be a major genetic component of complex diseases. Hence, elucidating the presence of functional relations among variants may be fundamental to identify putative variants' interactions. To this aim, we developed Polympact, a web-based resource that allows to explore functional relations among human common variants by exploiting variants' functional element landscape, their impact on transcription factor binding motifs, and their effect on transcript levels of protein-coding genes. Polympact characterizes over 18 million common variants and allows to explore putative relations by combining clustering analysis and innovative similarity and interaction network models. The properties of the network models were studied and the utility of Polympact was demonstrated by analysing the rich sets of Breast Cancer and Alzheimer's GWAS variants. We identified relations among multiple variants, suggesting putative interactions. Polympact is freely available at bcglab.cibio.unitn.it/polympact.

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.

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.

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.

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.

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.

SpikeFlow: automated and flexible analysis of ChIP-Seq data with spike-in control.

ChIP with reference exogenous genome (ChIP-Rx) is widely used to study histone modification changes across different biological conditions. A key step in the bioinformatics analysis of this data is calculating the normalization factors, which vary from the standard ChIP-seq pipelines. Choosing and applying the appropriate normalization method is crucial for interpreting the biological results. However, a comprehensive pipeline for complete ChIP-Rx data analysis is lacking. To address these challenges, we introduce SpikeFlow, an integrated Snakemake workflow that combines features from various existing tools to streamline ChIP-Rx data processing and enhance usability. SpikeFlow automates spike-in data scaling and provides multiple normalization options. It also performs peak calling and differential analysis with distinct modalities, enabling the detection of enrichment regions for histone modifications and transcription factor binding. Our workflow runs in-depth quality control at all the processing steps and generates an analysis report with tables and graphs to facilitate results interpretation. We validated the pipeline by performing a comparative analysis with DiffBind and SpikChIP, demonstrating robust performances in various biological models. By combining diverse functionalities into a single platform, SpikeFlow aims to simplify ChIP-Rx data analysis for the research community.

Germline determinants of aberrant signaling pathways in cancer.

Cancer is a complex disease influenced by a heterogeneous landscape of both germline genetic variants and somatic aberrations. While there is growing evidence suggesting an interplay between germline and somatic variants, and a substantial number of somatic aberrations in specific pathways are now recognized as hallmarks in many well-known forms of cancer, the interaction landscape between germline variants and the aberration of those pathways in cancer remains largely unexplored. Utilizing over 8500 human samples across 33 cancer types characterized by TCGA and considering binary traits defined using a large collection of somatic aberration profiles across ten well-known oncogenic signaling pathways, we conducted a series of GWAS and identified genome-wide and suggestive associations involving 276 SNPs. Among these, 94 SNPs revealed cis-eQTL links with cancer-related genes or with genes functionally correlated with the corresponding traits' oncogenic pathways. GWAS summary statistics for all tested traits were then used to construct a set of polygenic scores employing a customized computational strategy. Polygenic scores for 24 traits demonstrated significant performance and were validated using data from PCAWG and CCLE datasets. These scores showed prognostic value for clinical variables and exhibited significant effectiveness in classifying patients into specific cancer subtypes or stratifying patients with cancer-specific aggressive phenotypes. Overall, we demonstrate that germline genetics can describe patients' genetic liability to develop specific cancer molecular and clinical profiles.

The three YTHDF paralogs and VIRMA are strong cross-histotype tumor driver candidates among m6A core genes.

N6-Methyladenosine (m6A) is the most abundant internal modification in mRNAs. Despite accumulating evidence for the profound impact of m6A on cancer biology, there are conflicting reports that alterations in genes encoding the m6A machinery proteins can either promote or suppress cancer, even in the same tumor type. Using data from The Cancer Genome Atlas, we performed a pan-cancer investigation of 15 m6A core factors in nearly 10000 samples from 31 tumor types to reveal underlying cross-tumor patterns. Altered expression, largely driven by copy number variations at the chromosome arm level, results in the most common mode of dysregulation of these factors. YTHDF1, YTHDF2, YTHDF3 and VIRMA are the most frequently altered factors and the only ones to be uniquely altered when tumors are grouped according to the expression pattern of the m6A factors. These genes are also the only ones with coherent, pan-cancer predictive power for progression-free survival. On the contrary, METTL3, the most intensively studied m6A factor as a cancer target, shows much lower levels of alteration and no predictive power for patient survival. Therefore, we propose the non-enzymatic YTHDF and VIRMA genes as preferred subjects to dissect the role of m6A in cancer and as priority cancer targets.

Rarγ -Foxa1 signaling promotes luminal identity in prostate progenitors and is disrupted in prostate cancer.

Retinoic acid (RA) signaling is a master regulator of vertebrate development with crucial roles in directing body axis orientation and tissue differentiation, including in the reproductive system. However, a mechanistic understanding of how RA signaling promotes cell lineage identity in different tissues is often missing. Here, leveraging prostate organoid technology, we demonstrated that RA signaling orchestrates the commitment of adult mouse prostate progenitors to glandular identity, epithelial barrier integrity, and ultimately, proper specification of the prostatic lumen. Mechanistically, RA-dependent RARγ activation promotes the expression of the pioneer factor Foxa1, which synergizes with the androgen pathway for proper luminal expansion, cytoarchitecture and function. FOXA1 nucleotide variants are common in human prostate and breast cancers and considered driver mutations, though their pathogenic mechanism is incompletely understood. Combining functional genetics experiments with structural modeling of FOXA1 folding and chromatin binding analyses, we discovered that FOXA1 F254E255 is a loss-of-function mutation leading to compromised transcriptional function and lack of luminal fate commitment of prostate progenitors. Overall, we define RA as a crucial instructive signal for glandular identity in adult prostate progenitors. We propose deregulation of vitamin A metabolism as a risk factor for benign and malignant prostate disease, and identified cancer associated FOXA1 indels affecting residue F254 as loss-of-function mutations promoting dedifferentiation of adult prostate progenitors. Summary: Retinoic acid signaling orchestrates luminal differentiation of adult prostate progenitors.

Increased genomic instability and reshaping of tissue microenvironment underlie oncogenic properties of Arid1a mutations.

Oncogenic mutations accumulating in many chromatin-associated proteins have been identified in different tumor types. With a mutation rate from 10 to 57%, ARID1A has been widely considered a tumor suppressor gene. However, whether this role is mainly due to its transcriptional-related activities or its ability to preserve genome integrity is still a matter of intense debate. Here, we show that ARID1A is largely dispensable for preserving enhancer-dependent transcriptional regulation, being ARID1B sufficient and required to compensate for ARID1A loss. We provide in vivo evidence that ARID1A is mainly required to preserve genomic integrity in adult tissues. ARID1A loss primarily results in DNA damage accumulation, interferon type I response activation, and chronic inflammation leading to tumor formation. Our data suggest that in healthy tissues, the increased genomic instability that follows ARID1A mutations and the selective pressure imposed by the microenvironment might result in the emergence of aggressive, possibly immune-resistant, tumors.

Analysis of Genetic Ancestry from NGS Data Using EthSEQ.

Next-generation sequencing (NGS) is widely utilized both in translational cancer genomics studies and in the setting of precision medicine. Identification and stratification of an individual's ancestry is fundamental for the correct interpretation of genetic and genomic profiling. EthSEQ provides an easy and effective computational workflow to determine the ancestry of individuals, exploiting single nucleotide polymorphism genotypes computed from NGS data of whole-exome and targeted sequencing experiments. Genotypes are determined by EthSEQ from sequencing alignment files (BAM files) or can be provided as input in Variant Call Format (VCF) or CoreArray Genomic Data Structure (GDS) format. Ancestry is determined and assigned to individuals by EthSEQ exploiting a reference model and a standard or multi-step refinement approach based on Principal Component Analysis (PCA). A complete and detailed set of textual and graphical output files are generated by EthSEQ as result. EthSEQ is easy to use and can be integrated into any NGS-based processing pipeline also exploiting multi-core capabilities. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Perform ancestry analysis using a pre-computed reference model Alternate Protocol: Perform ancestry analysis using a user-specified GDS file as reference model Basic Protocol 2: Perform ancestry analysis using multi-step refinement Support Protocol 1: Create a reference model from multiple VCF genotype data files Support Protocol 2: Create VCF genotype data files from a BAM file.

Divergent HLA variations and heterogeneous expression but recurrent HLA loss-of- heterozygosity and common HLA-B and TAP transcriptional silencing across advanced pediatric solid cancers.

The human leukocyte antigen (HLA) system is a major factor controlling cancer immunosurveillance and response to immunotherapy, yet its status in pediatric cancers remains fragmentary. We determined high-confidence HLA genotypes in 576 children, adolescents and young adults with recurrent/refractory solid tumors from the MOSCATO-01 and MAPPYACTS trials, using normal and tumor whole exome and RNA sequencing data and benchmarked algorithms. There was no evidence for narrowed HLA allelic diversity but discordant homozygosity and allele frequencies across tumor types and subtypes, such as in embryonal and alveolar rhabdomyosarcoma, neuroblastoma MYCN and 11q subtypes, and high-grade glioma, and several alleles may represent protective or susceptibility factors to specific pediatric solid cancers. There was a paucity of somatic mutations in HLA and antigen processing and presentation (APP) genes in most tumors, except in cases with mismatch repair deficiency or genetic instability. The prevalence of loss-of-heterozygosity (LOH) ranged from 5.9 to 7.7% in HLA class I and 8.0 to 16.7% in HLA class II genes, but was widely increased in osteosarcoma and glioblastoma (~15-25%), and for DRB1-DQA1-DQB1 in Ewing sarcoma (~23-28%) and low-grade glioma (~33-50%). HLA class I and HLA-DR antigen expression was assessed in 194 tumors and 44 patient-derived xenografts (PDXs) by immunochemistry, and class I and APP transcript levels quantified in PDXs by RT-qPCR. We confirmed that HLA class I antigen expression is heterogeneous in advanced pediatric solid tumors, with class I loss commonly associated with the transcriptional downregulation of HLA-B and transporter associated with antigen processing (TAP) genes, whereas class II antigen expression is scarce on tumor cells and occurs on immune infiltrating cells. Patients with tumors expressing sufficient HLA class I and TAP levels such as some glioma, osteosarcoma, Ewing sarcoma and non-rhabdomyosarcoma soft-tissue sarcoma cases may more likely benefit from T cell-based approaches, whereas strategies to upregulate HLA expression, to expand the immunopeptidome, and to target TAP-independent epitopes or possibly LOH might provide novel therapeutic opportunities in others. The consequences of HLA class II expression by immune cells remain to be established. Immunogenetic profiling should be implemented in routine to inform immunotherapy trials for precision medicine of pediatric cancers.

LSD1/PRMT6-targeting gene therapy to attenuate androgen receptor toxic gain-of-function ameliorates spinobulbar muscular atrophy phenotypes in flies and mice.

Spinobulbar muscular atrophy (SBMA) is caused by CAG expansions in the androgen receptor gene. Androgen binding to polyQ-expanded androgen receptor triggers SBMA through a combination of toxic gain-of-function and loss-of-function mechanisms. Leveraging cell lines, mice, and patient-derived specimens, we show that androgen receptor co-regulators lysine-specific demethylase 1 (LSD1) and protein arginine methyltransferase 6 (PRMT6) are overexpressed in an androgen-dependent manner specifically in the skeletal muscle of SBMA patients and mice. LSD1 and PRMT6 cooperatively and synergistically transactivate androgen receptor, and their effect is enhanced by expanded polyQ. Pharmacological and genetic silencing of LSD1 and PRMT6 attenuates polyQ-expanded androgen receptor transactivation in SBMA cells and suppresses toxicity in SBMA flies, and a preclinical approach based on miRNA-mediated silencing of LSD1 and PRMT6 attenuates disease manifestations in SBMA mice. These observations suggest that targeting overexpressed co-regulators can attenuate androgen receptor toxic gain-of-function without exacerbating loss-of-function, highlighting a potential therapeutic strategy for patients with SBMA.