Co-targeting BET, CBP, and p300 inhibits neuroendocrine signalling in androgen receptor-null prostate cancer.

There are diverse phenotypes of castration-resistant prostate cancer, including neuroendocrine disease, that vary in their sensitivity to drug treatment. The efficacy of BET and CBP/p300 inhibitors in prostate cancer is attributed, at least in part, to their ability to decrease androgen receptor (AR) signalling. However, the activity of BET and CBP/p300 inhibitors in prostate cancers that lack the AR is unclear. In this study, we showed that BRD4, CBP, and p300 were co-expressed in AR-positive and AR-null prostate cancer. A combined inhibitor of these three proteins, NEO2734, reduced the growth of both AR-positive and AR-null organoids, as measured by changes in viability, size, and composition. NEO2734 treatment caused consistent transcriptional downregulation of cell cycle pathways. In neuroendocrine models, NEO2734 treatment reduced ASCL1 levels and other neuroendocrine markers, and reduced tumour growth in vivo. Collectively, these results show that epigenome-targeted inhibitors cause decreased growth and phenotype-dependent disruption of lineage regulators in neuroendocrine prostate cancer, warranting further development of compounds with this activity in the clinic. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Multi-substrate Metabolic Tracing Reveals Marked Heterogeneity and Dependency on Fatty Acid Metabolism in Human Prostate Cancer.

Cancer cells undergo metabolic reprogramming to meet increased bioenergetic demands. Studies in cells and mice have highlighted the importance of oxidative metabolism and lipogenesis in prostate cancer; however, the metabolic landscape of human prostate cancer remains unclear. To address this knowledge gap, we performed radiometric (14C) and stable (13C) isotope tracing assays in precision-cut slices of patient-derived xenografts (PDX). Glucose, glutamine, and fatty acid oxidation was variably upregulated in malignant PDXs compared with benign PDXs. De novo lipogenesis (DNL) and storage of free fatty acids into phospholipids and triacylglycerols were increased in malignant PDXs. There was no difference in substrate utilization between localized and metastatic PDXs and hierarchical clustering revealed marked metabolic heterogeneity across all PDXs. Mechanistically, glucose utilization was mediated by acetyl-CoA production rather than carboxylation of pyruvate, while glutamine entered the tricarboxylic acid cycle through transaminase reactions before being utilized via oxidative or reductive pathways. Blocking fatty acid uptake or fatty acid oxidation with pharmacologic inhibitors was sufficient to reduce cell viability in PDX-derived organoids, whereas blockade of DNL, or glucose or glutamine oxidation induced variable and limited therapeutic efficacy. These findings demonstrate that human prostate cancer, irrespective of disease stage, can effectively utilize all metabolic substrates, albeit with marked heterogeneity across tumors. We also confirm that fatty acid uptake and oxidation are targetable metabolic dependencies in human prostate cancer. IMPLICATIONS: Prostate cancer utilizes multiple substrates to fuel energy requirements, yet pharmacologic targeting of fatty acid uptake and oxidation reveals metabolic dependencies in localized and metastatic tumors.

The MURAL collection of prostate cancer patient-derived xenografts enables discovery through preclinical models of uro-oncology.

Preclinical testing is a crucial step in evaluating cancer therapeutics. We aimed to establish a significant resource of patient-derived xenografts (PDXs) of prostate cancer for rapid and systematic evaluation of candidate therapies. The PDX collection comprises 59 tumors collected from 30 patients between 2012-2020, coinciding with availability of abiraterone and enzalutamide. The PDXs represent the clinico-pathological and genomic spectrum of prostate cancer, from treatment-naïve primary tumors to castration-resistant metastases. Inter- and intra-tumor heterogeneity in adenocarcinoma and neuroendocrine phenotypes is evident from bulk and single-cell RNA sequencing data. Organoids can be cultured from PDXs, providing further capabilities for preclinical studies. Using a 1 x 1 x 1 design, we rapidly identify tumors with exceptional responses to combination treatments. To govern the distribution of PDXs, we formed the Melbourne Urological Research Alliance (MURAL). This PDX collection is a substantial resource, expanding the capacity to test and prioritize effective treatments for prospective clinical trials in prostate cancer.

Oral administration of bovine milk-derived extracellular vesicles induces senescence in the primary tumor but accelerates cancer metastasis.

The concept that extracellular vesicles (EVs) from the diet can be absorbed by the intestinal tract of the consuming organism, be bioavailable in various organs, and in-turn exert phenotypic changes is highly debatable. Here, we isolate EVs from both raw and commercial bovine milk and characterize them by electron microscopy, nanoparticle tracking analysis, western blotting, quantitative proteomics and small RNA sequencing analysis. Orally administered bovine milk-derived EVs survive the harsh degrading conditions of the gut, in mice, and is subsequently detected in multiple organs. Milk-derived EVs orally administered to mice implanted with colorectal and breast cancer cells reduce the primary tumor burden. Intriguingly, despite the reduction in primary tumor growth, milk-derived EVs accelerate metastasis in breast and pancreatic cancer mouse models. Proteomic and biochemical analysis reveal the induction of senescence and epithelial-to-mesenchymal transition in cancer cells upon treatment with milk-derived EVs. Timing of EV administration is critical as oral administration after resection of the primary tumor reverses the pro-metastatic effects of milk-derived EVs in breast cancer models. Taken together, our study provides context-based and opposing roles of milk-derived EVs as metastasis inducers and suppressors.

Mast Cell-Derived SAMD14 Is a Novel Regulator of the Human Prostate Tumor Microenvironment.

Mast cells (MCs) are important cellular components of the tumor microenvironment and are significantly associated with poor patient outcomes in prostate cancer and other solid cancers. The promotion of tumor progression partly involves heterotypic interactions between MCs and cancer-associated fibroblasts (CAFs), which combine to potentiate a pro-tumor extracellular matrix and promote epithelial cell invasion and migration. Thus far, the interactions between MCs and CAFs remain poorly understood. To identify molecular changes that may alter resident MC function in the prostate tumor microenvironment, we profiled the transcriptome of human prostate MCs isolated from patient-matched non-tumor and tumor-associated regions of fresh radical prostatectomy tissue. Transcriptomic profiling revealed a distinct gene expression profile of MCs isolated from prostate tumor regions, including the downregulation of SAMD14, a putative tumor suppressor gene. Proteomic profiling revealed that overexpression of SAMD14 in HMC-1 altered the secretion of proteins associated with immune regulation and extracellular matrix processes. To assess MC biological function within a model of the prostate tumor microenvironment, HMC-1-SAMD14+ conditioned media was added to co-cultures of primary prostatic CAFs and prostate epithelium. HMC-1-SAMD14+ secretions were shown to reduce the deposition and alignment of matrix produced by CAFs and suppress pro-tumorigenic prostate epithelial morphology. Overall, our data present the first profile of human MCs derived from prostate cancer patient specimens and identifies MC-derived SAMD14 as an important mediator of MC phenotype and function within the prostate tumor microenvironment.

Analytical validation of an error-corrected ultra-sensitive ctDNA next-generation sequencing assay.

Plasma circulating tumor DNA (ctDNA) analysis has emerged as a minimally invasive means to perform molecular tumor typing. Here we developed a custom ultra-sensitive ctDNA next-generation sequencing assay using molecular barcoding technology and off-the-shelf reagents combined with bioinformatics tools for enhanced ctDNA analysis. Assay performance was assessed via a spike-in experiment and the technique was applied to analyze 41 plasma samples from men with advanced prostate cancer. Orthogonal validation was performed using a commercial assay. Sensitivity and specificity of 93 and 99.5% were recorded for ultra-rare somatic variants (<1%), with high concordance observed between the in-house and commercial assays. The optimized protocol dramatically improved the efficiency of the assay and enabled the detection of low-frequency somatic variants from plasma cell-free DNA (cfDNA).

MTOR signaling orchestrates stress-induced mutagenesis, facilitating adaptive evolution in cancer.

In microorganisms, evolutionarily conserved mechanisms facilitate adaptation to harsh conditions through stress-induced mutagenesis (SIM). Analogous processes may underpin progression and therapeutic failure in human cancer. We describe SIM in multiple in vitro and in vivo models of human cancers under nongenotoxic drug selection, paradoxically enhancing adaptation at a competing intrinsic fitness cost. A genome-wide approach identified the mechanistic target of rapamycin (MTOR) as a stress-sensing rheostat mediating SIM across multiple cancer types and conditions. These observations are consistent with a two-phase model for drug resistance, in which an initially rapid expansion of genetic diversity is counterbalanced by an intrinsic fitness penalty, subsequently normalizing to complete adaptation under the new conditions. This model suggests synthetic lethal strategies to minimize resistance to anticancer therapy.

CRISP3 expression drives prostate cancer invasion and progression.

Identifying the factors stimulating prostate cancer cells migration and invasion has the potential to bring new therapeutic targets to the clinic. Cysteine-rich secretory protein 3 (CRISP3) is one of the most highly upregulated proteins during the transition of a healthy human prostatic epithelium to prostate cancer. Here we show using a genetically engineered mouse model of prostate cancer that CRISP3 production greatly facilitates disease progression from carcinoma in situ to invasive prostate cancer in vivo. This interpretation was confirmed using both human and mouse prostate cancer cell lines, which showed that exposure to CRISP3 enhanced cell motility and invasion. Further, using mass spectrometry, we show that CRISP3 induces changes in abundance of a subset of cell-cell adhesion proteins, including LASP1 and TJP1 both in vivo and in vitro. Collectively, these data identify CRISP3 as being pro-tumorigenic in the prostate and validate it as a potential target for therapeutic intervention.

Extracellular vesicles containing oncogenic mutant ß-catenin activate Wnt signalling pathway in the recipient cells.

Mutations in ß-catenin, especially at the residues critical for its degradation, render it constitutively active. Here, we show that mutant ß-catenin can be transported via extracellular vesicles (EVs) and activate Wnt signalling pathway in the recipient cells. An integrative proteogenomic analysis identified the presence of mutated ß-catenin in EVs secreted by colorectal cancer (CRC) cells. Follow-up experiments established that EVs released from LIM1215 CRC cells stimulated Wnt signalling pathway in the recipient cells with wild-type ß-catenin. SILAC-based quantitative proteomics analysis confirmed the transfer of mutant ß-catenin to the nucleus of the recipient cells. In vivo tracking of DiR-labelled EVs in mouse implanted with RKO CRC cells revealed its bio-distribution, confirmed the activation of Wnt signalling pathway in tumour cells and increased the tumour burden. Overall, for the first time, this study reveals that EVs can transfer mutant ß-catenin to the recipient cells and promote cancer progression.

Deletion of intestinal Hdac3 remodels the lipidome of enterocytes and protects mice from diet-induced obesity.

Histone deacetylase 3 (Hdac3) regulates the expression of lipid metabolism genes in multiple tissues, however its role in regulating lipid metabolism in the intestinal epithelium is unknown. Here we demonstrate that intestine-specific deletion of Hdac3 (Hdac3IKO) protects mice from diet induced obesity. Intestinal epithelial cells (IECs) from Hdac3IKO mice display co-ordinate induction of genes and proteins involved in mitochondrial and peroxisomal ß-oxidation, have an increased rate of fatty acid oxidation, and undergo marked remodelling of their lipidome, particularly a reduction in long chain triglycerides. Many HDAC3-regulated fatty oxidation genes are transcriptional targets of the PPAR family of nuclear receptors, Hdac3 deletion enhances their induction by PPAR-agonists, and pharmacological HDAC3 inhibition induces their expression in enterocytes. These findings establish a central role for HDAC3 in co-ordinating PPAR-regulated lipid oxidation in the intestinal epithelium, and identify intestinal HDAC3 as a potential therapeutic target for preventing obesity and related diseases.

Extracellular vesicles secreted by Saccharomyces cerevisiae are involved in cell wall remodelling.

Extracellular vesicles (EVs) are membranous vesicles that are released by cells. In this study, the role of the Endosomal Sorting Complex Required for Transport (ESCRT) machinery in the biogenesis of yeast EVs was examined. Knockout of components of the ESCRT machinery altered the morphology and size of EVs as well as decreased the abundance of EVs. In contrast, strains with deletions in cell wall biosynthesis genes, produced more EVs than wildtype. Proteomic analysis highlighted the depletion of ESCRT components and enrichment of cell wall remodelling enzymes, glucan synthase subunit Fks1 and chitin synthase Chs3, in yeast EVs. Interestingly, EVs containing Fks1 and Chs3 rescued the yeast cells from antifungal molecules. However, EVs from fks1∆ or chs3∆ or the vps23∆chs3∆ double knockout strain were unable to rescue the yeast cells as compared to vps23∆ EVs. Overall, we have identified a potential role for yeast EVs in cell wall remodelling.

Patient-derived Models of Abiraterone- and Enzalutamide-resistant Prostate Cancer Reveal Sensitivity to Ribosome-directed Therapy.

BACKGROUND: The intractability of castration-resistant prostate cancer (CRPC) is exacerbated by tumour heterogeneity, including diverse alterations to the androgen receptor (AR) axis and AR-independent phenotypes. The availability of additional models encompassing this heterogeneity would facilitate the identification of more effective therapies for CRPC. OBJECTIVE: To discover therapeutic strategies by exploiting patient-derived models that exemplify the heterogeneity of CRPC. DESIGN, SETTING, AND PARTICIPANTS: Four new patient-derived xenografts (PDXs) were established from independent metastases of two patients and characterised using integrative genomics. A panel of rationally selected drugs was tested using an innovative ex vivo PDX culture system. INTERVENTION: The following drugs were evaluated: AR signalling inhibitors (enzalutamide and galeterone), a PARP inhibitor (talazoparib), a chemotherapeutic (cisplatin), a CDK4/6 inhibitor (ribociclib), bromodomain and extraterminal (BET) protein inhibitors (iBET151 and JQ1), and inhibitors of ribosome biogenesis/function (RNA polymerase I inhibitor CX-5461 and pan-PIM kinase inhibitor CX-6258). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Drug efficacy in ex vivo cultures of PDX tissues was evaluated using immunohistochemistry for Ki67 and cleaved caspase-3 levels. Candidate drugs were also tested for antitumour efficacy in vivo, with tumour volume being the primary endpoint. Two-tailed t tests were used to compare drug and control treatments. RESULTS AND LIMITATIONS: Integrative genomics revealed that the new PDXs exhibited heterogeneous mechanisms of resistance, including known and novel AR mutations, genomic structural rearrangements of the AR gene, and a neuroendocrine-like AR-null phenotype. Despite their heterogeneity, all models were sensitive to the combination of ribosome-targeting agents CX-5461 and CX-6258. CONCLUSIONS: This study demonstrates that ribosome-targeting drugs may be effective against diverse CRPC subtypes including AR-null disease, and highlights the potential of contemporary patient-derived models to prioritise treatment strategies for clinical translation. PATIENT SUMMARY: Diverse types of therapy-resistant prostate cancers are sensitive to a new combination of drugs that inhibit protein synthesis pathways in cancer cells.

Arrestin-Domain Containing Protein 1 (Arrdc1) Regulates the Protein Cargo and Release of Extracellular Vesicles.

Extracellular vesicles (EVs) are lipid-bilayered vesicles that are released by multiple cell types and contain nucleic acids and proteins. Very little is known about how the cargo is packaged into EVs. Ubiquitination of proteins is a key posttranslational modification that regulates protein stability and trafficking to subcellular compartments including EVs. Recently, arrestin-domain containing protein 1 (Arrdc1), an adaptor for the Nedd4 family of ubiquitin ligases, has been implicated in the release of ectosomes, a subtype of EV that buds from the plasma membrane. However, it is currently unknown whether Arrdc1 can regulate the release of exosomes, a class of EVs that are derived endocytically. Furthermore, it is unclear whether Arrdc1 can regulate the sorting of protein cargo into the EVs. Exosomes and ectosomes are isolated from mouse embryonic fibroblasts isolated from wild type and Arrdc1-deficient (Arrdc1-/- ) mice. Nanoparticle tracking analysis-based EV quantitation shows that Arrdc1 regulates the release of both exosomes and ectosomes. Proteomic analysis highlights the change in protein cargo in EVs upon deletion of Arrdc1. Functional enrichment analysis reveals the enrichment of mitochondrial proteins in ectosomes, while proteins implicated in apoptotic cleavage of cell adhesion proteins and formation of cornified envelope are significantly depleted in exosomes upon knockout of Arrdc1.

Proteomic Profiling of Exosomes Secreted by Breast Cancer Cells with Varying Metastatic Potential.

Cancer cells actively release extracellular vesicles, including exosomes, into the surrounding microenvironment. Exosomes play pleiotropic roles in cancer progression and metastasis, including invasion, angiogenesis, and immune modulation. However, the proteome profile of exosomes isolated from cells with different metastatic potential and the role of these exosomes in driving metastasis remains unclear. Here, we conduct a comparative proteomic analysis of exosomes isolated from several genetically related mouse breast tumor lines with different metastatic propensity. The amount of exosomes produced and the extent of cancer-associated protein cargo vary significantly between nonmetastatic and metastatic cell-derived exosomes. Metastatic cell-derived exosomes contain proteins that promote migration, proliferation, invasion, and angiogenesis while the nonmetastatic cell-derived exosomes contain proteins involved in cell-cell/cell-matrix adhesion and polarity maintenance. The metastatic exosomes contain a distinct set of membrane proteins including Ceruloplasmin and Metadherin which could presumably aid in targeting the primary cancer cells to specific metastatic sites. Hence, it can be concluded that the exosomes contain different protein cargo based on the host cells metastatic properties and can facilitate in the dissemination of the primary tumors to distant sites.

Autotransporter Adhesins in Escherichia coli Pathogenesis.

Most bacteria produce adhesion molecules to facilitate the interaction with host cells and establish successful infections. An important group of bacterial adhesins belong to the autotransporter (AT) superfamily, the largest group of secreted and outer membrane proteins in Gram-negative bacteria. AT adhesins possess diverse functions that facilitate bacterial colonisation, survival and persistence, and as such are often associated with increased bacterial fitness and pathogenic potential. In this review, we will describe AIDA-I type AT adhesins, which comprise the biggest and most diverse group in the AT family. We will focus on Escherichia coli proteins and define general aspects of their biogenesis, distribution, structural properties and key roles in infection.

Bovine milk-derived exosomes from colostrum are enriched with proteins implicated in immune response and growth.

Exosomes are extracellular vesicles secreted by multiple cell types into the extracellular space. They contain cell-state specific cargos which often reflects the (patho)physiological condition of the cells/organism. Milk contains high amounts of exosomes and it is unclear whether their cargo is altered based on the lactation stage of the organism. Here, we isolated exosomes from bovine milk that were obtained at various stages of lactation and examined the content by quantitative proteomics. Exosomes were isolated by OptiPrep density gradient centrifugation from milk obtained from cow after 24, 48 and 72 h post calving. As control, exosomes were also isolated from cows during mid-lactation period which has been referred to as mature milk (MM). Biochemical and biophysical characterization of exosomes revealed the high abundance of exosomes in colostrum and MM samples. Quantitative proteomics analysis highlighted the change in the proteomic cargo of exosomes based on the lactation state of the cow. Functional enrichment analysis revealed that exosomes from colostrum are significantly enriched with proteins that can potentially regulate the immune response and growth. This study highlights the importance of exosomes in colostrum and hence opens up new avenues to exploit these vesicles in the regulation of the immune response and growth.

A novel community driven software for functional enrichment analysis of extracellular vesicles data.

Bioinformatics tools are imperative for the in depth analysis of heterogeneous high-throughput data. Most of the software tools are developed by specific laboratories or groups or companies wherein they are designed to perform the required analysis for the group. However, such software tools may fail to capture "what the community needs in a tool". Here, we describe a novel community-driven approach to build a comprehensive functional enrichment analysis tool. Using the existing FunRich tool as a template, we invited researchers to request additional features and/or changes. Remarkably, with the enthusiastic participation of the community, we were able to implement 90% of the requested features. FunRich enables plugin for extracellular vesicles wherein users can download and analyse data from Vesiclepedia database. By involving researchers early through community needs software development, we believe that comprehensive analysis tools can be developed in various scientific disciplines.

Powerful differential expression analysis incorporating network topology for next-generation sequencing data.

MOTIVATION: RNA-seq has become the technology of choice for interrogating the transcriptome. However, most methods for RNA-seq differential expression (DE) analysis do not utilize prior knowledge of biological networks to detect DE genes. With the increased availability and quality of biological network databases, methods that can utilize this prior knowledge are needed and will offer biologists with a viable, more powerful alternative when analyzing RNA-seq data. RESULTS: We propose a three-state Markov Random Field (MRF) method that utilizes known biological pathways and interaction to improve sensitivity and specificity and therefore reducing false discovery rates (FDRs) when detecting differentially expressed genes from RNA-seq data. The method requires normalized count data (e.g. in Fragments or Reads Per Kilobase of transcript per Million mapped reads (FPKM/RPKM) format) as its input and it is implemented in an R package pathDESeq available from Github. Simulation studies demonstrate that our method outperforms the two-state MRF model for various sample sizes. Furthermore, for a comparable FDR, it has better sensitivity than DESeq, EBSeq, edgeR and NOISeq. The proposed method also picks more top Gene Ontology terms and KEGG pathways terms when applied to real dataset from colorectal cancer and hepatocellular carcinoma studies, respectively. Overall, these findings clearly highlight the power of our method relative to the existing methods that do not utilize prior knowledge of biological network. AVAILABILITY AND IMPLEMENTATION: As an R package at https://github.com/MalathiSIDona/pathDESeq. TO INSTALL THE PACKAGE TYPE: install_github("MalathiSIDona/pathDESeq",build_vignettes = TRUE). After installation, type vignette("pathDESeq") to access the vignette. CONTACT: a.salim@latrobe.edu.au. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

An Introduction to Proteome Bioinformatics.

High-throughput techniques are indispensable for aiding basic and translational research. Among them, recent advances in proteomics techniques have allowed biomedical researchers to characterize the proteome of multiple organisms. This remarkable advancement have been well complemented by proteome bioinformatics methods and tools. Proteome bioinformatics refers to the study and application of informatics in the field of proteomics. This chapter provides an overview of computational strategies, methods, and techniques reported in this book for bioinformatics analysis of protein data. An outline of many bioinformatics tools, databases, and proteomic techniques described in each of the chapters is given here.

Proteomic Data Storage and Sharing.

With the advent of high-throughput genomic and proteomic techniques, there is a massive amount of multidimensional data being generated and has increased several orders of magnitude. But the amount of data that is cataloged in the central repositories and shared publicly with the scientific community does not correlate the same rate at which the data is generated. Here, in this chapter, we discuss various proteomics data repositories that are freely accessible to the researchers for further downstream meta-analysis.