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.

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.

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.

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.

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.

Unassigned MS/MS Spectra: Who Am I?

Recent advances in high resolution tandem mass spectrometry (MS) has resulted in the accumulation of high quality data. Paralleled with these advances in instrumentation, bioinformatics software have been developed to analyze such quality datasets. In spite of these advances, data analysis in mass spectrometry still remains critical for protein identification. In addition, the complexity of the generated MS/MS spectra, unpredictable nature of peptide fragmentation, sequence annotation errors, and posttranslational modifications has impeded the protein identification process. In a typical MS data analysis, about 60 % of the MS/MS spectra remains unassigned. While some of these could attribute to the low quality of the MS/MS spectra, a proportion can be classified as high quality. Further analysis may reveal how much of the unassigned MS spectra attribute to search space, sequence annotation errors, mutations, and/or posttranslational modifications. In this chapter, the tools used to identify proteins and ways to assign unassigned tandem MS spectra are discussed.

Proteotypic Peptides and Their Applications.

Recent advances in mass spectrometry based proteomic techniques and publicly available large proteomic repositories are being exploited to characterize the proteome of multiple organisms. While humongous amount of proteomic data is being acquired and analyzed, many biological questions still remain unanswered. Proteotypic peptides which uniquely represent target proteins or a protein isoform are used as an alternative strategy for protein identification in the field of immunological methods and targeted proteomic techniques. Using different computational approaches, resources and techniques used in the identification of proteotypic peptides of target proteins is discussed here.

Colorectal cancer atlas: An integrative resource for genomic and proteomic annotations from colorectal cancer cell lines and tissues.

In order to advance our understanding of colorectal cancer (CRC) development and progression, biomedical researchers have generated large amounts of OMICS data from CRC patient samples and representative cell lines. However, these data are deposited in various repositories or in supplementary tables. A database which integrates data from heterogeneous resources and enables analysis of the multidimensional data sets, specifically pertaining to CRC is currently lacking. Here, we have developed Colorectal Cancer Atlas (http://www.colonatlas.org), an integrated web-based resource that catalogues the genomic and proteomic annotations identified in CRC tissues and cell lines. The data catalogued to-date include sequence variations as well as quantitative and non-quantitative protein expression data. The database enables the analysis of these data in the context of signaling pathways, protein-protein interactions, Gene Ontology terms, protein domains and post-translational modifications. Currently, Colorectal Cancer Atlas contains data for >13 711 CRC tissues, >165 CRC cell lines, 62 251 protein identifications, >8.3 million MS/MS spectra, >18 410 genes with sequence variations (404 278 entries) and 351 pathways with sequence variants. Overall, Colorectal Cancer Atlas has been designed to serve as a central resource to facilitate research in CRC.

Proteogenomic analysis reveals exosomes are more oncogenic than ectosomes.

Extracellular vesicles (EVs) include the exosomes (30-100 nm) that are produced through the endocytic pathway via the multivesicular bodies and the ectosomes (100-1000 nm) that are released through the budding of the plasma membrane. Despite the differences in the mode of biogenesis and size, reliable markers that can distinguish between exosomes and ectosomes are non-existent. Moreover, the precise functional differences between exosomes and ectosomes remains poorly characterised. Here, using label-free quantitative proteomics, we highlight proteins that could be exploited as markers to discriminate between exosomes and ectosomes. For the first time, a global proteogenomics analysis unveiled the secretion of mutant proteins that are implicated in cancer progression through tumor-derived EVs. Follow up integrated bioinformatics analysis highlighted the enrichment of oncogenic cargo in exosomes and ectosomes. Interestingly, exosomes induced significant cell proliferation and migration in recipient cells compared to ectosomes confirming the oncogenic nature of exosomes. These findings ascertain that cancer cells facilitate oncogenesis by the secretion of mutant and oncoproteins into the tumor microenvironment via exosomes and ectosomes. The integrative proteogenomics approach utilized in this study has the potential to identify disease biomarker candidates which can be later assayed in liquid biopsies obtained from cancer patients.

Inhibition of cathepsin proteases attenuates migration and sensitizes aggressive N-Myc amplified human neuroblastoma cells to doxorubicin.

Neuroblastoma arises from the sympathetic nervous system and accounts for 15% of childhood cancer mortality. Amplification of the oncogene N-Myc is reported to occur in more than 20% of patients. While N-Myc amplification status strongly correlates with higher tumour aggression and resistance to treatment, the role of N-Myc in the aggressive progression of the disease is poorly understood. N-Myc being a transcription factor can modulate the secretion of key proteins that may play a pivotal role in tumorigenesis. Characterising the soluble secreted proteins or secretome will aid in understanding their role in the tumour microenvironment, such as promoting cancer cell invasion and resistance to treatment. The aim of this study is to characterise the secretome of human malignant neuroblastoma SK-N-BE2 (N-Myc amplified, more aggressive) and SH-SY5Y (N-Myc non-amplified, less aggressive) cells. Conditioned media from SK-N-BE2 and SH-SY5Y cell lines were subjected to proteomics analysis. We report a catalogue of 894 proteins identified in the secretome isolated from the two neuroblastoma cell lines, SK-N-BE2 and SH-SY5Y. Functional enrichment analysis using FunRich software identified enhanced secretion of proteins implicated in cysteine peptidase activity in the aggressive N-Myc amplified SK-N-BE2 secretome compared to the less tumorigenic SH-SY5Y cells. Protein-protein interaction-based network analysis highlighted the enrichment of cathepsin and epithelial-to-mesenchymal transition sub-networks. For the first time, inhibition of cathepsins by inhibitors sensitized the resistant SK-N-BE2 cells to doxorubicin as well as decreased its migratory potential. The dataset of secretome proteins of N-Myc amplified (more aggressive) and non-amplified (less aggressive) neuroblastoma cells represent the first inventory of neuroblastoma secretome. The study also highlights the prominent role of cathepsins in the N-Myc amplified neuroblastoma pathogenesis. As N-Myc amplification correlates with aggressive neuroblastoma and chemotherapy-based treatment failure, co-treatment with cathepsin inhibitors might be a better avenue for disease management.

Evaluation of protein expression pattern of stanniocalcin 2, insulin-like growth factor-binding protein 7, inhibin beta A and four and a half LIM domains 1 in esophageal squamous cell carcinoma.

The pathogenesis of esophageal squamous cell carcinoma (ESCC) involves both genetic and environmental factors. Previously, we have carried out gene and protein expression profiling of ESCC using DNA microarrays and mass spectrometry-based quantitative proteomics, respectively. These studies resulted in identification of several potential biomarkers of ESCC, some with known reports of differential expression in the scientific literature and others that were novel observations from our studies. We report systematic validation of selected markers from our studies on a larger cohort of cancer tissue sections by immunohistochemical labeling of tissue microarrays. We have validated expression of insulin-like growth factor-binding protein 7 (IGFBP7), stanniocalcin 2 (STC2), inhibin beta A (INHBA) and four and a half LIM domains 1 (FHL1). Immunohistochemical labeling with anti-stanniocalcin 2 antibody demonstrated its overexpression in 132/140 (94%) cases, IGFBP7 showed overexpression in 127/140 (91%) cases and overexpression of INHBA was observed in 62/105 (59%) of ESCC cases. In contrast, FHL1 expression was observed only in 12/143 (8%) of ESCC cases suggesting its possible involvement in tumor suppression. These data suggest that IGFBP7, INHBA, STC2 and FHL1 might play an important role in ESCC tumorigenesis, which can be explored in future studies. Overall, our findings open up new avenues for development of novel therapeutics and/or diagnostic approaches in ESCC.

Comprehensive proteomic analysis of human bile.

Bile serves diverse functions from metabolism to transport. In addition to acids and salts, bile is composed of proteins secreted or shed by the hepatobiliary system. Although there have been previous efforts to catalog biliary proteins, an in-depth analysis of the bile proteome has not yet been reported. We carried out fractionation of non-cancerous bile samples using a multipronged approach (SDS-PAGE, SCX and OFFGEL) followed by MS analysis on an LTQ-Orbitrap Velos mass spectrometer using high resolution at both MS and MS/MS levels. We identified 2552 proteins - the largest number of proteins reported in human bile till date. To our knowledge, there are no previous studies employing high-resolution MS reporting a more detailed catalog of any body fluid proteome in a single study. We propose that extensive fractionation coupled to high-resolution MS can be used as a standard methodology for in-depth characterization of any body fluid. This catalog should serve as a baseline for the future studies aimed at discovering biomarkers from bile in gallbladder, hepatic, and biliary cancers.