Comparative proteomic profiling of uric acid, ammonium acid urate, and calcium-based kidney stones.

INTRODUCTION: Kidney stone matrix proteins may help explain cellular mechanisms of stone genesis. However, most existing proteomic studies have focused on calcium oxalate stones. Here, we present a comparative proteomic analysis of different kidney stone types. METHODS: Proteins were extracted from the stones of patients undergoing percutaneous nephrolithotomy (PCNL). Approximately 20 µg of protein was digested into tryptic peptides using filter aided sample preparation, followed by liquid chromatography tandem-mass-spectrometry using an EASY-nLC 1200 and Orbitrap Fusion Lumos mass spectrometer. A standard false discovery rate cutoff of 1% was used for protein identification. Stone analysis was used to organize stone samples into similar groups. We selected the top 5% of proteins based on total ion intensities and used DAVID and Ingenuity Pathway Analysis to identify and compare significantly enriched gene ontologies and pathways between groups. RESULTS: Six specimens were included and organized into the following four groups: 1) mixed uric acid (UA) and calcium-based, 2) pure UA, 3) pure ammonium acid urate (AAU), and 4) pure calcium-based. We identified 2,426 unique proteins (1,310-1,699 per sample), with 11-16 significantly enriched KEGG pathways identified per group and compared via heatmap. Based on number of unique proteins identified, this is the deepest proteomic study of kidney stones to date and the first such study of an AAU stone. CONCLUSIONS: The results indicate that mixed UA and calcium-based kidney stones are more similar to pure UA stones than pure calcium-based stones. AAU stones appear more similar to pure calcium-based stones than UA containing stones and may be related to parasitic infections. Further research with larger cohorts and histopathologic correlation is warranted.

Non-Coding RNAs Set a New Phenotypic Frontier in Prostate Cancer Metastasis and Resistance.

Prostate cancer (PCa) mortality remains a significant public health problem, as advanced disease has poor survivability due to the development of resistance in response to both standard and novel therapeutic interventions. Therapeutic resistance is a multifaceted problem involving the interplay of a number of biological mechanisms including genetic, signaling, and phenotypic alterations, compounded by the contributions of a tumor microenvironment that supports tumor growth, invasiveness, and metastasis. The androgen receptor (AR) is a primary regulator of prostate cell growth, response and maintenance, and the target of most standard PCa therapies designed to inhibit AR from interacting with androgens, its native ligands. As such, AR remains the main driver of therapeutic response in patients with metastatic castration-resistant prostate cancer (mCRPC). While androgen deprivation therapy (ADT), in combination with microtubule-targeting taxane chemotherapy, offers survival benefits in patients with mCRPC, therapeutic resistance invariably develops, leading to lethal disease. Understanding the mechanisms underlying resistance is critical to improving therapeutic outcomes and also to the development of biomarker signatures of predictive value. The interconversions between epithelial-to-mesenchymal transition (EMT) and mesenchymal-to-epithelial transition (MET) navigate the prostate tumor therapeutic response, and provide a novel targeting platform in overcoming therapeutic resistance. Both microRNA (miRNA)- and long non-coding RNA (lncRNA)-mediated mechanisms have been associated with epigenetic changes in prostate cancer. This review discusses the current evidence-based knowledge of the role of the phenotypic transitions and novel molecular determinants (non-coding RNAs) as contributors to the emergence of therapeutic resistance and metastasis and their integrated predictive value in prostate cancer progression to advanced disease.

Pseudouridine as a novel biomarker in prostate cancer.

Epitranscriptomic analysis has recently led to the profiling of modified nucleosides in cancer cell biological matrices, helping to elucidate their functional roles in cancer and reigniting interest in exploring their use as potential markers of cancer development and progression. Pseudouridine, one of the most well-known and the most abundant of the RNA nucleotide modifications, is the C5-glycoside isomer of uridine and its distinctive physiochemical properties allows it to perform many essential functions. Pseudouridine functionally (a) confers rigidity to local RNA structure by enhancing RNA stacking, engaging in a cooperative effect on neighboring nucleosides that overall contributes to RNA stabilization (b) refines the structure of tRNAs, which influences their decoding activity (c) facilitates the accuracy of decoding and proofreading during translation and efficiency of peptide bond formation, thus collectively improving the fidelity of protein biosynthesis and (e) dynamically regulates mRNA coding and translation. Biochemical synthesis of pseudouridine is carried out by pseudouridine synthases. In this review we discuss the evidence supporting an association between elevated pseudouridine levels with the incidence and progression of human prostate cancer and the translational significance of the value of this modified nucleotide as a novel biomarker in prostate cancer progression to advanced disease.

Predictive value of pseudouridine in prostate cancer.

BACKGROUND: Recent studies have shown that certain small nucleolar RNAs (H/ACA snoRNAs) and the protein dyskerin (DKC1) are upregulated in prostate cancer and are thought to contribute to progression of disease. These components convert uridine to pseudouridine (abbreviated ψ), a type of post-transcriptional modification of RNA. Given the increased abundance of H/ACA snoRNAs and expression of DKC1 in prostate carcinomas, and because whole-body turnover of RNA increases in support of rapidly-growing cancer cells, we examined the value of pseudouridine as a biomarker for prostate cancer. METHODS: Using a monoclonal antibody against pseudouridine, we tested its ability to distinguish between two 25-base RNA oligonucleotide sequences that differed by only one ψ-substitution, and subsequently measured ψ in RNA isolated from several prostate cancer cell lines representing different stages of disease using dot blot assays and pseudouridinylated RNA linked immunosorbent assay (PURLISA). We also performed immunohistochemistry on a tissue micro array (12 cases/24 cores) containing prostate adenocarcinomas and normal adjacent tissue (NAT). RESULTS: High levels of pseudouridine were detected in androgen-independent cell lines (PC3 and Du145) compared to androgen-sensitive (LNCaP) and immortalized human prostate (RWPE) cells. Immunohistochemistry of a tissue micro array (TMA) containing normal adjacent and cancerous prostate tissue revealed a significant difference in immunoreactivity between normal and malignant tissue (P ≤ 0.0001). CONCLUSION: Our results provide new information on the relationship between pseudouridine expression and clinical progression of prostate cancer.

Inflammation and Prostate Cancer.

Chronic inflammation resulting from infections, altered metabolism, inflammatory diseases or other environmental factors can be a major contributor to the development of several types of cancer. In fact around 20% of all cancers are linked to some form of inflammation. Evidence gathered from genetic, epidemiological and molecular pathological studies suggest that inflammation plays a crucial role at various stages of prostatic carcinogenesis and tumor progression. These include initiation, promotion, malignant conversion, invasion, and metastasis. Detailed basic and clinical research in these areas, focused towards understanding the etiology of prostatic inflammation, as well as the exact roles that various signaling pathways play in promoting tumor growth, is critical for understanding this complex process. The information gained would be useful in developing novel therapeutic strategies such as molecular targeting of inflammatory mediators and immunotherapy-based approaches.

Intratumor heterogeneity in prostate cancer.

Prostate cancer (PCa) has long been thought of as a disease with a heterogeneous phenotype. It can manifest in men as benign growths that can be safely watched or as more aggressive malignancies that can prove fatal. Recent investigations at the genomic, histopathological and molecular levels have identified tumor heterogeneity, the phenomenon of individual tumor cells presenting distinct genomic and phenotypic characteristics, as one of the most confounding and complex factors underlying PCa diagnosis, prognosis, and treatment. Despite tremendous progress made over the course of the last decade we still have an incomplete understanding of the extent and effect of intra- and inter-tumoral heterogeneity in the course of PCa progression. For example, a primary tumor can be classified into one of several molecular subgroups depending on whether the cancer has a particular gene fusion or a mutation which in turn might yield some patient-specific therapeutic regimen, but this same type of heterogeneous growth can be spatially or temporally restricted proving it difficult to detect during biopsy. We therefore present here a comprehensive review of the various studies addressing intra-tumor heterogeneity in PCa and in the context of that seen in other solid tumors. We discuss the impact of heterogeneity on clinical decision-making in treating both primary and metastatic lesions and how our understanding of this heterogeneity might help in developing better diagnostic tools and biomarkers and in guiding the selection of better therapeutic strategies.

Induction of Neuroendocrine Differentiation in Prostate Cancer Cells by Dovitinib (TKI-258) and its Therapeutic Implications.

Prostate cancer (PCa) remains the second-leading cause of cancer-related deaths in American men with an estimated mortality of more than 26,000 in 2016 alone. Aggressive and metastatic tumors are treated with androgen deprivation therapies (ADT); however, the tumors acquire resistance and develop into lethal castration resistant prostate cancer (CRPC). With the advent of better therapeutics, the incidences of a more aggressive neuroendocrine prostate cancer (NEPC) variant continue to emerge. Although de novo occurrences of NEPC are rare, more than 25% of the therapy-resistant patients on highly potent new-generation anti-androgen therapies end up with NEPC. This, along with previous observations of an increase in the number of such NE cells in aggressive tumors, has been suggested as a mechanism of resistance development during prostate cancer progression. Dovitinib (TKI-258/CHIR-258) is a pan receptor tyrosine kinase (RTK) inhibitor that targets VEGFR, FGFR, PDGFR, and KIT. It has shown efficacy in mouse-model of PCa bone metastasis, and is presently in clinical trials for several cancers. We observed that both androgen receptor (AR) positive and AR-negative PCa cells differentiate into a NE phenotype upon treatment with Dovitinib. The NE differentiation was also observed when mice harboring PC3-xenografted tumors were systemically treated with Dovitinib. The mechanistic underpinnings of this differentiation are unclear, but seem to be supported through MAPK-, PI3K-, and Wnt-signaling pathways. Further elucidation of the differentiation process will enable the identification of alternative salvage or combination therapies to overcome the potential resistance development.

Combination effect of therapies targeting the PI3K- and AR-signaling pathways in prostate cancer.

Several promising targeted-therapeutics for prostate cancer (PCa), primarily affecting the androgen receptor (AR) and the PI3K/AKT/mTOR-pathway, are in various phases of development. However, despite promise, single-agent inhibitors targeting the two pathways have not shown long-term benefits, perhaps due to a complex compensatory cross talk that exists between the two pathways. Combination therapy has thus been proposed to maximize benefit. We have carried out a systematic study of two-drug combination effect of MDV3100 (AR antagonist), BKM120 (PI3K inhibitor), TKI258 (pan RTK inhibitor) and RAD001 (mTOR inhibitor) using various PCa cell lines. We observed strong synergy when AR-positive cells are treated with MDV3100 in combination with any one of the PI3K-pathway inhibitors: TKI258, BKM120, or RAD001. Growth curve based synergy determination combined with Western blot analysis suggested MDV3100+BKM120 to be the most effective in inducing cell death in such conditions. In the case of dual targeting of the PI3K-pathway BKM120+TKI258 combination displayed exquisite sensitivity in all the 5 cell lines tested irrespective of androgen sensitivity, (LNCaP, VCaP, 22Rv1, PC3 and Du145). The effect of blockade with BKM120+TKI258 in PC3 cells was similar to a combination of BKM120 with chemotherapy drug cabazitaxel.Taken together, our observation supports earlier observations that a combination of AR-inhibitor and PI3K-inhibitor is highly synergistic. Furthermore, combining BKM120 with TKI258 has better synergy than BKM120+RAD001 or RAD001+TKI258 in all the lines, irrespective of androgen sensitivity. Finally, BKM120 also displayed synergy when combined with chemotherapy drug cabazitaxel. No antagonism however was observed with any of the drug combinations.

Identification of a small-molecule ligand that activates the neuropeptide receptor GPR171 and increases food intake.

Several neuropeptide systems in the hypothalamus, including neuropeptide Y and agouti-related protein (AgRP), control food intake. Peptides derived from proSAAS, a precursor implicated in the regulation of body weight, also control food intake. GPR171 is a heterotrimeric guanine nucleotide-binding protein (G protein)-coupled receptor (GPCR) for BigLEN (b-LEN), a peptide derived from proSAAS. To facilitate studies exploring the physiological role of GPR171, we sought to identify small-molecule ligands for this receptor by performing a virtual screen of a compound library for interaction with a homology model of GPR171. We identified MS0015203 as an agonist of GPR171 and demonstrated the selectivity of MS0015203 for GPR171 by testing the binding of this compound to 80 other membrane proteins, including family A GPCRs. Reducing the expression of GPR171 by shRNA (short hairpin RNA)-mediated knockdown blunted the cellular and tissue response to MS0015203. Peripheral injection of MS0015203 into mice increased food intake and body weight, and these responses were significantly attenuated in mice with decreased expression of GPR171 in the hypothalamus. Together, these results suggest that MS0015203 is a useful tool to probe the pharmacological and functional properties of GPR171 and that ligands targeting GPR171 may eventually lead to therapeutics for food-related disorders.

Advancements in therapeutically targeting orphan GPCRs.

G-protein coupled receptors (GPCRs) are popular biological targets for drug discovery and development. To date there are more than 140 orphan GPCRs, i.e., receptors whose endogenous ligands are unknown. Traditionally orphan GPCRs have been difficult to study and the development of therapeutic compounds targeting these receptors has been extremely slow although these GPCRs are considered important targets based on their distribution and behavioral phenotype as revealed by animals lacking the receptor. Recent advances in several methods used to study orphan receptors, including protein crystallography and homology modeling are likely to be useful in the identification of therapeutics targeting these receptors. In the past 13 years, over a dozen different Class A GPCRs have been crystallized; this trend is exciting, since homology modeling of GPCRs has previously been limited by the availability of solved structures. As the number of solved GPCR structures continues to grow so does the number of templates that can be used to generate increasingly accurate models of phylogenetically related orphan GPCRs. The availability of solved structures along with the advances in using multiple templates to build models (in combination with molecular dynamics simulations that reveal structural information not provided by crystallographic data and methods for modeling hard-to-predict flexible loop regions) have improved the quality of GPCR homology models. This, in turn, has improved the success rates of virtual ligand screens that use homology models to identify potential receptor binding compounds. Experimental testing of the predicted hits and validation using traditional GPCR pharmacological approaches can be used to drive ligand-based efforts to probe orphan receptor biology as well as to define the chemotypes and chemical scaffolds important for binding. As a result of these advances, orphan GPCRs are emerging from relative obscurity as a new class of drug targets.