Metabolomic Heterogeneity of Urogenital Tract Cancers Analyzed by Complementary Chromatographic Techniques Coupled with Mass Spectrometry

lncRNA Profiling of Exosomes and Its Communication Role in Regulating Silica-Stimulated Macrophage Apoptosis and Fibroblast Activation

Long-term silica particle exposure leads to interstitial pulmonary inflammation and fibrosis, called silicosis. Silica-activated macrophages secrete a wide range of cytokines resulting in persistent inflammation. In addition, silica-stimulated activation of fibroblast is another checkpoint in the progression of silicosis. The pathogenesis after silica exposure is complex, involving intercellular communication and intracellular signaling pathway transduction, which was ignored previously. Exosomes are noteworthy because of their crucial role in intercellular communication by delivering bioactive substances, such as lncRNA. However, the expression profile of exosomal lncRNA in silicosis has not been reported yet. In this study, exosomes were isolated from the peripheral serum of silicosis patients or healthy donors. The exosomal lncRNAs were profiled using high-throughput sequencing technology. Target genes were predicted, and functional annotation was performed using differentially expressed lncRNAs. Eight aberrant expressed exosomal lncRNAs were considered to play a key role in the process of silicosis according to the OPLS-DA. Furthermore, the increased expression of lncRNA MSTRG.43085.16 was testified in vitro. Its target gene PARP1 was critical in regulating apoptosis based on bioinformatics analysis. In addition, the effects of exosomes on macrophage apoptosis and fibroblast activation were checked based on a co-cultured system. Our findings suggested that upregulation of lncRNA MSTRG.43085.16 could regulate silica-induced macrophage apoptosis through elevating PARP1 expression, and promote fibroblast activation, implying that the exosomal lncRNA MSTRG.43085.16 might have potential as a biomarker for the early diagnosis of silicosis.

Tumor microbiome - an integral part of the tumor microenvironment

The tumor microenvironment (TME) plays a significant role in tumor progression and cancer cell survival. Besides malignant cells and non-malignant components, including immune cells, elements of the extracellular matrix, stromal cells, and endothelial cells, the tumor microbiome is considered to be an integral part of the TME. Mounting evidence from preclinical and clinical studies evaluated the presence of tumor type-specific intratumoral bacteria. Differences in microbiome composition between cancerous tissues and benign controls suggest the importance of the microbiome-based approach. Complex host-microbiota crosstalk within the TME affects tumor cell biology via the regulation of oncogenic pathways, immune response modulation, and interaction with microbiota-derived metabolites. Significantly, the involvement of tumor-associated microbiota in cancer drug metabolism highlights the therapeutic implications. This review aims to summarize current knowledge about the emerging role of tumor microbiome in various types of solid malignancies. The clinical utility of tumor microbiome in cancer progression and treatment is also discussed. Moreover, we provide an overview of clinical trials evaluating the role of tumor microbiome in cancer patients. The research focusing on the communication between the gut and tumor microbiomes may bring new opportunities for targeting the microbiome to increase the efficacy of cancer treatment and improve patient outcomes.

Metabolic Phenotyping in Prostate Cancer Using Multi-Omics Approaches

Prostate cancer (PCa), one of the most frequently diagnosed cancers among men worldwide, is characterized by a diverse biological heterogeneity. It is well known that PCa cells rewire their cellular metabolism to meet the higher demands required for survival, proliferation, and invasion. In this context, a deeper understanding of metabolic reprogramming, an emerging hallmark of cancer, could provide novel opportunities for cancer diagnosis, prognosis, and treatment. In this setting, multi-omics data integration approaches, including genomics, epigenomics, transcriptomics, proteomics, lipidomics, and metabolomics, could offer unprecedented opportunities for uncovering the molecular changes underlying metabolic rewiring in complex diseases, such as PCa. Recent studies, focused on the integrated analysis of multi-omics data derived from PCa patients, have in fact revealed new insights into specific metabolic reprogramming events and vulnerabilities that have the potential to better guide therapy and improve outcomes for patients. This review aims to provide an up-to-date summary of multi-omics studies focused on the characterization of the metabolomic phenotype of PCa, as well as an in-depth analysis of the correlation between changes identified in the multi-omics studies and the metabolic profile of PCa tumors.

Noninvasive urine metabolomics of prostate cancer and its therapeutic approaches: a current scenario and future perspective

INTRODUCTION

The sensitive, specific, fast, robust and noninvasive biomarkers for the evaluation of prostate cancer (PC) remain elusive in medical research. However, efforts are in full sway to investigate and resolve these puzzles for clinical practice. Advances in modern analytical techniques, sample processing, and the emergence of multiple omics approaches have created a great hope for the development of better detection modalities for PC. The objective of the present review is to provide a concise overview of the PC metabolomics-based potential discriminating molecules in urine samples using nuclear magnetic resonance spectroscopy and mass spectrometry.

AREA COVERED

A literature search was executed to find the studies reporting the noninvasive urine-based biomarkers for the diagnosis and prognosis of underlying disease. Most studies have extensivelyreported PC discriminating molecules with their respective controls. Additionally, pathophysiology and the treatment paradigm of PC are summarized and related to the insights underpinning the therapeutic intervention of PC.

EXPERT OPINION

With multi-centric, global, comprehensive omics approaches via either a non- or least-invasive bio-matrix may open new avenues of research for PC biomarker discovery, backed by a molecular mechanistic outline.

Comprehensive Metabolomics and Lipidomics Profiling of Prostate Cancer Tissue Reveals Metabolic Dysregulations Associated with Disease Development

Prostate cancer (PCa) is a global health problem that affects millions of men every year. In the past decade, metabolomics and related subareas, such as lipidomics, have demonstrated an enormous potential to identify novel mechanisms underlying PCa development and progression, providing a good basis for the development of new and more effective therapies and diagnostics. In this study, a multiplatform metabolomics and lipidomics approach, combining untargeted mass spectrometry (MS) and nuclear magnetic resonance (NMR)-based techniques, was applied to PCa tissues to investigate dysregulations associated with PCa development, in a cohort of 40 patients submitted to radical prostatectomy for PCa. Results revealed significant alterations in the levels of 26 metabolites and 21 phospholipid species in PCa tissue compared with adjacent nonmalignant tissue, suggesting dysregulation in 13 metabolic pathways associated with PCa development. The most affected metabolic pathways were amino acid metabolism, nicotinate and nicotinamide metabolism, purine metabolism, and glycerophospholipid metabolism. A clear interconnection between metabolites and phospholipid species participating in these pathways was observed through correlation analysis. Overall, these dysregulations may reflect the reprogramming of metabolic responses to produce high levels of cellular building blocks required for rapid PCa cell proliferation.

Advances and Perspectives in Prostate Cancer Biomarker Discovery in the Last 5 Years through Tissue and Urine Metabolomics

Prostate cancer (PCa) is the second most diagnosed cancer in men worldwide. For its screening, serum prostate specific antigen (PSA) test has been largely performed over the past decade, despite its lack of accuracy and inability to distinguish indolent from aggressive disease. Metabolomics has been widely applied in cancer biomarker discovery due to the well-known metabolic reprogramming characteristic of cancer cells. Most of the metabolomic studies have reported alterations in urine of PCa patients due its noninvasive collection, but the analysis of prostate tissue metabolome is an ideal approach to disclose specific modifications in PCa development. This review aims to summarize and discuss the most recent findings from tissue and urine metabolomic studies applied to PCa biomarker discovery. Eighteen metabolites were found consistently altered in PCa tissue among different studies, including alanine, arginine, uracil, glutamate, fumarate, and citrate. Urine metabolomic studies also showed consistency in the dysregulation of 15 metabolites and, interestingly, alterations in the levels of valine, taurine, leucine and citrate were found in common between urine and tissue studies. These findings unveil that the impact of PCa development in human metabolome may offer a promising strategy to find novel biomarkers for PCa diagnosis.

The Luminescence of 1,8-Diazafluoren-9-One/Titanium Dioxide Composite Thin Films for Optical Application

The investigation of innovative label-free α-amino acids detection methods represents a crucial step for the early diagnosis of several diseases. While 1,8-diazafluoren-9-one (DFO) is known in forensic application because of the fluorescent products by reacting with the amino acids present in the papillary exudate, its application for diagnostic purposes has not been fully investigated. The stabilization of DFO over a transparent substrate allows its complexation with biomolecules for the detection of α-amino acids. In this study, DFO was immobilized into a titanium dioxide (TiO₂) matrix for the fluorescence detection of glycine, as a target α-amino acid (a potential marker of the urogenital tract cancers). The DFO/TiO₂ composite was characterized by atomic force microscopy, spectroscopic ellipsometry, fluorescence spectroscopy and fluorescence microscopy. The performed fluorescent studies indicate spectacular formation of aggregates at higher concentration. The measurements performed using various fluorescence and microscopic techniques together with the suitable analysis show that the aggregates are able to emit short-lived fluorescence.

System level characterization of small molecule drugs and their affected long noncoding RNAs

Long noncoding RNAs (lncRNAs) have multiple regulatory roles and are involved in many human diseases. A potential therapeutic strategy based on targeting lncRNAs was recently developed. To gain insight into the global relationship between small molecule drugs and their affected lncRNAs, we constructed a small molecule lncRNA network consisting of 1206 nodes (1033 drugs and 173 lncRNAs) and 4770 drug-lncRNA associations using LNCmap, which reannotated the microarray data from the Connectivity Map (CMap) database. Based on network biology, we found that the connected drug pairs tended to share the same targets, indications, and side effects. In addition, the connected drug pairs tended to have a similar structure. By inferring the functions of lncRNAs through their co-expressing mRNAs, we found that lncRNA functions related to the modular interface were associated with the mode of action or side effects of the corresponding connected drugs, suggesting that lncRNAs may directly/indirectly participate in specific biological processes after drug administration. Finally, we investigated the tissue-specificity of drug-affected lncRNAs and found that some kinds of drugs tended to have a broader influence (e.g. antineoplastic and immunomodulating drugs), whereas some tissue-specific lncRNAs (nervous system) tended to be affected by multiple types of drugs.

Targeted metabolomics in bladder cancer: From analytical methods development and validation towards application to clinical samples

Bladder cancer constitutes the ninth most common cancer worldwide and, despite continuous development of new diagnostic approaches, the thirteenth leading cause of global cancer mortality. In our previous untargeted urine metabolomic investigation, seventeen metabolites were found to be statistically differentiating bladder cancer patients and healthy volunteers. Therefore, the main goal of this study was to develop and validate an analytical method for simultaneous quantitative determination of those metabolites using reversed phase high-performance liquid chromatography coupled with triple quadrupole mass spectrometry technique (RP-HPLC-QQQ/MS). Different chromatographic conditions, as well as various sample treatment procedures were tested in order to provide the best separation and the lowest limit of quantification (LOQ) values for studied compounds. The validation was performed according to the Food and Drug Administration guidelines (FDA). The limit of determination (LOD) and the LOQ values were in the range of 0.21-10.51 ng/ml and 0.69-35.02 ng/ml, respectively. The concentration range of compounds was developed between 2.5 and 12500 ng/ml. Only one compound (trimethyllysine) showed a significant matrix effect (61%) and consequently low process efficiency (64%). Overall, developed method presented recovery and precision values within the ranges proposed by FDA guidelines. The optimized and validated method was applied to urine samples obtained from 40 patients with bladder cancer and 40 healthy volunteers matched according to ones of the most important risk factors for developing urinary bladder tumors, e.i. age, gender and BMI. Afterwards, statistical analysis was provided by the use of Student's t-test or U-Mann Whitney test. The developed method was sensitive, selective and reproducible to be applied for the quantification of metabolites in the investigation of urine samples. As a consequence, ten out of previously chosen seventeen compounds, participating in different metabolites' pathways (gut floral metabolism, RNA degradation, purine metabolism, etc.), were found to be statistically significantly different in the urine concentration (p < 0.05) between cancer and control groups.