Onychocolone A produced by the fungus Onychocola sp. targets cancer stem cells and stops pancreatic cancer progression by inhibiting MEK2-dependent cell signaling.

Pancreatic cancer (PC) shows a high fatality rate that can only be faced with a combination of surgery and chemotherapy or palliative treatment in the case of advanced patients. Besides, PC tumors are enriched with subpopulations of cancer stem cells (CSCs) that are resistant to the existing chemotherapeutic agents, which raises an important need for the identification of new drugs. To fill this gap, we have tested the anti-tumoral activity of microbial extracts, which chemical diversity offers a broad spectrum of potential new bioactive compounds. Extracts derived from the fungus Onychocola sp. CF-107644 were assayed via high throughput screening followed by bioassay-guided fractionation and resulted in the identification and isolation of six benzophenone derivatives with antitumoral activity: onychocolones A-F (#1-6). The structures of the compounds were established by spectroscopic methods, including ESI-TOF MS, 1D and 2D NMR analyses and X-ray diffraction. Compounds #1-4 significantly inhibited the growth of the pancreas tumoral cell lines, with low-micromolar Median Effective Doses (ED50s). Compound #1 (onychocolone A) was prioritized for further profiling due to its pro-apoptotic effect, which was further validated on 3D spheroids and pancreatic CSCs. Protein expression assays showed that the effect was mechanistically linked to the inhibition of MEK onco-signaling pathway. The efficacy of onychocolone A was also demonstrated in vivo by the reduction of tumor growth in a pancreatic xenograft mouse model generated by CSCs. Altogether, the data support that onychocolone A is a promising new small molecule for hit-to-lead development of a new treatment for PC.

Assessment of Untargeted Metabolomics by Hydrophilic Interaction Liquid Chromatography-Mass Spectrometry to Define Breast Cancer Liquid Biopsy-Based Biomarkers in Plasma Samples.

An early diagnosis of cancer is fundamental not only in regard to reducing its mortality rate but also in terms of counteracting the progression of the tumor in the initial stages. Breast cancer (BC) is the most common tumor pathology in women and the second deathliest cancer worldwide, although its survival rate is increasing thanks to improvements in screening programs. However, the most common techniques to detect a breast tumor tend to be time-consuming, unspecific or invasive. Herein, the use of untargeted hydrophilic interaction liquid chromatography-mass spectrometry analysis appears as an analytical technique with potential use for the early detection of biomarkers in liquid biopsies from BC patients. In this research, plasma samples from 134 BC patients were compared with 136 from healthy controls (HC), and multivariate statistical analyses showed a clear separation between four BC phenotypes (LA, LB, HER2, and TN) and the HC group. As a result, we identified two candidate biomarkers that discriminated between the groups under study with a VIP > 1 and an AUC of 0.958. Thus, targeting the specific aberrant metabolic pathways in future studies may allow for better molecular stratification or early detection of the disease.

Identification of novel biomarkers in the early diagnosis of malignant melanoma by untargeted liquid chromatography coupled to high-resolution mass spectrometry-based metabolomics: a pilot study.

BACKGROUND: Malignant melanoma (MM) is a highly aggressive form of skin cancer whose incidence continues to rise worldwide. If diagnosed at an early stage, it has an excellent prognosis, but mortality increases significantly at advanced stages after distant spread. Unfortunately, early detection of aggressive melanoma remains a challenge. OBJECTIVES: To identify novel blood-circulating biomarkers that may be useful in the diagnosis of MM to guide patient counselling and appropriate disease management. METHODS: In this study, 105 serum samples from 26 healthy patients and 79 with MM were analysed using an untargeted approach by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) to compare the metabolomic profiles of both conditions. Resulting data were subjected to both univariate and multivariate statistical analysis to select robust biomarkers. The classification model obtained from this analysis was further validated with an independent cohort of 12 patients with stage I MM. RESULTS: We successfully identified several lipidic metabolites differentially expressed in patients with stage I MM vs. healthy controls. Three of these metabolites were used to develop a classification model, which exhibited exceptional precision (0.92) and accuracy (0.94) when validated on an independent sample. CONCLUSIONS: These results demonstrate that metabolomics using LC-HRMS is a powerful tool to identify and quantify metabolites in bodily fluids that could serve as potential early diagnostic markers for MM.

Melanoma is a type of skin cancer that can be deadly if it is not detected at an early stage. Unfortunately, the early detection of melanoma is challenging. Our team has developed a model that could be used to predict whether a person has stage I malignant melanoma based on blood serum analysis. The model was trained on data from a group of people with melanoma and it was found to be accurate in predicting melanoma at an early stage. This means that the model could be used to identify people who have skin cancer before it progresses and becomes more complicated to treat. Although the researchers recommend that further studies are conducted to validate the model in a larger population of people, this research could help with the early diagnosis of melanoma and work toward improving survival rates.

Predicting dynamic response to neoadjuvant chemotherapy in breast cancer: a novel metabolomics approach.

Neoadjuvant chemotherapy (NACT) outcomes vary according to breast cancer (BC) subtype. Since pathologic complete response is one of the most important target endpoints of NACT, further investigation of NACT outcomes in BC is crucial. Thus, identifying sensitive and specific predictors of treatment response for each phenotype would enable early detection of chemoresistance and residual disease, decreasing exposures to ineffective therapies and enhancing overall survival rates. We used liquid chromatography-high-resolution mass spectrometry (LC-HRMS)-based untargeted metabolomics to detect molecular changes in plasma of three different BC subtypes following the same NACT regimen, with the aim of searching for potential predictors of response. The metabolomics data set was analyzed by combining univariate and multivariate statistical strategies. By using ANOVA-simultaneous component analysis (ASCA), we were able to determine the prognostic value of potential biomarker candidates of response to NACT in the triple-negative (TN) subtype. Higher concentrations of docosahexaenoic acid and secondary bile acids were found at basal and presurgery samples, respectively, in the responders group. In addition, the glycohyocholic and glycodeoxycholic acids were able to classify TN patients according to response to treatment and overall survival with an area under the curve model > 0.77. In relation to luminal B (LB) and HER2+ subjects, it should be noted that significant differences were related to time and individual factors. Specifically, tryptophan was identified to be decreased over time in HER2+ patients, whereas LysoPE (22:6) appeared to be increased, but could not be associated with response to NACT. Therefore, the combination of untargeted-based metabolomics along with longitudinal statistical approaches may represent a very useful tool for the improvement of treatment and in administering a more personalized BC follow-up in the clinical practice.

Identification of Compounds with Potential Therapeutic Uses from Sweet Pepper (Capsicum annuum L.) Fruits and Their Modulation by Nitric Oxide (NO).

Plant species are precursors of a wide variety of secondary metabolites that, besides being useful for themselves, can also be used by humans for their consumption and economic benefit. Pepper (Capsicum annuum L.) fruit is not only a common food and spice source, it also stands out for containing high amounts of antioxidants (such as vitamins C and A), polyphenols and capsaicinoids. Particular attention has been paid to capsaicin, whose anti-inflammatory, antiproliferative and analgesic activities have been reported in the literature. Due to the potential interest in pepper metabolites for human use, in this project, we carried out an investigation to identify new bioactive compounds of this crop. To achieve this, we applied a metabolomic approach, using an HPLC (high-performance liquid chromatography) separative technique coupled to metabolite identification by high resolution mass spectrometry (HRMS). After chromatographic analysis and data processing against metabolic databases, 12 differential bioactive compounds were identified in sweet pepper fruits, including quercetin and its derivatives, L-tryptophan, phytosphingosin, FAD, gingerglycolipid A, tetrahydropentoxylin, blumenol C glucoside, colnelenic acid and capsoside A. The abundance of these metabolites varied depending on the ripening stage of the fruits, either immature green or ripe red. We also studied the variation of these 12 metabolites upon treatment with exogenous nitric oxide (NO), a free radical gas involved in a good number of physiological processes in higher plants such as germination, growth, flowering, senescence, and fruit ripening, among others. Overall, it was found that the content of the analyzed metabolites depended on the ripening stage and on the presence of NO. The metabolic pattern followed by quercetin and its derivatives, as a consequence of the ripening stage and NO treatment, was also corroborated by transcriptomic analysis of genes involved in the synthesis of these compounds. This opens new research perspectives on the pepper fruit's bioactive compounds with nutraceutical potentiality, where biotechnological strategies can be applied for optimizing the level of these beneficial compounds.

Human Plasma Metabolomics for Biomarker Discovery: Targeting the Molecular Subtypes in Breast Cancer.

PURPOSE: The aim of this study is to identify differential metabolomic signatures in plasma samples of distinct subtypes of breast cancer patients that could be used in clinical practice as diagnostic biomarkers for these molecular phenotypes and to provide a more individualized and accurate therapeutic procedure. METHODS: Untargeted LC-HRMS metabolomics approach in positive and negative electrospray ionization mode was used to analyze plasma samples from LA, LB, HER2+ and TN breast cancer patients and healthy controls in order to determine specific metabolomic profiles through univariate and multivariate statistical data analysis. RESULTS: We tentatively identified altered metabolites displaying concentration variations among the four breast cancer molecular subtypes. We found a biomarker panel of 5 candidates in LA, 7 in LB, 5 in HER2 and 3 in TN that were able to discriminate each breast cancer subtype with a false discovery range corrected p-value < 0.05 and a fold-change cutoff value > 1.3. The model clinical value was evaluated with the AUROC, providing diagnostic capacities above 0.85. CONCLUSION: Our study identifies metabolic profiling differences in molecular phenotypes of breast cancer. This may represent a key step towards therapy improvement in personalized medicine and prioritization of tailored therapeutic intervention strategies.

Metabolomic profile of cancer stem cell-derived exosomes from patients with malignant melanoma.

Malignant melanoma (MM) is the most aggressive and life-threatening form of skin cancer. It is characterized by an extraordinary metastasis capacity and chemotherapy resistance, mainly due to melanoma cancer stem cells (CSCs). To date, there are no suitable clinical diagnostic, prognostic or predictive biomarkers for this neoplasia. Therefore, there is an urgent need for new MM biomarkers that enable early diagnosis and effective disease monitoring. Exosomes represent a novel source of biomarkers since they can be easily isolated from different body fluids. In this work, a primary patient-derived MM cell line enriched in CSCs was characterized by assessing the expression of specific markers and their stem-like properties. Exosomes derived from CSCs and serums from patients with MM were characterized, and their metabolomic profile was analysed by high-resolution mass spectrometry (HRMS) following an untargeted approach and applying univariate and multivariate statistical analyses. The aim of this study was to search potential biomarkers for the diagnosis of this disease. Our results showed significant metabolomic differences in exosomes derived from MM CSCs compared with those from differentiated tumour cells and also in serum-derived exosomes from patients with MM compared to those from healthy controls. Interestingly, we identified similarities between structural lipids differentially expressed in CSC-derived exosomes and those derived from patients with MM such as the glycerophosphocholine PC 16:0/0:0. To our knowledge, this is the first metabolomic-based study aimed at characterizing exosomes derived from melanoma CSCs and patients' serum in order to identify potential biomarkers for MM diagnosis. We conclude that metabolomic characterization of CSC-derived exosomes sets an open door to the discovery of clinically useful biomarkers in this neoplasia.

Discovery of Pancreatic Adenocarcinoma Biomarkers by Untargeted Metabolomics.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and lethal cancers, with a 5-year survival rate of less than 5%. In fact, complete surgical resection remains the only curative treatment. However, fewer than 20% of patients are candidates for surgery at the time of presentation. Hence, there is a critical need to identify diagnostic biomarkers with potential clinical utility in this pathology. In this context, metabolomics could be a powerful tool to search for new robust biomarkers. Comparative metabolomic profiling was performed in serum samples from 59 unresectable PDAC patients and 60 healthy controls. Samples were analyzed by using an untargeted metabolomics workflow based on liquid chromatography, coupled to high-resolution mass spectrometry in positive and negative electrospray ionization modes. Univariate and multivariate analysis allowed the identification of potential candidates that were significantly altered in PDAC patients. A panel of nine candidates yielded excellent diagnostic capacities. Pathway analysis revealed four altered pathways in our patients. This study shows the potential of liquid chromatography coupled to high-resolution mass spectrometry as a diagnostic tool for PDAC. Furthermore, it identified novel robust biomarkers with excellent diagnostic capacities.

Optimization of piperazine-derived ureas privileged structures for effective antiadenovirus agents.

In recent years, human adenovirus (HAdV) infections have shown a high clinical impact in both immunosuppressed and immunocompetent patients. The research into specific antiviral drugs for the treatment of HAdV infections in immunocompromised patients constitutes a principal objective for medicinal chemistry due to the lack of any specific secure drug to treat these infections. In this study, we report a small-molecule library (67 compounds) designed from an optimization process of piperazine-derived urea privileged structures and their biological evaluation: antiviral activity and cytotoxicity. The active compounds selected were further evaluated to gain mechanistic understanding for their inhibition. Twelve derivatives were identified that inhibited HAdV infections at nanomolar and low micromolar concentrations (IC50 from 0.6 to 5.1 µM) with low cytotoxicity. In addition, our mechanistic assays suggested differences in the way the derivatives exert their anti-HAdV activity targeting transcription, DNA replication and later steps in the HAdV replication cycle. Furthermore, eight of the 12 studied derivatives blocked human cytomegalovirus (HCMV) DNA replication at low micromolar concentrations. The data provided herein indicates that the 12 thiourea/urea piperazine derivatives studied may represent potential lead compounds for clinical evaluation and development of new anti-HAdV drugs.

Bisphenol-A in the European Prospective Investigation into Cancer and Nutrition cohort in Spain: Levels at recruitment and associated dietary factors.

Bisphenol A (BPA) is considered an endocrine disruptor and it is present in numerous products of daily use. The aim of this study was to analyze serum BPA concentrations in a subcohort of the Spanish European Prospective Investigation into Cancer and Nutrition (EPIC), as well as to identify potential predictors of the exposure. The population consisted on 3553 subjects from 4 EPIC-Spain centres and BPA levels were measured in serum samples by UHPLC-MS/MS. Almost 70% of the participants showed detectable BPA values (>0.2 ng/ml), with a geometric mean of 1.19 ng/ml (95% CI: 1.12-1.25). By sex, detectable percentages were similar (p = 0.56) but with higher serum levels in men (1.27 vs 1.11 ng/ml, p = 0.01). Based on the adjusted regression models, a 50 g/day increase in the consumption of added fats and oils were associated with 43% lower BPA serum levels, while sugar and confectionary was associated with 25% higher levels of serum BPA. We evidenced differential exposure levels by province, sex and age, but not by anthropometric or lifestyle characteristics. Further investigation is needed to understand the influence of diet in BPA exposure.

Untargeted LC-HRMS-based metabolomics to identify novel biomarkers of metastatic colorectal cancer.

Colorectal cancer is one of the main causes of cancer death worldwide, and novel biomarkers are urgently needed for its early diagnosis and treatment. The utilization of metabolomics to identify and quantify metabolites in body fluids may allow the detection of changes in their concentrations that could serve as diagnostic markers for colorectal cancer and may also represent new therapeutic targets. Metabolomics generates a pathophysiological 'fingerprint' that is unique to each individual. The purpose of our study was to identify a differential metabolomic signature for metastatic colorectal cancer. Serum samples from 60 healthy controls and 65 patients with metastatic colorectal cancer were studied by liquid chromatography coupled to high-resolution mass spectrometry in an untargeted metabolomic approach. Multivariate analysis revealed a separation between patients with metastatic colorectal cancer and healthy controls, who significantly differed in serum concentrations of one endocannabinoid, two glycerophospholipids, and two sphingolipids. These findings demonstrate that metabolomics using liquid-chromatography coupled to high-resolution mass spectrometry offers a potent diagnostic tool for metastatic colorectal cancer.

Systemic blockade of LPA1/3 lysophosphatidic acid receptors by ki16425 modulates the effects of ethanol on the brain and behavior.

The systemic administration of lysophosphatidic acid (LPA) LPA1/3 receptor antagonists is a promising clinical tool for cancer, sclerosis and fibrosis-related diseases. Since LPA1 receptor-null mice engage in increased ethanol consumption, we evaluated the effects of systemic administration of an LPA1/3 receptor antagonist (intraperitoneal ki16425, 20 mg/kg) on ethanol-related behaviors as well as on brain and plasma correlates. Acute administration of ki16425 reduced motivation for ethanol but not for saccharine in ethanol self-administering Wistar rats. Mouse experiments were conducted in two different strains. In Swiss mice, ki16425 treatment reduced both ethanol-induced sedation (loss of righting reflex, LORR) and ethanol reward (escalation in ethanol consumption and ethanol-induced conditioned place preference, CPP). Furthermore, in the CPP-trained Swiss mice, ki16425 prevented the effects of ethanol on basal c-Fos expression in the medial prefrontal cortex and on adult neurogenesis in the hippocampus. In the c57BL6/J mouse strain, however, no effects of ki16425 on LORR or voluntary drinking were observed. The c57BL6/J mouse strain was then evaluated for ethanol withdrawal symptoms, which were attenuated when ethanol was preceded by ki16425 administration. In these animals, ki16425 modulated the expression of glutamate-related genes in brain limbic regions after ethanol exposure; and peripheral LPA signaling was dysregulated by either ki16425 or ethanol. Overall, these results suggest that LPA1/3 receptor antagonists might be a potential new class of drugs that are suitable for treating or preventing alcohol use disorders. A pharmacokinetic study revealed that systemic ki16425 showed poor brain penetration, suggesting the involvement of peripheral events to explain its effects.

Untargeted LC-HRMS-Based Metabolomics for Searching New Biomarkers of Pancreatic Ductal Adenocarcinoma: A Pilot Study.

Pancreatic ductal adenocarcinoma is one of the most lethal tumors since it is usually detected at an advanced stage in which surgery and/or current chemotherapy have limited efficacy. The lack of sensitive and specific markers for diagnosis leads to a dismal prognosis. The purpose of this study is to identify metabolites in serum of pancreatic ductal adenocarcinoma patients that could be used as diagnostic biomarkers of this pathology. We used liquid chromatography-high-resolution mass spectrometry for a nontargeted metabolomics approach with serum samples from 28 individuals, including 16 patients with pancreatic ductal adenocarcinoma and 12 healthy controls. Multivariate statistical analysis, which included principal component analysis and partial least squares, revealed clear separation between the patient and control groups analyzed by liquid chromatography-high-resolution mass spectrometry using a nontargeted metabolomics approach. The metabolic analysis showed significantly lower levels of phospholipids in the serum from patients with pancreatic ductal adenocarcinoma compared with serum from controls. Our results suggest that the liquid chromatography-high-resolution mass spectrometry-based metabolomics approach provides a potent and promising tool for the diagnosis of pancreatic ductal adenocarcinoma patients using the specific metabolites identified as novel biomarkers that could be used for an earlier detection and treatment of these patients.

In vitro toxicity of reuterin, a potential food biopreservative.

Reuterin has a high potential as a food preservative due to both its chemical characteristics and its antimicrobial activity against food-borne pathogens and spoilage bacteria. However, there is a lack of information about its toxicity and its capacity to interfere with the metabolism of drugs by inhibiting cytochrome P450 (CYP) activity. The results of this study indicated that reuterin exhibited a moderate cytotoxicity in the human hepatoma cell line HepG2 according to assays measuring three different endpoints in the same set of cells. Reuterin was much less toxic than acrolein and only four times more toxic than diacetyl, a generally recognized as safe flavoring compound. In vitro experiments utilizing human liver microsomes showed that reuterin presents low possibility of displaying in vivo drug interactions by inhibition of CYP3A4, CYP2D6, and CYP2C9. Therefore, reuterin can be considered a promising food biopreservative, although additional toxicology research is needed before permission for use can be granted.

High-Throughput Screening Platform for the Discovery of New Immunomodulator Molecules from Natural Product Extract Libraries.

It is widely accepted that central nervous system inflammation and systemic inflammation play a significant role in the progression of chronic neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease, neurotropic viral infections, stroke, paraneoplastic disorders, traumatic brain injury, and multiple sclerosis. Therefore, it seems reasonable to propose that the use of anti-inflammatory drugs might diminish the cumulative effects of inflammation. Indeed, some epidemiological studies suggest that sustained use of anti-inflammatory drugs may prevent or slow down the progression of neurodegenerative diseases. However, the anti-inflammatory drugs and biologics used clinically have the disadvantage of causing side effects and a high cost of treatment. Alternatively, natural products offer great potential for the identification and development of bioactive lead compounds into drugs for treating inflammatory diseases with an improved safety profile. In this work, we present a validated high-throughput screening approach in 96-well plate format for the discovery of new molecules with anti-inflammatory/immunomodulatory activity. The in vitro models are based on the quantitation of nitrite levels in RAW264.7 murine macrophages and interleukin-8 in Caco-2 cells. We have used this platform in a pilot project to screen a subset of 5976 noncytotoxic crude microbial extracts from the MEDINA microbial natural product collection. To our knowledge, this is the first report on an high-throughput screening of microbial natural product extracts for the discovery of immunomodulators.