Risk Assessment for Venous Thromboembolism in Chemotherapy-Treated Ambulatory Cancer Patients: A Machine Learning Approach

OBJECTIVE: To design a precision medicine approach aimed at exploiting significant patterns in data, in order to produce venous thromboembolism (VTE) risk predictors for cancer outpatients that might be of advantage over the currently recommended model (Khorana score). DESIGN: Multiple kernel learning (MKL) based on support vector machines and random optimization (RO) models were used to produce VTE risk predictors (referred to as machine learning [ML]-RO) yielding the best classification performance over a training (3-fold cross-validation) and testing set. RESULTS: Attributes of the patient data set ( n = 1179) were clustered into 9 groups according to clinical significance. Our analysis produced 6 ML-RO models in the training set, which yielded better likelihood ratios (LRs) than baseline models. Of interest, the most significant LRs were observed in 2 ML-RO approaches not including the Khorana score (ML-RO-2: positive likelihood ratio [+LR] = 1.68, negative likelihood ratio [-LR] = 0.24; ML-RO-3: +LR = 1.64, -LR = 0.37). The enhanced performance of ML-RO approaches over the Khorana score was further confirmed by the analysis of the areas under the Precision-Recall curve (AUCPR), and the approaches were superior in the ML-RO approaches (best performances: ML-RO-2: AUCPR = 0.212; ML-RO-3-K: AUCPR = 0.146) compared with the Khorana score (AUCPR = 0.096). Of interest, the best-fitting model was ML-RO-2, in which blood lipids and body mass index/performance status retained the strongest weights, with a weaker association with tumor site/stage and drugs. CONCLUSIONS: Although the monocentric validation of the presented predictors might represent a limitation, these results demonstrate that a model based on MKL and RO may represent a novel methodological approach to derive VTE risk classifiers. Moreover, this study highlights the advantages of optimizing the relative importance of groups of clinical attributes in the selection of VTE risk predictors

Induction of Isochromanones by Co-Cultivation of the Marine Fungus Cosmospora sp. and the Phytopathogen Magnaporthe oryzae

Microbial co-cultivation is a promising approach for the activation of biosynthetic gene clusters (BGCs) that remain transcriptionally silent under artificial culture conditions. As part of our project aiming at the discovery of marine-derived fungal agrochemicals, we previously used four phytopathogens as model competitors in the co-cultivation of 21 marine fungal strains. Based on comparative untargeted metabolomics analyses and anti-phytopathogenic activities of the co-cultures, we selected the co-culture of marine Cosmospora sp. with the phytopathogen Magnaporthe oryzae for in-depth chemical studies. UPLC-MS/MS-based molecular networking (MN) of the co-culture extract revealed an enhanced diversity of compounds in several molecular families, including isochromanones, specifically induced in the co-culture. Large scale co-cultivation of Cosmospora sp. and M. oryzae resulted in the isolation of five isochromanones from the whole co-culture extract, namely the known soudanones A, E, D (1-3) and their two new derivatives, soudanones H-I (4-5), the known isochromans, pseudoanguillosporins A and B (6, 7), naphtho-γ-pyrones, cephalochromin and ustilaginoidin G (8, 9), and ergosterol (10). Their structures were established by NMR, HR-ESIMS, FT-IR, electronic circular dichroism (ECD) spectroscopy, polarimetry ([α]D), and Mosher’s ester reaction. Bioactivity assays revealed antimicrobial activity of compounds 2 and 3 against the phytopathogens M. oryzae and Phytophthora infestans, while pseudoanguillosporin A (6) showed the broadest and strongest anti-phytopathogenic activity against Pseudomonas syringae, Xanthomonas campestris, M. oryzae and P. infestans. This is the first study assessing the anti-phytopathogenic activities of soudanones

Application of Feature-Based Molecular Networking for Comparative Metabolomics and Targeted Isolation of Stereoisomers from Algicolous Fungi

Seaweed endophytic (algicolous) fungi are talented producers of bioactive natural products. We have previously isolated two strains of the endophytic fungus, Pyrenochaetopsis sp. FVE-001 and FVE-087, from the thalli of the brown alga Fucus vesiculosus. Initial chemical studies yielded four new decalinoylspirotetramic acid derivatives with antimelanoma activity, namely pyrenosetins A–C (1–3) from Pyrenochaetopsis sp. strain FVE-001, and pyrenosetin D (4) from strain FVE-087. In this study, we applied a comparative metabolomics study employing HRMS/MS based feature-based molecular networking (FB MN) on both Pyrenochaetopsis strains. A higher chemical capacity in production of decalin derivatives was observed in Pyrenochaetopsis sp. FVE-087. Notably, several decalins showed different retention times despite the same MS data and MS/MS fragmentation pattern with the previously isolated pyrenosetins, indicating they may be their stereoisomers. FB MN-based targeted isolation studies coupled with antimelanoma activity testing on the strain FVE-087 afforded two new stereoisomers, pyrenosetins E (5) and F (6). Extensive NMR spectroscopy including DFT computational studies, HR-ESIMS, and Mosher’s ester method were used in the structure elucidation of compounds 5 and 6. The 3′R,5′R stereochemistry determined for compound 6 was identical to that previously reported for pyrenosetin C (3), whose stereochemistry was revised as 3′S,5′R in this study. Pyrenosetin E (5) inhibited the growth of human malignant melanoma cells (A-375) with an IC50 value of 40.9 μM, while 6 was inactive. This study points out significant variations in the chemical repertoire of two closely related fungal strains and the versatility of FB MN in identification and targeted isolation of stereoisomers. It also confirms that the little-known fungal genus Pyrenochaetopsis is a prolific source of complex decalinoylspirotetramic acid derivatives

Isolation of Isotrichophycin C and Trichophycins G–I from a Collection of Trichodesmium thiebautii

The trichophycin family of compounds are chlorinated polyketides first discovered from environmental collections of a bloom-forming Trichodesmium sp. cyanobacterium. In an effort to fully capture the chemical space of this group of metabolites, the utilization of MS/MS-based molecular networking of a Trichodesmium thiebautii extract revealed a metabolome replete with halogenated compounds. Subsequent MS-guided isolation resulted in the characterization of isotrichophycin C and trichophycins G–I (1–4). These new metabolites had intriguing structural variations from those trichophycins previously characterized, which allowed for a comparative study to examine structural features that are associated with toxicity to murine neuroblastoma cells. Additionally, we propose the absolute configuration of the previously characterized trichophycin A (5). Overall, the metabolome of the Trichodesmium bloom is hallmarked by an unprecedented amount of chlorinated molecules, many of which remain to be structurally characterized

SINEUP Non-coding RNA Targeting GDNF Rescues Motor Deficits and Neurodegeneration in a Mouse Model of Parkinson's Disease.

International audience; Glial cell-derived neurotrophic factor (GDNF) has a potent action in promoting the survival of dopamine (DA) neurons. Several studies indicate that increasing GDNF levels may be beneficial for the treatment of Parkinson's disease (PD) by reducing neurodegeneration of DA neurons. Despite a plethora of preclinical studies showing GDNF efficacy in PD animal models, its application in humans remains questionable for its poor efficacy and side effects due to its uncontrolled, ectopic expression. Here we took advantage of SINEUPs, a new class of antisense long non-coding RNA, that promote translation of partially overlapping sense protein-coding mRNAs with no effects on their mRNA levels. By synthesizing a SINEUP targeting Gdnf mRNA, we were able to increase endogenous GDNF protein levels by about 2-fold. Adeno-associated virus (AAV)9-mediated delivery in the striatum of wild-type (WT) mice led to an increase of endogenous GDNF protein for at least 6 months and the potentiation of the DA system's functions while showing no side effects. Furthermore, SINEUP-GDNF was able to ameliorate motor deficits and neurodegeneration of DA neurons in a PD neurochemical mouse model. Our data indicate that SINEUP-GDNF could represent a new strategy to increase endogenous GDNF protein levels in a more physiological manner for therapeutic treatments of PD

Influence of Antisynthetase Antibodies Specificities on Antisynthetase Syndrome Clinical Spectrum TimeCourse

Introduction: Increased cardiovascular (CV) morbidity and mortality is observed in inflammatory joint diseases (IJDs) such as rheumatoid arthritis, ankylosing spondylitis, and psoriatic arthritis. However, the management of CV disease in these conditions is far from being well established.Areas covered: This review summarizes the main epidemiologic, pathophysiological, and clinical risk factors of CV disease associated with IJDs. Less common aspects on early diagnosis and risk stratification of the CV disease in these conditions are also discussed. In Europe, the most commonly used risk algorithm in patients with IJDs is the modified SCORE index based on the revised recommendations proposed by the EULAR task force in 2017.Expert opinion: Early identification of IJD patients at high risk of CV disease is essential. It should include the use of complementary noninvasive imaging techniques. A multidisciplinary approach aimed to improve heart-healthy habits, including strict control of classic CV risk factors is crucial. Adequate management of the underlying IJD is also of main importance since the reduction of disease activity decreases the risk of CV events. Non-steroidal anti-inflammatory drugs may have a lesser harmful effect in IJD than in the general population, due to their anti-inflammatory effects along with other potential beneficial effects.This research was partially funded by FOREUM—Foundation for Research in Rheumatolog

New Tricks with an Old Sponge: Feature-Based Molecular Networking Led to Fast Identification of New Stylissamide L from Stylissa caribica

Feature-based molecular networking was used to re-examine the secondary metabolites in extracts of a very well studied marine sponge, Stylissa caribica, known to contain a large array of cyclic peptides and brominated alkaloids. The analysis revealed the presence of 13 cyclic peptides in the sponge that had never been detected in previous work and appeared to be new compounds. The most abundant one was isolated and shown to be a new proline-rich cyclic heptapetide that was called stylissamide L (1). Structure of compound 1, including the cis/trans geometry of the three proline residues, was determined by extensive NMR studies; the l configuration of the seven amino acid residues was determined using Marfey’s method. Stylissamide L was tested for activity as a cell growth inhibitor and cell migration inhibitor on two cancer cell lines but, unlike other members of the stylissamide family, it showed no significant activity. This approach showed that even a thoroughly studied species such as S. caribica may contain new chemistry that can be revealed if studied with the right tools

Innovative strategies in the identification of new natural lead compounds from marine organisms

Marine environment represents one of the most interesting sources of inspiration for the development of new drugs. Marine organisms, for example porifera, tunicates, aquatic plants, can synthesize and/or accumulate an important plurality of secondary metabolites with peculiar and unusual molecular structures, implicated in defence mechanisms, in intra- and inter-species communication and in processes of adaptation to extreme conditions. In the spectrum of pharmacological activities boasted by natural products isolated from marine organisms, it is fundamental to mention the antibiotic, antifungal, antiviral and antineoplastic activities. In recent years, about 20 compounds from marine origin have been in phase I, II or III clinical trials, whereas some marine natural product-derived compounds are commercially available. Significant advances in the field of structural elucidation techniques, occurred in recent years, allow for the complete elucidation of sub milligram samples. In addition, the development of innovative techniques combining data obtained from sophisticated analytical techniques and efficient data analysis software, has allowed to stem the difficulty in identifying new natural compounds from complex extracts, facilitating the process of dereplication of the huge number of metabolites. Among these, molecular networking is an innovative computational technique, which is a valuable complement to traditional dereplication techniques. Molecular networking processes the massive amounts of data obtained from LC-MS/MS analysis of complex extracts, allowing the automated identification of the structural similarity between metabolites based on similarity between the fragmentation spectra of the compounds in the extract. The research work described in this PhD thesis fits into this scenario. A significant part of the research activity was focused on molecular networking, demonstrating its effectiveness both in the discovery of new natural products and in environmental analysis. In particular, the workflow that integrates the analysis of LC-MS/MS data of extracts of the widely studied sponge Stylissa caribica with molecular networking, in its feature-based molecular networking variant, allowed the rapid isolation of a new cyclic heptapeptide, stylissamide L. Moreover, the study with these methods of the extract of the sponge Clathria faviformis led to the isolation of a new phospholipid, favilipid A. The validity of the methodology was further verified with the analysis of extracts from the cyanobacterium Trichodesmium thiebautii, whose metabolome had shown traits in common with the metabolic profile of the marine sponge Smenospongia aurea. Thanks to Feature-Based Molecular Networking, it was possible to focus the analysis on halogenated compounds in the extract, leading to the isolation of 4 new polyketide compounds, included in the class of trichophycins (isotrichophycin C and trichophycins G-I). The cytotoxicity of the newly isolated compounds, along with the previously identified trichophycins was evaluated against the mouse neuroblastoma cell line N2A, as part of a broader structure-activity relationship (SAR) study, aimed at determining the features that modulate bioactivity. In the context of environmental monitoring of cyanobacteria, the validity of a pipeline that integrates the investigation of the territory thanks to specific satellites, allowing the rapid identification of potentially toxic cyanobacterial blooms, and the subsequent chemical analysis of collected environmental samples, based on molecular networking, was verified in the analysis of an unusual cyanobacteria bloom that took place in Lake Avernus at the turn of the lockdown period from COVID-19 in Italy. The presence in the extracts of cyanotoxins, particularly microcystins, was verified by genome amplification analysis and by in-depth analysis of molecular networking clusters containing nodes recognized as known toxins by in-silico tools, provided by the freely accessible website GNPS. In addition, the cytotoxic activity of the chloroform extracts was confirmed. Another important part of the research activity was focused on the detailed structural elucidation of new natural products isolated from the extracts of the seagrass Zostera marina. The structure of the new cyclic diarylheptanoids, zosteraphenol A and zosteraphenol B was completely elucidated. They both displayed broad and unresolved signals in 1D and 2D NMR spectra even at low temperature, which were shown to be related to a conformational equilibrium between rotamers with opposite axial chirality with the support of quantum mechanical calculations. Further analysis of extracts from Z. marina led to the discovery of two unique diarylheptanoid dimers, zosterabisphenone A and B, each composed of two different cyclic diarylheptanoids. They showed the same conformational equilibrium as zosteraphenols A and B, and their structure elucidation required extensive use of DFT calculations. A possible biosynthesis of zosterabisphenone A was proposed. In cytotoxicity assays performed for these compounds, zosterabisphenone B exhibited time-dependent and concentration-dependent cytotoxic activity towards HCT116 cells. Finally, the new phenolic acid, 7″,8″-didehydrosalviolanic acid B was isolated and characterized as part of a study investigating seasonal variations of phenolic compounds in Z. marina. Its absolute configuration was assigned by comparison of the ECD spectrum of methyl (3,4-dihydroxyphenyl)lactate produced by degradation of the isolated compound, and methyl (3,4-dihydroxyphenyl) lactate produced by degradation of rosmarinic acid, whose absolute configuration is known from previous studies