A metabolomics cell-based approach for anticipating and investigating drug-induced liver injury

In preclinical stages of drug development, anticipating potential adverse drug effects such as toxicity is an important issue for both saving resources and preventing public health risks. Current in vitro cytotoxicity tests are restricted by their predictive potential and their ability to provide mechanistic information. This study aimed to develop a metabolomic mass spectrometry-based approach for the detection and classification of drug-induced hepatotoxicity. To this end, the metabolite profiles of human derived hepatic cells (i.e., HepG2) exposed to different well-known hepatotoxic compounds acting through different mechanisms (i.e., oxidative stress, steatosis, phospholipidosis, and controls) were compared by multivariate data analysis, thus allowing us to decipher both common and mechanism-specific altered biochemical pathways. Briefly, oxidative stress damage markers were found in the three mechanisms, mainly showing altered levels of metabolites associated with glutathione and γ-glutamyl cycle. Phospholipidosis was characterized by a decreased lysophospholipids to phospholipids ratio, suggestive of phospholipid degradation inhibition. Whereas, steatosis led to impaired fatty acids β-oxidation and a subsequent increase in triacylglycerides synthesis. The characteristic metabolomic profiles were used to develop a predictive model aimed not only to discriminate between non-toxic and hepatotoxic drugs, but also to propose potential drug toxicity mechanism(s)

Predicting Phospholipidosis Using Machine Learning

Phospholipidosis is an adverse effect caused by numerous cationic amphiphilic drugs and can affect many cell types. It is characterized by the excess accumulation of phospholipids and is most reliably identified by electron microscopy of cells revealing the presence of lamellar inclusion bodies. The development of phospholipidosis can cause a delay in the drug development process, and the importance of computational approaches to the problem has been well documented. Previous work on predictive methods for phospholipidosis showed that state of the art machine learning methods produced the best results. Here we extend this work by looking at a larger data set mined from the literature. We find that circular fingerprints lead to better models than either E-Dragon descriptors or a combination of the two. We also observe very similar performance in general between Random Forest and Support Vector Machine models.</p

ECOG-ACRIN EAZ171: Prospective Validation Trial of Germline Predictors of Taxane-Induced Peripheral Neuropathy in Black Women With Early-Stage Breast Cancer

PURPOSE: Black women experience higher rates of taxane-induced peripheral neuropathy (TIPN) compared with White women when receiving adjuvant once weekly paclitaxel for early-stage breast cancer, leading to more dose reductions and higher recurrence rates. EAZ171 aimed to prospectively validate germline predictors of TIPN and compare rates of TIPN and dose reductions in Black women receiving (neo)adjuvant once weekly paclitaxel and once every 3 weeks docetaxel for early-stage breast cancer. METHODS: Women with early-stage breast cancer who self-identified as Black and had intended to receive (neo)adjuvant once weekly paclitaxel or once every 3 weeks docetaxel were eligible, with planned accrual to 120 patients in each arm. Genotyping was performed to determine germline neuropathy risk. Grade 2-4 TIPN by Common Terminology Criteria for Adverse Events (CTCAE) v5.0 was compared between high- versus low-risk genotypes and between once weekly paclitaxel versus once every 3 weeks docetaxel within 1 year. Patient-rated TIPN and patient-reported outcomes were compared using patient-reported outcome (PRO)-CTCAE and Functional Assessment of Cancer Therapy/Gynecologic Oncology Group-Neurotoxicity. RESULTS: Two hundred and forty of 249 enrolled patients had genotype data, and 91 of 117 (77.8%) receiving once weekly paclitaxel and 87 of 118 (73.7%) receiving once every 3 weeks docetaxel were classified as high-risk. Physician-reported grade 2-4 TIPN was not significantly different in high- versus low-risk genotype groups with once weekly paclitaxel (47% v 35%; P = .27) or with once every 3 weeks docetaxel (28% v 19%; P = .47). Grade 2-4 TIPN was significantly higher in the once weekly paclitaxel versus once every 3 weeks docetaxel arm by both physician-rated CTCAE (45% v 29%; P = .02) and PRO-CTCAE (40% v 24%; P = .03). Patients receiving once weekly paclitaxel required more dose reductions because of TIPN (28% v 9%; P &lt; .001) or any cause (39% v 25%; P = .02). CONCLUSION: Germline variation did not predict risk of TIPN in Black women receiving (neo)adjuvant once weekly paclitaxel or once every 3 weeks docetaxel. Once weekly paclitaxel was associated with significantly more grade 2-4 TIPN and required more dose reductions than once every 3 weeks docetaxel

Simulation-based cheminformatic analysis of organelle-targeted molecules: lysosomotropic monobasic amines

Cell-based molecular transport simulations are being developed to facilitate exploratory cheminformatic analysis of virtual libraries of small drug-like molecules. For this purpose, mathematical models of single cells are built from equations capturing the transport of small molecules across membranes. In turn, physicochemical properties of small molecules can be used as input to simulate intracellular drug distribution, through time. Here, with mathematical equations and biological parameters adjusted so as to mimic a leukocyte in the blood, simulations were performed to analyze steady state, relative accumulation of small molecules in lysosomes, mitochondria, and cytosol of this target cell, in the presence of a homogenous extracellular drug concentration. Similarly, with equations and parameters set to mimic an intestinal epithelial cell, simulations were also performed to analyze steady state, relative distribution and transcellular permeability in this non-target cell, in the presence of an apical-to-basolateral concentration gradient. With a test set of ninety-nine monobasic amines gathered from the scientific literature, simulation results helped analyze relationships between the chemical diversity of these molecules and their intracellular distributions

Global phylogeography and ancient evolution of the widespread human gut virus crAssphage

Microbiomes are vast communities of microorganisms and viruses that populate all natural ecosystems. Viruses have been considered to be the most variable component of microbiomes, as supported by virome surveys and examples of high genomic mosaicism. However, recent evidence suggests that the human gut virome is remarkably stable compared with that of other environments. Here, we investigate the origin, evolution and epidemiology of crAssphage, a widespread human gut virus. Through a global collaboration, we obtained DNA sequences of crAssphage from more than one-third of the world's countries and showed that the phylogeography of crAssphage is locally clustered within countries, cities and individuals. We also found fully colinear crAssphage-like genomes in both Old-World and New-World primates, suggesting that the association of crAssphage with primates may be millions of years old. Finally, by exploiting a large cohort of more than 1,000 individuals, we tested whether crAssphage is associated with bacterial taxonomic groups of the gut microbiome, diverse human health parameters and a wide range of dietary factors. We identified strong correlations with different clades of bacteria that are related to Bacteroidetes and weak associations with several diet categories, but no significant association with health or disease. We conclude that crAssphage is a benign cosmopolitan virus that may have coevolved with the human lineage and is an integral part of the normal human gut virome

Global phylogeography and ancient evolution of the widespread human gut virus crAssphage

Microbiomes are vast communities of microorganisms and viruses that populate all natural ecosystems. Viruses have been considered to be the most variable component of microbiomes, as supported by virome surveys and examples of high genomic mosaicism. However, recent evidence suggests that the human gut virome is remarkably stable compared with that of other environments. Here, we investigate the origin, evolution and epidemiology of crAssphage, a widespread human gut virus. Through a global collaboration, we obtained DNA sequences of crAssphage from more than one-third of the world’s countries and showed that the phylogeography of crAssphage is locally clustered within countries, cities and individuals. We also found fully colinear crAssphage-like genomes in both Old-World and New-World primates, suggesting that the association of crAssphage with primates may be millions of years old. Finally, by exploiting a large cohort of more than 1,000 individuals, we tested whether crAssphage is associated with bacterial taxonomic groups of the gut microbiome, diverse human health parameters and a wide range of dietary factors. We identified strong correlations with different clades of bacteria that are related to Bacteroidetes and weak associations with several diet categories, but no significant association with health or disease. We conclude that crAssphage is a benign cosmopolitan virus that may have coevolved with the human lineage and is an integral part of the normal human gut virome