Toxicological Sciences最新文献

Metabolic dysfunction-associated steatotic liver disease (MASLD) is one of the most prevalent liver disorders, affecting approximately one-third of the global adult population. The disease begins with hepatic fat accumulation (steatosis) and can progress to inflammation, fibrosis, and hepatocellular carcinoma. To elucidate the complex mechanisms underlying MASLD, we have developed a novel mathematical model that integrates glucose and lipid metabolism, oxidative stress, insulin signaling and resistance, and cytokine function. We demonstrated that variations in extracellular fatty acid and lactate concentrations, as well as alterations in the activities of important glycolytic and triglyceride-synthesizing enzymes observed in actual patients, exert a substantial impact on oxidative stress and subsequent cellular damage. Moreover, this model enabled us to evaluate daily metabolic dynamics characteristic of steatotic liver-specific protein patterns. Importantly, it also allowed simulation of cytokine release from hepatocytes into the blood circulation (autocrine and endocrine effects) and the impact of locally elevated cytokine concentrations derived from immune cells (paracrine effects). Our model revealed the dynamics of the early stages of MASLD progression in response to alterations in blood metabolites levels, hepatic enzyme activities, insulin profiles, and cytokine patterns. Furthermore, we identified specific combinations of these factors that may alleviate the hepatic fat accumulation or oxidative stress, highlighting the importance of patient specificity. This study presents the first mechanistic framework constructed based on experimental data to describe the crosstalk among hepatic metabolism, insulin, and cytokines, serving as a powerful tool for elucidating disease mechanisms and developing therapeutic strategies.

Why and how does cancer start? Building from a Symposium at the 2025 Society of Toxicology meeting, we convened a group of international experts to answer this seemingly simple question. As experimental evidence has evolved, perspectives on cancers' origins have shifted from the accumulation of DNA mutations in single cells to complex processes involving signals from an altered tissue microenvironment which promote tumorigenesis. Carcinogen exposures impact the biology of the microenvironment in complex and tissue-specific ways. These changes can include the infiltration of inflammatory cells that produce growth factors, neo-angiogenesis, morphological changes, and immune tolerance that avoids immune-mediated elimination. In this in-depth review, we discuss the evidence linking chemical-driven microenvironmental changes in the development of a range of solid and liquid tumors. We discuss specific phenotypic alterations, such as selection pressure driving clonal expansion and cellular plasticity and reacquisition of stem cell states, linked to carcinogen-induced changes in the microenvironment. We describe assays and biomarkers which can allow us to experimentally assess links between chemical exposures, the microenvironment, and cancer phenotypes. We end by discussing how understanding the role of the microenvironment and malignancy in toxicology is essential for accurate cancer hazard evaluation, development of next-generation risk assessment frameworks, identifying new strategies for cancer prevention, and improving patient care.

Cardiovascular-Kidney-Metabolic (CKM) syndrome imposes a rising global health burden, yet the link between environmental metal mixtures and CKM progression remains unclear. To assess the joint effects of metal mixtures on CKM syndrome staging and identify critical toxic drivers through advanced mixture analysis. NHANES data (2011-2016) from 1,816 participants were analyzed via Weighted Quantile Sum (WQS) regression, generalized linear models (GLMs), ridge regression, Shapley Additive exPlanations (SHAP) analysis, and polynomial regression. An Adverse Outcome Pathway (AOP) framework was utilized to characterize the mechanisms of metal-mediated CKM. The WQS model revealed an association between mixed metal exposure and CKM (β = 0.502, p = 0.013). Subsequently, GLMs and ridge regression further identified the associative characteristics of individual metals, with all three models pointing to cobalt as the key driver. The SHAP model validated cobalt's dominant contribution from the perspective of marginal feature importance. Additionally, a polynomial equation analysis showed that cobalt exhibited a linear dose-response relationship with CKM syndrome. Based on these findings, the AOP framework furtherly identified that early CKM stages are linked with cobalt-related metabolic and immune dysregulation. In contrast, late stages involve disruptions in calcium homeostasis, lipid metabolism, and cell apoptosis-survival balance. Our findings highlight the impact of metal exposure on the progression of CKM syndrome, the AOP framework has deciphered stage-specific mechanisms of cobalt, revealing distinct toxicological pathways in early versus late CKM.

New approach methods (NAMs), including in vitro paradigms, are needed to increase throughput, sustainability, and ethicality in toxicity research. However, selecting optimal cell culture models that mimic in vivo physiological conditions is challenging. To identify cell lines that best recapitulate physiological cells, we compared gene expression signatures of cell lines and in vivo tissues. We curated 214 transcriptomics datasets from 17 human and mouse hepatic cell lines representing hepatocytes, hepatic stellate cells, and cholangiocytes and determined basal gene expression profiles for each. We also collected 7 in vivo single cell RNA sequencing (scRNAseq) datasets from human and mouse livers, which provide physiologically relevant transcriptome profiles for hepatic cell types. We compared cell line transcriptome profiles to liver scRNAseq data to determine which cell lines best represent in vivo physiology for each cell type and compared genes, regulatory networks, and biological pathways between cell lines and hepatic cell types. We further analyzed 15 cell line, in vivo, and primary hepatocyte datasets from hepatotoxicity studies to relate baseline patterns to toxicological responses. We identified HepaRG as optimal to model hepatocytes both at baseline and in hepatotoxicity application studies of diverse toxicants, and further provided biological insights into the key differences of some of the widely used hepatic cell lines from in vivo biology. Overall, we present a new in silico approach that leverages existing big data to guide selection of cell lines with better functional relevance, which can be applied to in vitro modeling of other tissues and broad biomedical applications.

Prolonged exposure to ozone causes lung injury and persistent inflammation, pathologies associated with emphysema and asthma. Herein, we characterized inflammatory cells in the lungs using a murine model of prolonged ozone exposure, with the long-term goal of assessing their role in disease pathogenesis. Mice were exposed to air or ozone (1.5 ppm, 2 h, 2x/wk, 6 wk). Bronchoalveolar lavage fluid (BAL) and cells and lung tissue were collected 24 h after the final exposure. Alveolar/bronchiolar hyperplasia, epithelial degeneration and mononuclear cell infiltration were observed following ozone exposure; BAL protein, cells, fibrinogen, and SP-A and SP-D were also increased, along with markers of oxidative stress, and impaired pulmonary function. Flow cytometric analysis of infiltrating myeloid cells revealed that after ozone exposure, the majority of these cells were mature infiltrating macrophages. These were comprised mainly of anti-inflammatory/profibrotic macrophages, with a smaller number of proinflammatory macrophages. Proinflammatory genes (Il1β, Ccl3, Ccl17, Ccl22, Tnfα) and NF-κB activity were increased in BAL cells from ozone exposed mice (>97% macrophages); profibrotic genes (Mmp12, Mmp28, Tgfβ), but not anti-inflammatory genes (Il10, Arg1), were also upregulated. Following ozone exposure, glycolytic activity and oxidative phosphorylation increased in BAL cells, consistent with proinflammatory and profibrotic activation, respectively. These findings are important as they provide a rationale for evaluating the role of inflammatory macrophages in the pathophysiological response to prolonged ozone exposure.

Cardiovascular-Kidney-Metabolic (CKM) syndrome imposes a rising global health burden, yet the link between environmental metal mixtures and CKM progression remains unclear. To assess the joint effects of metal mixtures on CKM syndrome staging and identify critical toxic drivers through advanced mixture analysis. NHANES data (2011-2016) from 1,816 participants were analyzed via Weighted Quantile Sum (WQS) regression, generalized linear models (GLMs), ridge regression, Shapley Additive exPlanations (SHAP) analysis, and polynomial regression. An Adverse Outcome Pathway (AOP) framework was utilized to characterize the mechanisms of metal-mediated CKM. The WQS model revealed an association between mixed metal exposure and CKM (β  =  0.502, p = 0.013). Subsequently, GLMs and ridge regression further identified the associative characteristics of individual metals, with all three models pointing to cobalt as the key driver. The SHAP model validated cobalt's dominant contribution from the perspective of marginal feature importance. Additionally, a polynomial equation analysis showed that cobalt exhibited a linear dose-response relationship with CKM syndrome. Based on these findings, the AOP framework furtherly identified that early CKM stages are linked with cobalt-related metabolic and immune dysregulation. In contrast, late stages involve disruptions in calcium homeostasis, lipid metabolism, and cell apoptosis-survival balance. Our findings highlight the impact of metal exposure on the progression of CKM syndrome, the AOP framework has deciphered stage-specific mechanisms of cobalt, revealing distinct toxicological pathways in early versus late CKM.

KT-474 is a first-in-class IRAK4 heterobifunctional degrader that utilizes cereblon (CRBN) for E3 ligase recruitment and was rationally designed to be devoid of immunomodulatory imide drug (IMiD)-related neosubstrate degradation. Like KT-474, most degraders in clinical trials to date rely on CRBN for E3 ligase recruitment to harness the ubiquitin-proteasome system to selectively degrade disease-associated proteins. Structural similarities of the CRBN-binding portion of these degraders to IMiDs (e.g., thalidomide) have raised safety concerns due to potential degradation of CRBN neosubstrates implicated in teratogenicity, such as SALL4. To address this theoretical concern, the potential of KT-474 to degrade CRBN neosubstrates in vitro and cause developmental toxicity in vivo was evaluated. Proteomic analyses across three human cell systems (peripheral blood mononuclear cells [PBMCs], induced pluripotent stem cells, and SK-N-DZ cells) demonstrated that KT-474 selectively degraded IRAK4 without affecting SALL4, or other detected CRBN neosubstrates. In embryo-fetal development studies, no KT-474-related malformations or embryo-fetal toxicity was observed in rats or rabbits at the highest doses tested. Associated exposures (AUC) provided 23- to 9-fold multiples, respectively, over exposures at the clinical dose of KT-474 associated with robust degradation of IRAK4 and early signals of efficacy. Deep IRAK4 degradation by KT-474 in primary rat cells, rabbit PBMCs, and a range of tissues provides confidence in the appropriateness of the animal species tested. Taken together, these data clearly differentiate KT-474 from IMiDs, support that CRBN-mediated teratogenicity seen with IMiD drugs is neosubstrate-driven, and demonstrate that structure-based design can generate highly selective degraders devoid of teratogenic risk.

With advancements in anticancer therapy, concerns over delayed cardiotoxicity are increasing, creating demand for precise in vitro systems to evaluate long-term cardiotoxic effects in drug discovery. In this study, we examined the impact of doxorubicin on the contractility of cell sheet tissues made from human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) maintained at a steady pacing rate of 1 Hz. Using our system for continuous contractile force measurement over 5 days, tissues exposed to 0.3 µM doxorubicin exhibited progressive force decline and arrhythmias, despite no significant changes in 4 biomarkers, ANP, BNP, NT-proBNP, and cTnT, sampled post-measurement. These findings suggest that indirect biomarker-based assessment of the cardiotoxicity of doxorubicin may be challenging. Notably, an increased slope during the relaxation stage preceded reduction in contraction amplitude in 0.3 µM-exposed tissues. Further analysis, dividing the relaxation into early, middle, and terminal phases, indicated that doxorubicin induces a rapid force decline during the early phase, followed by a gradual decrease in the terminal phase. We discussed the mechanistic basis of this toxicity based on intracellular Ca2+ dynamics. These insights derive from a system that enables stable, long-term measurement of contractile force under a consistent beating rate, and such technological advancements promise to enable more reliable evaluation of delayed cardiotoxicity in future drug development. Thus, our rate-controlled, continuous force platform reveals early relaxation-phase changes not detected by soluble biomarkers and offers a more sensitive in vitro approach for preclinical cardiotoxicity screening.