The P286R mutation of DNA polymerase ε activates cancer-cell-intrinsic immunity and suppresses endometrial tumorigenesis via the cGAS-STING pathway.

Endometrial carcinoma (EC) is a prevalent gynecological tumor in women, and its treatment and prevention are significant global health concerns. The mutations in DNA polymerase ε (POLE) are recognized as key features of EC and may confer survival benefits in endometrial cancer patients undergoing anti-PD-1/PD-L1 therapy. However, the anti-tumor mechanism of POLE mutations remains largely elusive. This study demonstrates that the hot POLE P286R mutation impedes endometrial tumorigenesis by inducing DNA breakage and activating the cGAS-STING signaling pathway. The POLE mutations were found to inhibit the proliferation and stemness of primary human EC cells. Mechanistically, the POLE mutants enhance DNA damage and suppress its repair through the interaction with DNA repair proteins, leading to genomic instability and the upregulation of cytoplasmic DNA. Additionally, the POLE P286R mutant also increases cGAS level, promotes TBK1 phosphorylation, and stimulates inflammatory gene expression and anti-tumor immune response. Furthermore, the POLE P286R mutation inhibits tumor growth and facilitates the infiltration of cytotoxic T cells in human endometrial cancers. These findings uncover a novel mechanism of POLE mutations in antagonizing tumorigenesis and provide a promising direction for effective cancer therapy.

A multi-approach and multi-scale platform to model CD4+ T cells responding to infections.

Immune responses rely on a complex adaptive system in which the body and infections interact at multiple scales and in different compartments. We developed a modular model of CD4+ T cells, which uses four modeling approaches to integrate processes at three spatial scales in different tissues. In each cell, signal transduction and gene regulation are described by a logical model, metabolism by constraint-based models. Cell population dynamics are described by an agent-based model and systemic cytokine concentrations by ordinary differential equations. A Monte Carlo simulation algorithm allows information to flow efficiently between the four modules by separating the time scales. Such modularity improves computational performance and versatility and facilitates data integration. We validated our technology by reproducing known experimental results, including differentiation patterns of CD4+ T cells triggered by different combinations of cytokines, metabolic regulation by IL2 in these cells, and their response to influenza infection. In doing so, we added multi-scale insights to single-scale studies and demonstrated its predictive power by discovering switch-like and oscillatory behaviors of CD4+ T cells that arise from nonlinear dynamics interwoven across three scales. We identified the inflamed lymph node's ability to retain naive CD4+ T cells as a key mechanism in generating these emergent behaviors. We envision our model and the generic framework encompassing it to serve as a tool for understanding cellular and molecular immunological problems through the lens of systems immunology.

Role of NAD+ in regulating cellular and metabolic signaling pathways.

BACKGROUND: Nicotinamide adenine dinucleotide (NAD+), a critical coenzyme present in every living cell, is involved in a myriad of metabolic processes associated with cellular bioenergetics. For this reason, NAD+ is often studied in the context of aging, cancer, and neurodegenerative and metabolic disorders. SCOPE OF REVIEW: Cellular NAD+ depletion is associated with compromised adaptive cellular stress responses, impaired neuronal plasticity, impaired DNA repair, and cellular senescence. Increasing evidence has shown the efficacy of boosting NAD+ levels using NAD+ precursors in various diseases. This review provides a comprehensive understanding into the role of NAD+ in aging and other pathologies and discusses potential therapeutic targets. MAJOR CONCLUSIONS: An alteration in the NAD+/NADH ratio or the NAD+ pool size can lead to derailment of the biological system and contribute to various neurodegenerative disorders, aging, and tumorigenesis. Due to the varied distribution of NAD+/NADH in different locations within cells, the direct role of impaired NAD+-dependent processes in humans remains unestablished. In this regard, longitudinal studies are needed to quantify NAD+ and its related metabolites. Future research should focus on measuring the fluxes through pathways associated with NAD+ synthesis and degradation.

Integrative computational approach identifies drug targets in CD4+ T-cell-mediated immune disorders.

CD4+ T cells provide adaptive immunity against pathogens and abnormal cells, and they are also associated with various immune-related diseases. CD4+ T cells' metabolism is dysregulated in these pathologies and represents an opportunity for drug discovery and development. Genome-scale metabolic modeling offers an opportunity to accelerate drug discovery by providing high-quality information about possible target space in the context of a modeled disease. Here, we develop genome-scale models of naïve, Th1, Th2, and Th17 CD4+ T-cell subtypes to map metabolic perturbations in rheumatoid arthritis, multiple sclerosis, and primary biliary cholangitis. We subjected these models to in silico simulations for drug response analysis of existing FDA-approved drugs and compounds. Integration of disease-specific differentially expressed genes with altered reactions in response to metabolic perturbations identified 68 drug targets for the three autoimmune diseases. In vitro experimental validation, together with literature-based evidence, showed that modulation of fifty percent of identified drug targets suppressed CD4+ T cells, further increasing their potential impact as therapeutic interventions. Our approach can be generalized in the context of other diseases, and the metabolic models can be further used to dissect CD4+ T-cell metabolism.