Lenvatinib is a multiple receptor tyrosine kinase inhibitor targeting mainly vascular endothelial growth factor (VEGF) and fibroblast growth factor (FGF) receptors. We investigated the immunomodulatory activities of lenvatinib in the tumor microenvironment and its mechanisms of enhanced antitumor activity when combined with a programmed cell death-1 (PD-1) blockade. Antitumor activity was examined in immunodeficient and immunocompetent mouse tumor models. Single-cell analysis, flow cytometric analysis, and immunohistochemistry were used to analyze immune cell populations and their activation. Gene co-expression network analysis and pathway analysis using RNA sequencing data were used to identify lenvatinib-driven combined activity with anti-PD-1 antibody (anti-PD-1). Lenvatinib showed potent antitumor activity in the immunocompetent tumor microenvironment compared with the immunodeficient tumor microenvironment. Antitumor activity of lenvatinib plus anti-PD-1 was greater than that of either single treatment. Flow cytometric analysis revealed that lenvatinib reduced tumor-associated macrophages (TAMs) and increased the percentage of activated CD8 + T cells secreting interferon (IFN)-γ + and granzyme B (GzmB). Combination treatment further increased the percentage of T cells, especially CD8 + T cells, among CD45 + cells and increased IFN-γ + and GzmB + CD8 + T cells. Transcriptome analyses of tumors resected from treated mice showed that genes specifically regulated by the combination were significantly enriched for type-I IFN signaling. Pretreatment with lenvatinib followed by anti-PD-1 treatment induced significant antitumor activity compared with anti-PD-1 treatment alone. Our findings show that lenvatinib modulates cancer immunity in the tumor microenvironment by reducing TAMs and, when combined with PD-1 blockade, shows enhanced antitumor activity via the IFN signaling pathway. These findings provide a scientific rationale for combination therapy of lenvatinib with PD-1 blockade to improve cancer immunotherapy.

Local responses of energy metabolism during brain ischemia are too heterogeneous to decipher redox distribution between anoxic core and adjacent salvageable regions such as penumbra. Imaging mass spectrometry combined by capillary electrophoresis=mass spectrometry providing quantitative metabolomics revealed spatiotemporal changes in adenylates and NADH in a mouse middle-cerebral artery occlusion model. Unlike the core where ATP decreased, the penumbra displayed paradoxical elevation of ATP despite the constrained blood supply. It is noteworthy that the NADH elevation in the ischemic region is clearly demarcated by the ATPdepleting core. Results suggest that metabolism in ischemic penumbra does not respond passively to compromised circulation, but actively compensates energy charges. Antioxid. Redox Signal. 13, 1157-1167. Quantitative Imaging Mass Spectrometry as a Novel Tactics to Decipher Metabolic Dynamics of Brain IschemiaT o develop neuroprotective therapies for cerebrovascular diseases, it is necessary to characterize spatiotemporal changes in energy metabolism occurring at two functionally defined areas of ischemic brain: one is the ischemic core, which is unsalvageable, and another is its adjacent zone termed penumbra, which is salvageable by interventions. Such characterization requires technical breakthrough including simultaneous identification of multiple compounds comprising energy metabolic systems and quantitative analytical methods sensitive enough to detect low levels of metabolites in the heterogeneous regions of ischemic brain. To achieve these requirements, we combined two types of mass spectrometry (MS): matrix-assisted laser desorption ionization (MALDI)=MS and capillary electrophoresis=electrospray ionization (CE=ESI)=MS. Unlike conventional spectroscopic techniques with which chemical profiles are obtained from one selected volume at a time, MALDI=MS has strengths in visualizing multiple metabolites in discrete areas with a single laser ablation (10, 26, 32). However, it still requires further efforts to be supported for quantification. By contrast, CE=ESI=MS excels in quantification of metabolites (15,22,23) because ESI is efficient in transferring molecules from liquid phase to gas phase. Comparison of transcriptional expression profiles with CE=ESI= MS-based metabolomics previously led us to hypothesize the existence of novel metabolic pathways (33) and their regulatory mechanisms (15,22,23). However, it removes spatial distribution of molecules due to tissue homogenization to extract metabolites.Using imaging MS (IMS) combined with CE=ESI=MS, we herein constructed maps of adenine nucleotides whereby abundance of these metabolites was assigned in absolute terms, that is, mmol=g tissue. Such assignment of contents made it possible to directly compare patterns of biochemical derangements in and around the ischemic core at different time points during infarction. Our results suggest that, unlike the core, the penumbra displays paradoxical elevation of ATP despite the constrained b...

Reprogramming is a dynamic process that can result in multiple pluripotent cell types emerging from divergent paths. Cell surface protein expression is a particularly desirable tool to categorize reprogramming and pluripotency as it enables robust quantification and enrichment of live cells. Here we use cell surface proteomics to interrogate mouse cell reprogramming dynamics and discover CD24 as a marker that tracks the emergence of reprogramming-responsive cells, while enabling the analysis and enrichment of transgene-dependent (F-class) and -independent (traditional) induced pluripotent stem cells (iPSCs) at later stages. Furthermore, CD24 can be used to delineate epiblast stem cells (EpiSCs) from embryonic stem cells (ESCs) in mouse pluripotent culture. Importantly, regulated CD24 expression is conserved in human pluripotent stem cells (PSCs), tracking the conversion of human ESCs to more naive-like PSC states. Thus, CD24 is a conserved marker for tracking divergent states in both reprogramming and standard pluripotent culture.

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Pluripotent stem cells (PSCs) exist in multiple stable states, each with specific cellular properties and molecular signatures. The mechanisms that maintain pluripotency, or that cause its destabilization to initiate development, are complex and incompletely understood. We have developed a model to predict stabilized PSC gene regulatory network (GRN) states in response to input signals. Our strategy used random asynchronous Boolean simulations (R‐ABS) to simulate single‐cell fate transitions and strongly connected components (SCCs) strategy to represent population heterogeneity. This framework was applied to a reverse‐engineered and curated core GRN for mouse embryonic stem cells (mESCs) and used to simulate cellular responses to combinations of five signaling pathways. Our simulations predicted experimentally verified cell population compositions and input signal combinations controlling specific cell fate transitions. Extending the model to PSC differentiation, we predicted a combination of signaling activators and inhibitors that efficiently and robustly generated a Cdx2+Oct4− cells from naïve mESCs. Overall, this platform provides new strategies to simulate cell fate transitions and the heterogeneity that typically occurs during development and differentiation.