provided expertise to develop 18 F nutrient uptake assays. F.X. and M.N.T injected and handled mice for 18 F nutrient uptake assays, and performed and provided expertise for PET imaging and autoradiography. T.H. and W.D.M. performed and provided expertise for intrarenal Renca experiments. R.W.J. and V.T.M generated and provided expertise for PyMT GEMM tumors. R.E.B and C.S.W. generated and provided expertise for AOM/DSS CRC tumors. B.I.R. R.T.O. and M.H.W. generated the pTZeo-EL-thy1.1 transposon construct and engineered MC38 cells using this transposon system. B.I.R, M.Z.M, and A.S. performed in vivo 2NBDG studies. J.E.B. provided expertise in characterizing TAM. A.R.P provided expertise in flow sorting for mRNA transcript analysis. B.I.R. and M.Z.M performed extracellular flux and mRNA transcript experiments. F.M.M. and E.F.M performed and provided expertise in cell staining for light microscopy. E.F.M performed light microscopy and pathologic examination of MC38 tumors. A.A (VU) conducted transcriptomic analysis. B.I.R and M.Z.M. analyzed all data generated in this study. J.C.R. and W.K.R. obtained funding for this study.Data Availability Statement (DAS) All data will be made available upon reasonable request to JCR/WKR. Tumor mRNA transcript data that support the findings of this study have been deposited in Gene Expression Omnibus (GEO) under accession GSE165223. These data are also found in Supplementary Information Table 4. Code Availability Statement (CAS)The code used to support tumor mRNA transcript analysis has been previously published (see methods references) and will be made available upon request to JCR/WKR.

No abstract

No abstract

BackgroundImmune checkpoint inhibitors, the most widespread class of immunotherapies, have demonstrated unique response patterns that are not always adequately captured by traditional response criteria such as the Response Evaluation Criteria in Solid Tumors or even immune-specific response criteria. These response metrics rely on monitoring tumor growth, but an increase in tumor size and/or appearance after starting immunotherapy does not always represent tumor progression, but also can be a result of T cell infiltration and thus positive treatment response. Therefore, non-invasive and longitudinal monitoring of T cell infiltration are needed to assess the effects of immunotherapies such as checkpoint inhibitors. Here, we proposed an innovative concept that a sufficiently large influx of tumor infiltrating T cells, which have a smaller diameter than cancer cells, will change the diameter distribution and decrease the average size of cells within a volume to a degree that can be quantified by non-invasive MRI.MethodsWe validated our hypothesis by studying tumor response to combination immune-checkpoint blockade (ICB) of anti-PD-1 and anti-CTLA4 in a mouse model of colon adenocarcinoma (MC38). The response was monitored longitudinally using Imaging Microstructural Parameters Using Limited Spectrally Edited Diffusion (IMPULSED), a diffusion MRI-based method which has been previously shown to non-invasively map changes in intracellular structure and cell sizes with the spatial resolution of MRI, in cell cultures and in animal models. Tumors were collected for immunohistochemical and flow cytometry analyzes immediately after the last imaging session.ResultsImmunohistochemical analysis revealed that increased T cell infiltration of the tumors results in a decrease in mean cell size (eg, a 10% increase of CD3+ T cell fraction results a ~1 µm decrease in the mean cell size). IMPULSED showed that the ICB responders, mice with tumor volumes were less than 250 mm3 or had tumors with stable or decreased volumes, had significantly smaller mean cell sizes than both Control IgG-treated tumors and ICB non-responder tumors.ConclusionsIMPULSED-derived cell size could potentially serve as an imaging marker for differentiating responsive and non-responsive tumors after checkpoint inhibitor therapies, a current clinical challenge that is not solved by simply monitoring tumor growth.

T effector cells promote inflammation in asthmatic patients, and both Th2 and Th17 CD4 T cells have been implicated in severe forms of the disease. The metabolic phenotypes and dependencies of these cells, however, remain poorly understood in the regulation of airway inflammation. In this study, we show the bronchoalveolar lavage fluid of asthmatic patients had markers of elevated glucose and glutamine metabolism. Further, peripheral blood T cells of asthmatics had broadly elevated expression of metabolic proteins when analyzed by mass cytometry compared with healthy controls. Therefore, we hypothesized that glucose and glutamine metabolism promote allergic airway inflammation. We tested this hypothesis in two murine models of airway inflammation. T cells from lungs of mice sensitized with Alternaria alternata extract displayed genetic signatures for elevated oxidative and glucose metabolism by single-cell RNA sequencing. This result was most pronounced when protein levels were measured in IL-17–producing cells and was recapitulated when airway inflammation was induced with house dust mite plus LPS, a model that led to abundant IL-4– and IL-17–producing T cells. Importantly, inhibitors of the glucose transporter 1 or glutaminase in vivo attenuated house dust mite + LPS eosinophilia, T cell cytokine production, and airway hyperresponsiveness as well as augmented the immunosuppressive properties of dexamethasone. These data show that T cells induce markers to support metabolism in vivo in airway inflammation and that this correlates with inflammatory cytokine production. Targeting metabolic pathways may provide a new direction to protect from disease and enhance the effectiveness of steroid therapy.