IRE1α–XBP1 controls T cell function in ovarian cancer by regulating mitochondrial activity

Tumours evade immune control by creating hostile microenvironments that perturb T cell metabolism and effector function 1?4 . However, it remains unclear how intra-tumoral T cells integrate and interpret metabolic stress signals. Here we report that ovarian cancer?an aggressive malignancy that is refractory to standard treatments and current immunotherapies 5?8 ?induces endoplasmic reticulum stress and activates the IRE1α?XBP1 arm of the unfolded protein response 9,10 in T cells to control their mitochondrial respiration and anti-tumour function. In T cells isolated from specimens collected from patients with ovarian cancer, upregulation of XBP1 was associated with decreased infiltration of T cells into tumours and with reduced IFNG mRNA expression. Malignant ascites fluid obtained from patients with ovarian cancer inhibited glucose uptake and caused N-linked protein glycosylation defects in T cells, which triggered IRE1α?XBP1 activation that suppressed mitochondrial activity and IFNγ production. Mechanistically, induction of XBP1 regulated the abundance of glutamine carriers and thus limited the influx of glutamine that is necessary to sustain mitochondrial respiration in T cells under glucose-deprived conditions. Restoring N-linked protein glycosylation, abrogating IRE1α?XBP1 activation or enforcing expression of glutamine transporters enhanced mitochondrial respiration in human T cells exposed to ovarian cancer ascites. XBP1-deficient T cells in the metastatic ovarian cancer milieu exhibited global transcriptional reprogramming and improved effector capacity. Accordingly, mice that bear ovarian cancer and lack XBP1 selectively in T cells demonstrate superior anti-tumour immunity, delayed malignant progression and increased overall survival. Controlling endoplasmic reticulum stress or targeting IRE1α?XBP1 signalling may help to restore the metabolic fitness and anti-tumour capacity of T cells in cancer hosts.Fil: Song, Minkyung. Weill Cornell Medicine; Estados UnidosFil: Sandoval, Tito A.. Weill Cornell Medicine; Estados UnidosFil: Chae, Chang-Suk. Weill Cornell Medicine; Estados UnidosFil: Chopra, Sahil. Weill Cornell Medicine; Estados UnidosFil: Tan, Chen. Weill Cornell Medicine; Estados UnidosFil: Rutkowski, Melanie R.. University of Virginia; Estados UnidosFil: Raundhal, Mahesh. Dana Farber Cancer Institute; Estados Unidos. Harvard Medical School; Estados UnidosFil: Chaurio, Ricardo A.. H. Lee Moffitt Cancer Center & Research Institute; Estados UnidosFil: Payne, Kyle K.. H. Lee Moffitt Cancer Center & Research Institute; Estados UnidosFil: Konrad, Csaba. Weill Cornell Medicine; Estados UnidosFil: Bettigole, Sarah E.. Quentis Therapeutics Inc.; Estados UnidosFil: Shin, Hee Rae. Quentis Therapeutics Inc.; Estados UnidosFil: Crowley, Michael J. P.. Weill Cornell Graduate School of Medical Sciences; Estados UnidosFil: Cerliani, Juan Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Kossenkov, Andrew V.. The Wistar Institute; Estados UnidosFil: Motorykin, Ievgen. Weill Cornell Medicine,; Estados UnidosFil: Zhang, Sheng. Weill Cornell Medicine,; Estados UnidosFil: Manfredi, Giovanni. Weill Cornell Medicine,; Estados UnidosFil: Zamarin, Dmitriy. Memorial Sloan Kettering Cancer Center; Estados UnidosFil: Holcomb, Kevin. Weill Cornell Medicine,; Estados UnidosFil: Rodriguez, Paulo C.. H. Lee Moffitt Cancer Center & Research Institute; Estados UnidosFil: Rabinovich, Gabriel Adrián. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; ArgentinaFil: Conejo Garcia, Jose R.. H. Lee Moffitt Cancer Center & Research Institute; Estados UnidosFil: Glimcher, Laurie H.. Dana Farber Cancer Institute; Estados Unidos. Harvard Medical School; Estados UnidosFil: Cubillos-Ruiz, Juan R.. Weill Graduate School Of Medical Sciences; Estados Unidos. Weill Graduate School Of Medical Sciences; Estados Unido

Viral-mediated oncolysis is the most critical factor in the late-phase of the tumor regression process upon vaccinia virus infection

<p>Abstract</p> <p>Background</p> <p>In principle, the elimination of malignancies by oncolytic virotherapy could proceed by different mechanisms - e.g. tumor cell specific oncolysis, destruction of the tumor vasculature or an anti-tumoral immunological response. In this study, we analyzed the contribution of these factors to elucidate the responsible mechanism for regression of human breast tumor xenografts upon colonization with an attenuated vaccinia virus (VACV).</p> <p>Methods</p> <p>Breast tumor xenografts were analyzed 6 weeks post VACV infection (p.i.; regression phase) by immunohistochemistry and mouse-specific expression arrays. Viral-mediated oncolysis was determined by tumor growth analysis combined with microscopic studies of intratumoral virus distribution. The tumor vasculature was morphologically characterized by diameter and density measurements and vessel functionality was analyzed by lectin perfusion and extravasation studies. Immunological aspects of viral-mediated tumor regression were studied in either immune-deficient mouse strains (T-, B-, NK-cell-deficient) or upon cyclophosphamide-induced immunosuppression (MHCII⁺-cell depletion) in nude mice.</p> <p>Results</p> <p>Late stage VACV-infected breast tumors showed extensive necrosis, which was highly specific to cancer cells. The tumor vasculature in infected tumor areas remained functional and the endothelial cells were not infected. However, viral colonization triggers hyperpermeability and dilatation of the tumor vessels, which resembled the activated endothelium in wounded tissue. Moreover, we demonstrated an increased expression of genes involved in leukocyte-endothelial cell interaction in VACV-infected tumors, which orchestrate perivascular inflammatory cell infiltration. The immunohistochemical analysis of infected tumors displayed intense infiltration of MHCII-positive cells and colocalization of tumor vessels with MHCII⁺/CD31⁺vascular leukocytes. However, GI-101A tumor growth analysis upon VACV-infection in either immunosuppressed nude mice (MHCII⁺-cell depleted) or in immune-deficient mouse strains (T-, B-, NK-cell-deficient) revealed that neither MHCII-positive immune cells nor T-, B-, or NK cells contributed significantly to VACV-mediated tumor regression. In contrast, tumors of immunosuppressed mice showed enhanced viral spreading and tumor necrosis.</p> <p>Conclusions</p> <p>Taken together, these results indicate that VACV-mediated oncolysis is the primary mechanism of tumor shrinkage in the late regression phase. Neither the destruction of the tumor vasculature nor the massive VACV-mediated intratumoral inflammation was a prerequisite for tumor regression. We propose that approaches to enhance viral replication and spread within the tumor microenvironment should improve therapeutical outcome.</p

Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject

Functional crosstalk of PGC-1 coactivators and inflammation in skeletal muscle pathophysiology

Skeletal muscle is an organ involved in whole body movement and energy metabolism with the ability to dynamically adapt to different states of (dis-)use. At a molecular level, the peroxisome proliferator-activated receptor γ coactivators 1 (PGC-1s) are important mediators of oxidative metabolism in skeletal muscle and in other organs. Musculoskeletal disorders as well as obesity and its sequelae are associated with PGC-1 dysregulation in muscle with a concomitant local or systemic inflammatory reaction. In this review, we outline the function of PGC-1 coactivators in physiological and pathological conditions as well as the complex interplay of metabolic dysregulation and inflammation in obesity with special focus on skeletal muscle. We further put forward the hypothesis that, in this tissue, oxidative metabolism and inflammatory processes mutually antagonize each other. The nuclear factor κB (NF-κB) pathway thereby plays a key role in linking metabolic and inflammatory programs in muscle cells. We conclude this review with a perspective about the consequences of such a negative crosstalk on the immune system and the possibilities this opens for clinical applications

Low-carbohydrate diets: nutritional and physiological aspects

Recently, diets low in carbohydrate content have become a matter of international attention because of the WHO recommendations to reduce the overall consumption of sugars and rapidly digestible starches. One of the common metabolic changes assumed to take place when a person follows a low-carbohydrate diet is ketosis. Low-carbohydrate intakes result in a reduction of the circulating insulin level, which promotes high level of circulating fatty acids, used for oxidation and production of ketone bodies. It is assumed that when carbohydrate availability is reduced in short term to a significant amount, the body will be stimulated to maximize fat oxidation for energy needs. The currently available scientific literature shows that low-carbohydrate diets acutely induce a number of favourable effects, such as a rapid weight loss, decrease of fasting glucose and insulin levels, reduction of circulating triglyceride levels and improvement of blood pressure. On the other hand some less desirable immediate effects such as enhanced lean body mass loss, increased urinary calcium loss, increased plasma homocysteine levels, increased low-density lipoprotein-cholesterol have been reported. The long-term effect of the combination of these changes is at present not known. The role of prolonged elevated fat consumption along with low-carbohydrate diets should be addressed. However, these undesirable effects may be counteracted with consumption of a low-carbohydrate, high-protein, low-fat diet, because this type of diet has been shown to induce favourable effects on feelings of satiety and hunger, help preserve lean body mass, effectively reduce fat mass and beneficially impact on insulin sensitivity and on blood lipid status while supplying sufficient calcium for bone mass maintenance. The latter findings support the need to do more research on this type of hypocaloric low-carbohydrate diet

Closed formulas in local sensitivity analysis for some classes of linear and non-linear problems

Local sensitivity, Mathematical programming, Duality, Closed formulas for sensitivities, 90C31, 90C05, 90C30,