Similarities and Distinctions of Cancer and Immune Metabolism in Inflammation and Tumors

Andrejeva, Gabriela; Rathmell, Jeffrey C.

doi:10.1016/j.cmet.2017.06.004

Cited by 276 publications

(254 citation statements)

References 305 publications

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“…Non-malignant cells such as immune and stromal cells are important constituents of the tumor microenvironment. These cells are known to differentiate into subtypes with distinct roles, and this process involves metabolic reprogramming to satisfy their cell autonomous metabolic demands and enable interactions with other cell types 10,11,32,33 . Next, we use scRNA-seq to characterize the metabolic features of T cell and fibroblast subpopulations which together constitute the largest non-malignant cell populations in the melanoma and HNSCC datasets.…”

Section: Metabolic Features Of Non-malignant Cell Subtypesmentioning

confidence: 99%

Metabolic landscape of the tumor microenvironment

Xiao

Dai

Locasale

2019

Preprint

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The tumor milieu consists of numerous cell types with each cell existing in a different nutritional environment. However, a characterization of intratumoral metabolic heterogeneity at the single-cell level in human cancer is not established. Here, we develop a computational pipeline to analyze metabolic gene expression programs of single cells within human tumors. In two representative cancer types, melanoma and head and neck, we apply this algorithm to define the single-cell metabolic landscape of human tumors. We find that malignant cells in general have higher metabolic activity and higher metabolic variation than previously observed from studies of bulk tumor comparisons. Indeed, most of the observed metabolic variation of single tumor and normal cells were found to be inconsistent with comparisons with bulk tumor samples. Variation in the expression of mitochondrial programs is the major contributor to intratumoral metabolic heterogeneity. Surprisingly, the expression of both glycolytic and mitochondrial programs strongly correlates with hypoxia in almost all cell types. Immune and stromal cells could also be distinguished by their metabolic features.Taken together this analysis establishes a computational framework for characterizing metabolism using single cell expression data and defines principles of intratumoral metabolic heterogeneity.

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Section: Metabolic Features Of Non-malignant Cell Subtypesmentioning

confidence: 99%

Metabolic landscape of the tumor microenvironment

Xiao

Dai

Locasale

2019

Preprint

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“…Meanwhile, the transition to the memory T cell fate is associated with the inhibition of PI3K/mTORC1 signaling and silencing of aerobic glycolysis by AMP-activated protein kinase (AMPK) in favor of mitochondrial biogenesis and fusion 8,14,15,16 , which is mediated by peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1a) 11,17 .…”

Section: Introductionmentioning

confidence: 99%

“…However, integrating the measurement of metabolism into these studies remains largely unexplored. Many of the regulatory mechanisms that govern cellular metabolism are posttranslational and therefore not directly measurable by sequencing 17 . Therefore, to comprehensively assess the coordinated program dictating CD8 T cell fate and function, a single-cell proteomic approach provides unique opportunities.…”

Section: Introductionmentioning

confidence: 99%

Single-cell metabolic dynamics of early activated CD8 T cells during the primary immune response to infection

Levine

Hiam

Márquez

et al. 2020

Preprint

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Mass cytometry permits high-dimensional analysis of diverse aspects of cellular behavior. Here, we adapted this platform to simultaneously profile metabolism, signaling, cell cycle, and effector function with single-cell resolution. Using this approach, we measured enzymes characterizing glycolysis, the TCA cycle, fatty acid oxidation, oxidative phosphorylation, and nutrient transport.In conjunction, we measured downstream targets of TCR signaling regulating translation, proliferation and cytotoxicity as well as surface markers and transcription factors delineating CD8 T cell differentiation. High-dimensional single-cell metabolic analysis by mass cytometry permits identification of unique metabolic and differentiation states of extremely rare cell populations, such as antigen-specific T cells. We interrogated antigen-specific CD8 T cell activation in vitro as well as the trajectory of CD8 T cells responding to Listeria monocytogenes infection, a well-characterized model for studies of T cell differentiation. This integrated, highdimensional approach revealed a novel, activated, and highly metabolically active transitional T cell subset emerging at four days post-infection. These cells simultaneously exhibit glycolytic and oxidative functional programs, which we propose represents a key metabolic inflection point in CD8+ T cell differentiation. This approach should be useful for mechanistic investigations of metabolic regulation of immune responses in vivo.Recombinant human IL-2 (IL-2; TECIN (Teceleukin)) was provided by the National Cancer Institute.

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“…There is growing support for a strong link between metabolism and inflammation (Andrejeva and Rathmell, 2017;Bettencourt and Powell, 2017). Various fasting regimes are known to provide many health benefits including anti-inflammatory effects (Corrales et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Long non-coding RNA Gm15441 attenuates hepatic inflammasome activation in response to metabolic stress

Brocker

Kim

Melia

et al. 2019

Preprint

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Fasting paradigms elicit a wide-range of health benefits including suppressing inflammation.Exploring the molecular mechanisms that prevent inflammation during caloric restriction may yield promising new therapeutic targets. During fasting, activation of the nuclear receptor peroxisome proliferator-activated receptor alpha (PPARA) promotes the utilization of lipids as an energy source. Herein, we show that ligand activation of PPARA directly upregulates the long non-coding RNA gene Gm15441 through binding sites within its promoter. Gm15441 expression suppresses its antisense transcript, encoding thioredoxin interacting protein (TXNIP). This, in turn, decreases TXNIP-stimulated NLRP3 inflammasome activation, caspase-1 (CASP1) cleavage, and proinflammatory interleukin 1 beta (IL1B) maturation. Gm15441-null mice were developed and shown to be more susceptible to NLRP3 inflammasome activation and to exhibit elevated CASP1 and IL1B cleavage in response to metabolic and inflammatory stimuli. These findings provide evidence for a novel mechanism by which PPARA attenuates hepatic inflammasome activation in response to metabolic stress through lncRNA Gm15441 induction. 4Txnip expression in vivo. Gm15441 LSL mice were treated with a PPARA agonist or fasted to assess how loss of Gm15441 impacts hepatic inflammasome activation in response to both pharmacological and physiologically-induced metabolic stress. TXNIP protein, caspase-1 (CASP1) levels, and interleukin 1 beta (IL1B) cleavage were elevated in Gm15441 LSL mice and were further increased by PPARA activation, indicating that this lncRNA plays a major role in attenuating inflammasome activation. Thus, hepatic PPARA directly regulates the lncRNA Gm15441, which in turn suppresses Txnip expression, which attenuates NLRP3 inflammasome activation during periods of metabolic stress. These studies revealed a novel regulatory mechanism supporting the beneficial effects of fasting, namely, reduced inflammation. Results LncRNA regulation by PPARA is highly tissue-specificTo assess the regulation of lncRNAs by PPARA, RNA-seq was performed using total liver RNA isolated from Ppara +/+ mice, both with and without dietary exposure to the PPARA agonist WY-14643. A lncRNA discovery pipeline was implemented that identified 15,558 liver-expressed lncRNA genes. Of these, 13,343 were intergenic, 1,966 were antisense, and 249 were intragenic lncRNAs. 44% of the 15,558 liver-expressed lncRNAs are considered novel (Melia and Waxman, 2019). Differential gene expression analysis revealed that a total of 1,735 RefSeq genes and 442 liver-expressed lncRNA genes responded to treatment with WY-14643 at an expression foldchange >2 at FDR<0.05, with 968 RefSeq genes and 245 lncRNA genes upregulated, and 767

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Similarities and Distinctions of Cancer and Immune Metabolism in Inflammation and Tumors

Cited by 276 publications

References 305 publications

Metabolic landscape of the tumor microenvironment

Metabolic landscape of the tumor microenvironment

Single-cell metabolic dynamics of early activated CD8 T cells during the primary immune response to infection

Long non-coding RNA Gm15441 attenuates hepatic inflammasome activation in response to metabolic stress

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