Distinct Regulation of Th17 and Th1 Cell Differentiation by Glutaminase-Dependent Metabolism.

Activated T cells differentiate into functional subsets with distinct metabolic programs. Glutaminase (GLS) converts glutamine to glutamate to support the tricarboxylic acid cycle and redox and epigenetic reactions. Here, we identify a key role for GLS in T cell activation and specification. Though GLS deficiency diminished initial T cell activation and proliferation and impaired differentiation of Th17 cells, loss of GLS also increased Tbet to promote differentiation and effector function of CD4 Th1 and CD8 CTL cells. This was associated with altered chromatin accessibility and gene expression, including decreased PIK3IP1 in Th1 cells that sensitized to IL-2-mediated mTORC1 signaling. In vivo, GLS null T cells failed to drive Th17-inflammatory diseases, and Th1 cells had initially elevated function but exhausted over time. Transient GLS inhibition, however, led to increased Th1 and CTL T cell numbers. Glutamine metabolism thus has distinct roles to promote Th17 but constrain Th1 and CTL effector cell differentiation.

MTHFD2 is a metabolic checkpoint controlling effector and regulatory T cell fate and function.

Antigenic stimulation promotes T cell metabolic reprogramming to meet increased biosynthetic, bioenergetic, and signaling demands. We show that the one-carbon (1C) metabolism enzyme methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) regulates de novo purine synthesis and signaling in activated T cells to promote proliferation and inflammatory cytokine production. In pathogenic T helper-17 (Th17) cells, MTHFD2 prevented aberrant upregulation of the transcription factor FoxP3 along with inappropriate gain of suppressive capacity. MTHFD2 deficiency also promoted regulatory T (Treg) cell differentiation. Mechanistically, MTHFD2 inhibition led to depletion of purine pools, accumulation of purine biosynthetic intermediates, and decreased nutrient sensor mTORC1 signaling. MTHFD2 was also critical to regulate DNA and histone methylation in Th17 cells. Importantly, MTHFD2 deficiency reduced disease severity in multiple in vivo inflammatory disease models. MTHFD2 is thus a metabolic checkpoint to integrate purine metabolism with pathogenic effector cell signaling and is a potential therapeutic target within 1C metabolism pathways.

Obesity induces PD-1 on macrophages to suppress anti-tumour immunity.

Obesity is a leading risk factor for progression and metastasis of many cancers1,2, yet can in some cases enhance survival3-5 and responses to immune checkpoint blockade therapies, including anti-PD-1, which targets PD-1 (encoded by PDCD1), an inhibitory receptor expressed on immune cells6-8. Although obesity promotes chronic inflammation, the role of the immune system in the obesity-cancer connection and immunotherapy remains unclear. It has been shown that in addition to T cells, macrophages can express PD-19-12. Here we found that obesity selectively induced PD-1 expression on tumour-associated macrophages (TAMs). Type I inflammatory cytokines and molecules linked to obesity, including interferon-γ, tumour necrosis factor, leptin, insulin and palmitate, induced macrophage PD-1 expression in an mTORC1- and glycolysis-dependent manner. PD-1 then provided negative feedback to TAMs that suppressed glycolysis, phagocytosis and T cell stimulatory potential. Conversely, PD-1 blockade increased the level of macrophage glycolysis, which was essential for PD-1 inhibition to augment TAM expression of CD86 and major histocompatibility complex I and II molecules and ability to activate T cells. Myeloid-specific PD-1 deficiency slowed tumour growth, enhanced TAM glycolysis and antigen-presentation capability, and led to increased CD8+ T cell activity with a reduced level of markers of exhaustion. These findings show that obesity-associated metabolic signalling and inflammatory cues cause TAMs to induce PD-1 expression, which then drives a TAM-specific feedback mechanism that impairs tumour immune surveillance. This may contribute to increased cancer risk yet improved response to PD-1 immunotherapy in obesity.

Cell-programmed nutrient partitioning in the tumour microenvironment.

Cancer cells characteristically consume glucose through Warburg metabolism1, a process that forms the basis of tumour imaging by positron emission tomography (PET). Tumour-infiltrating immune cells also rely on glucose, and impaired immune cell metabolism in the tumour microenvironment (TME) contributes to immune evasion by tumour cells2-4. However, whether the metabolism of immune cells is dysregulated in the TME by cell-intrinsic programs or by competition with cancer cells for limited nutrients remains unclear. Here we used PET tracers to measure the access to and uptake of glucose and glutamine by specific cell subsets in the TME. Notably, myeloid cells had the greatest capacity to take up intratumoral glucose, followed by T cells and cancer cells, across a range of cancer models. By contrast, cancer cells showed the highest uptake of glutamine. This distinct nutrient partitioning was programmed in a cell-intrinsic manner through mTORC1 signalling and the expression of genes related to the metabolism of glucose and glutamine. Inhibiting glutamine uptake enhanced glucose uptake across tumour-resident cell types, showing that glutamine metabolism suppresses glucose uptake without glucose being a limiting factor in the TME. Thus, cell-intrinsic programs drive the preferential acquisition of glucose and glutamine by immune and cancer cells, respectively. Cell-selective partitioning of these nutrients could be exploited to develop therapies and imaging strategies to enhance or monitor the metabolic programs and activities of specific cell populations in the TME.

Differential Effects of Glutamine Inhibition Strategies on Antitumor CD8 T Cells.

Activated T cells undergo metabolic reprogramming to meet anabolic, differentiation, and functional demands. Glutamine supports many processes in activated T cells, and inhibition of glutamine metabolism alters T cell function in autoimmune disease and cancer. Multiple glutamine-targeting molecules are under investigation, yet the precise mechanisms of glutamine-dependent CD8 T cell differentiation remain unclear. We show that distinct strategies of glutamine inhibition by glutaminase-specific inhibition with small molecule CB-839, pan-glutamine inhibition with 6-diazo-5-oxo-l-norleucine (DON), or by glutamine-depleted conditions (No Q) produce distinct metabolic differentiation trajectories in murine CD8 T cells. T cell activation with CB-839 treatment had a milder effect than did DON or No Q treatment. A key difference was that CB-839-treated cells compensated with increased glycolytic metabolism, whereas DON and No Q-treated cells increased oxidative metabolism. However, all glutamine treatment strategies elevated CD8 T cell dependence on glucose metabolism, and No Q treatment caused adaptation toward reduced glutamine dependence. DON treatment reduced histone modifications and numbers of persisting cells in adoptive transfer studies, but those T cells that remained could expand normally upon secondary Ag encounter. In contrast, No Q-treated cells persisted well yet demonstrated decreased secondary expansion. Consistent with reduced persistence, CD8 T cells activated in the presence of DON had reduced ability to control tumor growth and reduced tumor infiltration in adoptive cell therapy. Overall, each approach to inhibit glutamine metabolism confers distinct effects on CD8 T cells and highlights that targeting the same pathway in different ways can elicit opposing metabolic and functional outcomes.

dynamic : An R Package for Deriving Dynamic Fit Index Cutoffs for Factor Analysis.

To evaluate the fit of a confirmatory factor analysis model, researchers often rely on fit indices such as SRMR, RMSEA, and CFI. These indices are frequently compared to benchmark values of .08, .06, and .96, respectively, established by Hu and Bentler (Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1-55). However, these indices are affected by model characteristics and their sensitivity to misfit can change across models. Decisions about model fit can therefore be improved by tailoring cutoffs to each model. The methodological literature has proposed methods for deriving customized cutoffs, although it can require knowledge of linear algebra and Monte Carlo simulation. Given that many empirical researchers do not have training in these technical areas, empirical studies largely continue to rely on fixed benchmarks even though they are known to generalize poorly and can be poor arbiters of fit. To address this, this paper introduces the R package, dynamic, to make computation of dynamic fit index cutoffs (which are tailored to the user's model) more accessible to empirical researchers. dynamic heavily automatizes this process and only requires a lavaan object to automatically conduct several custom Monte Carlo simulations and output fit index cutoffs designed to be sensitive to misfit with the user's model characteristics.

Dynamic fit index cutoffs for one-factor models.

Assessing whether a multiple-item scale can be represented with a one-factor model is a frequent interest in behavioral research. Often, this is done in a factor analysis framework with approximate fit indices like RMSEA, CFI, or SRMR. These fit indices are continuous measures, so values indicating acceptable fit are up to interpretation. Cutoffs suggested by Hu and Bentler (1999) are a common guideline used in empirical research. However, these cutoffs were derived with intent to detect omitted cross-loadings or omitted factor covariances in multifactor models. These types of misspecifications cannot exist in one-factor models, so the appropriateness of using these guidelines in one-factor models is uncertain. This paper uses a simulation study to address whether traditional fit index cutoffs are sensitive to the types of misspecifications common in one-factor models. The results showed that traditional cutoffs have very poor sensitivity to misspecification in one-factor models and that the traditional cutoffs generalize poorly to one-factor contexts. As an alternative, we investigate the accuracy and stability of the recently introduced dynamic fit cutoff approach for creating fit index cutoffs for one-factor models. Simulation results indicated excellent performance of dynamic fit index cutoffs to classify correct or misspecified one-factor models and that dynamic fit index cutoffs are a promising approach for more accurate assessment of model fit in one-factor contexts.

Thinking twice about sum scores.

A common way to form scores from multiple-item scales is to sum responses of all items. Though sum scoring is often contrasted with factor analysis as a competing method, we review how factor analysis and sum scoring both fall under the larger umbrella of latent variable models, with sum scoring being a constrained version of a factor analysis. Despite similarities, reporting of psychometric properties for sum scored or factor analyzed scales are quite different. Further, if researchers use factor analysis to validate a scale but subsequently sum score the scale, this employs a model that differs from validation model. By framing sum scoring within a latent variable framework, our goal is to raise awareness that (a) sum scoring requires rather strict constraints, (b) imposing these constraints requires the same type of justification as any other latent variable model, and (c) sum scoring corresponds to a statistical model and is not a model-free arithmetic calculation. We discuss how unjustified sum scoring can have adverse effects on validity, reliability, and qualitative classification from sum score cut-offs. We also discuss considerations for how to use scale scores in subsequent analyses and how these choices can alter conclusions. The general goal is to encourage researchers to more critically evaluate how they obtain, justify, and use multiple-item scale scores.

HIF-2α expression and metabolic signaling require ACSS2 in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is an aggressive cancer driven by VHL loss and aberrant HIF-2α signaling. Identifying means to regulate HIF-2α thus has potential therapeutic benefit. Acetyl-CoA synthetase 2 (ACSS2) converts acetate to acetyl-CoA and is associated with poor patient prognosis in ccRCC. Here we tested the effects of ACSS2 on HIF-2α and cancer cell metabolism and growth in ccRCC models and clinical samples. ACSS2 inhibition reduced HIF-2α levels and suppressed ccRCC cell line growth in vitro, in vivo, and in cultures of primary ccRCC patient tumors. This treatment reduced glycolytic signaling, cholesterol metabolism, and mitochondrial integrity, all of which are consistent with loss of HIF-2α. Mechanistically, ACSS2 inhibition decreased chromatin accessibility and HIF-2α expression and stability. While HIF-2α protein levels are widely regulated through pVHL-dependent proteolytic degradation, we identify a potential pVHL-independent pathway of degradation via the E3 ligase MUL1. We show that MUL1 can directly interact with HIF-2α and that overexpression of MUL1 decreased HIF-2α levels in a manner partially dependent on ACSS2. These findings identify multiple mechanisms to regulate HIF-2α stability and ACSS2 inhibition as a strategy to complement HIF-2α-targeted therapies and deplete pathogenically stabilized HIF-2α.

VHL loss reprograms the immune landscape to promote an inflammatory myeloid microenvironment in renal tumorigenesis.

Clear cell renal cell carcinoma (ccRCC) is characterized by dysregulated hypoxia signaling and a tumor microenvironment (TME) highly enriched in myeloid and lymphoid cells. Loss of the von Hippel Lindau (VHL) gene is a critical early event in ccRCC pathogenesis and promotes stabilization of HIF. Whether VHL loss in cancer cells affects immune cells in the TME remains unclear. Using Vhl WT and Vhl-KO in vivo murine kidney cancer Renca models, we found that Vhl-KO tumors were more infiltrated by immune cells. Tumor-associated macrophages (TAMs) from Vhl-deficient tumors demonstrated enhanced in vivo glucose consumption, phagocytosis, and inflammatory transcriptional signatures, whereas lymphocytes from Vhl-KO tumors showed reduced activation and a lower response to anti-programmed cell death 1 (anti-PD-1) therapy in vivo. The chemokine CX3CL1 was highly expressed in human ccRCC tumors and was associated with Vhl deficiency. Deletion of Cx3cl1 in cancer cells decreased myeloid cell infiltration associated with Vhl loss to provide a mechanism by which Vhl loss may have contributed to the altered immune landscape. Here, we identify cancer cell-specific genetic features that drove environmental reprogramming and shaped the tumor immune landscape, with therapeutic implications for the treatment of ccRCC.

Dynamic fit index cutoffs for confirmatory factor analysis models.

Model fit assessment is a central component of evaluating confirmatory factor analysis models and the validity of psychological assessments. Fit indices remain popular and researchers often judge fit with fixed cutoffs derived by Hu and Bentler (1999). Despite their overwhelming popularity, methodological studies have cautioned against fixed cutoffs, noting that the meaning of fit indices varies based on a complex interaction of model characteristics like factor reliability, number of items, and number of factors. Criticism of fixed cutoffs stems primarily from the fact that they were derived from one specific confirmatory factor analysis model and lack generalizability. To address this, we propose a simulation-based method called dynamic fit index cutoffs such that derivation of cutoffs is adaptively tailored to the specific model and data characteristics being evaluated. Unlike previously proposed simulation-based techniques, our method removes existing barriers to implementation by providing an open-source, Web based Shiny software application that automates the entire process so that users neither need to manually write any software code nor be knowledgeable about foundations of Monte Carlo simulation. Additionally, we extend fit index cutoff derivations to include sets of cutoffs for multiple levels of misspecification. In doing so, fit indices can more closely resemble their originally intended purpose as effect sizes quantifying misfit rather than improperly functioning as ad hoc hypothesis tests. We also provide an approach specifically designed for the nuances of 1-factor models, which have received surprisingly little attention in the literature despite frequent substantive interests in unidimensionality. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Survey Uses May Influence Survey Responses.

Traditional validation processes for psychological surveys tend to focus on analyzing item responses instead of the cognitive processes that participants use to generate these responses. When screening for invalid responses, researchers typically focus on participants who manipulate their answers for personal gain or respond carelessly. In this paper, we introduce a new invalid response process, discordant responding, that arises when participants disagree with the use of the survey and discuss similarities and differences between this response style and protective responding. Results show that nearly all participants reflect on the intended uses of an assessment when responding to items and may decline to respond or modify their responses if they are not comfortable with the way the results will be used. Incidentally, we also find that participants may misread survey instructions if they are not interactive. We introduce a short screener to detect invalid responses, the discordant response identifiers (DRI), which provides researchers with a simple validity tool to use when validating surveys. Finally, we provide recommendations about how researchers may use these findings to design surveys that reduce this response manipulation in the first place.

The Inventory of Nonordinary Experiences (INOE): Evidence of validity in the United States and India.

Researchers increasingly recognize that the mind and culture interact at many levels to constitute our lived experience, yet we know relatively little about the extent to which culture shapes the way people appraise their experiences and the likelihood that a given experience will be reported. Experiences that involve claims regarding deities, extraordinary abilities, and/or psychopathology offer an important site for investigating the interplay of mind and culture at the population level. However, the difficulties inherent in comparing culture-laden experiences, exacerbated by the siloing of research on experiences based on discipline-specific theoretical constructs, have limited our ability to do so. We introduce the Inventory of Nonordinary Experiences (INOE), which allows researchers to compare experiences by separating the phenomenological features from how they are appraised and asking about both. It thereby offers a new means of investigating the potentially universal (etic) and culture-specific (emic) aspects of lived experiences. To ensure that the INOE survey items are understood as intended by English speakers in the US and Hindi speakers in India, and thus can serve as a basis for cross-cultural comparison, we used the Response Process Evaluation (RPE) method to collect evidence of item-level validity. Our inability to validate some items drawn from other surveys suggests that they are capturing a wider range of experiences than researchers intend. Wider use of the RPE method would increase the likelihood that survey results are due to the differences that researchers intend to measure.

Immunogenicity in renal cell carcinoma: shifting focus to alternative sources of tumour-specific antigens.

Renal cell carcinoma (RCC) comprises a group of malignancies arising from the kidney with unique tumour-specific antigen (TSA) signatures that can trigger cytotoxic immunity. Two classes of TSAs are now considered potential drivers of immunogenicity in RCC: small-scale insertions and deletions (INDELs) that result in coding frameshift mutations, and activation of human endogenous retroviruses. The presence of neoantigen-specific T cells is a hallmark of solid tumours with a high mutagenic burden, which typically have abundant TSAs owing to non-synonymous single nucleotide variations within the genome. However, RCC exhibits high cytotoxic T cell reactivity despite only having an intermediate non-synonymous single nucleotide variation mutational burden. Instead, RCC tumours have a high pan-cancer proportion of INDEL frameshift mutations, and coding frameshift INDELs are associated with high immunogenicity. Moreover, cytotoxic T cells in RCC subtypes seem to recognize tumour-specific endogenous retrovirus epitopes, whose presence is associated with clinical responses to immune checkpoint blockade therapy. Here, we review the distinct molecular landscapes in RCC that promote immunogenic responses, discuss clinical opportunities for discovery of biomarkers that can inform therapeutic immune checkpoint blockade strategies, and identify gaps in knowledge for future investigations.

Tissue-Specific Dependence of Th1 Cells on the Amino Acid Transporter SLC38A1 in Inflammation.

Amino acid (AA) uptake is essential for T cell metabolism and function, but how tissue sites and inflammation affect CD4+ T cell subset requirements for specific AA remains uncertain. Here we tested CD4+ T cell AA demands with in vitro and multiple in vivo CRISPR screens and identify subset- and tissue-specific dependencies on the AA transporter SLC38A1 (SNAT1). While dispensable for T cell persistence and expansion over time in vitro and in vivo lung inflammation, SLC38A1 was critical for Th1 but not Th17 cell-driven Experimental Autoimmune Encephalomyelitis (EAE) and contributed to Th1 cell-driven inflammatory bowel disease. SLC38A1 deficiency reduced mTORC1 signaling and glycolytic activity in Th1 cells, in part by reducing intracellular glutamine and disrupting hexosamine biosynthesis and redox regulation. Similarly, pharmacological inhibition of SLC38 transporters delayed EAE but did not affect lung inflammation. Subset- and tissue-specific dependencies of CD4+ T cells on AA transporters may guide selective immunotherapies.

STING-activating nanoparticles normalize the vascular-immune interface to potentiate cancer immunotherapy.

The tumor-associated vasculature imposes major structural and biochemical barriers to the infiltration of effector T cells and effective tumor control. Correlations between stimulator of interferon genes (STING) pathway activation and spontaneous T cell infiltration in human cancers led us to evaluate the effect of STING-activating nanoparticles (STANs), which are a polymersome-based platform for the delivery of a cyclic dinucleotide STING agonist, on the tumor vasculature and attendant effects on T cell infiltration and antitumor function. In multiple mouse tumor models, intravenous administration of STANs promoted vascular normalization, evidenced by improved vascular integrity, reduced tumor hypoxia, and increased endothelial cell expression of T cell adhesion molecules. STAN-mediated vascular reprogramming enhanced the infiltration, proliferation, and function of antitumor T cells and potentiated the response to immune checkpoint inhibitors and adoptive T cell therapy. We present STANs as a multimodal platform that activates and normalizes the tumor microenvironment to enhance T cell infiltration and function and augments responses to immunotherapy.

Who Opts In to Alcohol Feedback and How Does That Impact Behavior? A Pilot Trial.

OBJECTIVE: Personalized feedback interventions are effective in reducing alcohol consumption and related problems. However, little is known about the role of choice in outcomes. The current study sought to (a) characterize individuals who opt in for brief alcohol-related feedback, (b) assess participants' consistency in that choice over two time points, and (c) evaluate changes in peak alcohol consumption among those who did and did not receive feedback. METHOD: Participants reporting past-12-month alcohol consumption were recruited through Prolific. At the outset of the survey, participants were asked if they would like to receive feedback on their drinking at the end of the survey ("opt in"). Participants at Time 1 (T1; N = 732) were 41% female, 91% White, and 8% Hispanic (mean age = 36, SD = 12.25, range: 18-80). A subset was invited back for a 30-day retest (Time 2 [T2]; n = 234). RESULTS: Those reporting higher maximum drinks and more drug use were more likely to opt in to feedback than those with lower use. Further, 85% of participants were consistent in their choice of whether to receive feedback across T1 and T2 (κ = .65). Among heavy drinking participants with T1 and T2 data (n = 163), there was an effect of feedback on intensity of consumption at T2. CONCLUSIONS: Individuals who engage in heavy alcohol use are more likely to opt in to personalized alcohol feedback, and most do so consistently. Among heavy drinkers, feedback at T1 reduced intensity of consumption at T2, but the effect was small and requires future replication in more diverse samples.

Modeling clear cell renal cell carcinoma and therapeutic implications.

Renal cell carcinoma (RCC) comprises a diverse group of malignancies arising from the nephron. The most prevalent type, clear cell renal cell carcinoma (ccRCC), is characterized by genetic mutations in factors governing the hypoxia signaling pathway, resulting in metabolic dysregulation, heightened angiogenesis, intratumoral heterogeneity, and deleterious tumor microenvironmental (TME) crosstalk. Identification of specific genetic variances has led to therapeutic innovation and improved survival for patients with ccRCC. Current barriers to effective long-term therapeutic success highlight the need for continued drug development using improved modeling systems. ccRCC preclinical models can be grouped into three broad categories: cell line, mouse, and 3D models. Yet, the breadth of important unanswered questions in ccRCC research far exceeds the accessibility of model systems capable of carrying them out. Accordingly, we review the strengths, weaknesses, and therapeutic implications of each model system that are relied upon today.

Fine-Needle Aspiration-Based Patient-Derived Cancer Organoids.

Patient-derived cancer organoids hold great potential to accurately model and predict therapeutic responses. Efficient organoid isolation methods that minimize post-collection manipulation of tissues would improve adaptability, accuracy, and applicability to both experimental and real-time clinical settings. Here we present a simple and minimally invasive fine-needle aspiration (FNA)-based organoid culture technique using a variety of tumor types including gastrointestinal, thyroid, melanoma, and kidney. This method isolates organoids directly from patients at the bedside or from resected tissues, requiring minimal tissue processing while preserving the histologic growth patterns and infiltrating immune cells. Finally, we illustrate diverse downstream applications of this technique including in vitro high-throughput chemotherapeutic screens, in situ immune cell characterization, and in vivo patient-derived xenografts. Thus, routine clinical FNA-based collection techniques represent an unappreciated substantial source of material that can be exploited to generate tumor organoids from a variety of tumor types for both discovery and clinical applications.