Fibrinogen-to-albumin ratio (FAR) is the best biomarker for the overall survival of patients with non-small-cell lung cancer.

Objective: The inflammatory response and the nutritional status are associated with overall survival (OS) in patients with non-small cell lung cancer (NSCLC), but it is unclear which biomarkers are better suited to predict prognosis. This study sought to determine which of the commonly existing inflammatory and nutritional indicators best predicted the OS. Methods: This study included 15 compound indicators based on inflammation or nutrition, with cutoff points obtained through the receiver operating characteristic (ROC) curve. Univariate and multivariate Cox proportional risk models were used to evaluate the relationship between these predictors and OS. Kaplan-Meier curves were used for survival analysis, and log-rank tests were used to compare differences between groups. The C-index was calculated to evaluate the predictive ability of the different indicators. Results: The study included 899 patients with NSCLC. In the univariate analysis, all 15 measures were significantly associated with the OS of patients (all p < 0.05). The results of the C-index analysis showed that the fibrinogen-to-albumin ratio (FAR), the systemic immune-inflammation index (SII), and the albumin-to-alkaline phosphatase ratio (AAPR) were the three indices with the best predictive performance. Among them, FAR (C-index = 0.639) had the best predictive power for OS in patients with NSCLC. In the different subgroups, FAR had the highest C-index in male, non-smoking, adenocarcinoma, and stage II patients. The C-index of the platelet-to-lymphocyte ratio (PLR) in female patients was the highest. SII was the highest in smokers, in those aged <65 and ≥65 years, and in stage III patients. The C-index of AAPR was the highest in non-adenocarcinomas. The C-index of the pan-immune-inflammation value (PIV) was the highest in stage I patients. In the multivariate Cox regression analysis, among FAR, SII, and AAPR, only FAR was an independent predictor of OS in patients with NSCLC. A high FAR was associated with a higher risk of death in patients with NSCLC (HR = 1.601, 95% CI = 1.028-2.495). In order to further evaluate the potential prognostic value of FAR, SII, and AAPR in patients with different stages, Cox regression analysis was performed for those with stage I-II and stage III NSCLC. The results showed that FAR was an independent prognostic factor for OS in patients with stage I-II NSCLC. Conclusion: For all patients with NSCLC, the prognostic power of FAR was superior to that of other inflammatory and nutritional indicators.

The Construction of a Nomogram Using the Pan-Immune-Inflammation Value Combined with a PILE Score for Immunotherapy Prediction Prognosis in Advanced NSCLC.

Purpose: The purpose of this study was to investigate the predictive value of Pan-Immune-Inflammation Value (PIV) combined with the PILE score for immunotherapy in patients with advanced non-small cell lung cancer (NSCLC) and to construct a nomogram prediction model to provide reference for clinical work. Patients and Methods: Patients with advanced NSCLC who received ICIs treatment in Qingdao Municipal Hospital from January 2019 to December 2021 were selected as the study subjects. The chi-square test, Kaplan-Meier survival analysis, and Cox proportional risk regression analysis were used to evaluate the prognosis. The results were visualized by a nomogram, and the performance of the model was judged by indicators such as the area under the subject operating characteristic curve (AUC) and C-index. The patients were divided into high- and low-risk groups by PILE score, and the prognosis of patients in different risk groups was evaluated. Results: Multivariate Cox regression analysis showed that immune-related adverse events (irAEs) were prognostic factors for overall survival (OS) improvement, and ECOG PS score ≥2, bone metastases before treatment, and high PIV expression were independent risk factors for OS. The C index of OS predicted by the nomogram model is 0.750 (95% CI: 0.677-0.823), and the Calibration and ROC curves show that the model has good prediction performance. Compared with the low-risk group, patients in the high-risk group of PILE were associated with a higher inflammatory state and poorer physical condition, which often resulted in a poorer prognosis. Conclusion: PIV can be used as a prognostic indicator for patients with advanced NSCLC treated with ICIs, and a nomogram prediction model can be constructed to evaluate the survival prediction of patients, thus contributing to better clinical decision-making and prognosis assessment.

Risk factor analysis and nomogram prediction model construction of postoperative complications of thoracoscopic non-small cell lung cancer.

Background: A series of complications will inevitably occur after thoracoscopic pulmonary resection. How to avoid or reduce postoperative complications is an important research area in the perioperative treatment of thoracic surgery. This study analyzed the risk factors for thoracoscopic postoperative complications of non-small cell lung cancer (NSCLC) and established a nomogram prediction model in order to provide help for clinical decision-making. Methods: Patients with NSCLC who underwent thoracoscopic surgery from January 2017 to December 2021 were selected as study subjects. The relationship between patient characteristics, surgical factors, and postoperative complications was collected and analyzed. Based on the results of the statistical regression analysis, a nomogram model was constructed, and the predictive performance of the nomogram model was evaluated. Results: A total of 872 patients who met the study criteria were included in the study. A total of 171 patients had complications after thoracoscopic surgery, accounting for 19.6% of the study population. Logistic regression analysis showed that thoracic adhesion, history of respiratory disease, and lymphocyte-monocyte ratio (LMR) were independent risk factors for complications after thoracoscopic surgery (P<0.05). Variables with P<0.1 in logistic regression analysis were included in the nomogram model. The verification results showed that the area under curve (AUC) of the model was 0.734 [95% confidence interval (CI): 0.693-0.775], and the calibration curve showed that the model had good differentiation. The decision curve analysis (DCA) curve showed that this model has good clinical application value. In subgroup analysis of complications, gender, history of respiratory disease, body mass index (BMI), type of surgical procedure, thoracic adhesion, and Time of operation were identified as significant risk factors for prolonged air leak (PAL) after surgery. Tumor location and forced expiratory volume in the first second (FEV1) were identified as important risk factors for postoperative pulmonary infection. N stage and thoracic adhesion were identified as significant risk factors for postoperative pleural effusion. The AUC for PAL was 0.823 (95% CI: 0.768-0.879). The AUC of postoperative pulmonary infection was 0.714 (95% CI: 0.627-0.801). The AUC of postoperative pleural effusion was 0.757 (95% CI: 0.650-0.864). The calibration curve and DCA curve indicated that the model had good predictive performance and clinical application value. Conclusions: This study analyzed the risk factors affecting the postoperative complications of NSCLC through thoracoscopic surgery, and the nomogram model built based on the influencing factors has certain significance for the identification and reduction of postoperative complications.

CRISPR screens reveal convergent targeting strategies against evolutionarily distinct chemoresistance in cancer.

Resistance to chemotherapy has been a major hurdle that limits therapeutic benefits for many types of cancer. Here we systematically identify genetic drivers underlying chemoresistance by performing 30 genome-scale CRISPR knockout screens for seven chemotherapeutic agents in multiple cancer cells. Chemoresistance genes vary between conditions primarily due to distinct genetic background and mechanism of action of drugs, manifesting heterogeneous and multiplexed routes towards chemoresistance. By focusing on oxaliplatin and irinotecan resistance in colorectal cancer, we unravel that evolutionarily distinct chemoresistance can share consensus vulnerabilities identified by 26 second-round CRISPR screens with druggable gene library. We further pinpoint PLK4 as a therapeutic target to overcome oxaliplatin resistance in various models via genetic ablation or pharmacological inhibition, highlighting a single-agent strategy to antagonize evolutionarily distinct chemoresistance. Our study not only provides resources and insights into the molecular basis of chemoresistance, but also proposes potential biomarkers and therapeutic strategies against such resistance.

Prognostic factors and predictive model construction in patients with non-small cell lung cancer: a retrospective study.

Objective: The purpose of this study was to construct a nomogram model based on the general characteristics, histological features, pathological and immunohistochemical results, and inflammatory and nutritional indicators of patients so as to effectively predict the overall survival (OS) and progression-free survival (PFS) of patients with non-small cell lung cancer (NSCLC) after surgery. Methods: Patients with NSCLC who received surgical treatment in our hospital from January 2017 to June 2021 were selected as the study subjects. The predictors of OS and PFS were evaluated by univariate and multivariable Cox regression analysis using the Cox proportional risk model. Based on the results of multi-factor Cox proportional risk regression analysis, a nomogram model was established using the R survival package. The bootstrap method (repeated sampling for 1 000 times) was used to internally verify the nomogram model, and C-index was used to represent the prediction performance of the nomogram model. The calibration graph method was used to visually represent its prediction compliance, and decision curve analysis (DCA) was used to evaluate the application value of the model. Results: Univariate and multivariate analyses were used to identify independent prognostic factors and to construct a nomogram of postoperative survival and disease progression in operable NSCLC patients, with C-index values of 0.927 (907-0.947) and 0.944 (0.922-0.966), respectively. The results showed that the model had high predictive performance. Calibration curves for 1-year, 2-year, and 3-year OS and PFS show a high degree of agreement between the predicted probability and the actual observed probability. In addition, the results of the DCA curve show that the model has good clinical application value. Conclusion: We established a predictive model of survival prognosis and disease progression in patients with non-small cell lung cancer after surgery, which has good predictive performance and can guide clinicians to make the best clinical decision.

The advanced lung cancer inflammation index (ALI) predicted the postoperative survival rate of patients with non-small cell lung cancer and the construction of a nomogram model.

OBJECTIVE: To investigate the prognostic significance of the advanced lung cancer inflammation index (ALI) in patients with operable non-small-cell lung carcinoma (NSCLC). By constructing the nomogram model, it can provide a reference for clinical work. METHODS: A total of 899 patients with non-small cell lung cancer who underwent surgery in our hospital between January 2017 and June 2021 were retrospectively included. ALI was calculated by body mass index (BMI) × serum albumin/neutrophil to lymphocyte ratio (NLR). The optimal truncation value of ALI was obtained using the receiver operating characteristic (ROC) curve and divided into two groups. Survival analysis was represented by the Kaplan-Meier curve. The predictors of Overall survival (OS) were evaluated by the Cox proportional risk model using single factor and stepwise regression multifactor analysis. Based on the results of multi-factor Cox proportional risk regression analysis, a nomogram model was established using the R survival package. The bootstrap method (repeated sampling 1 000 times) was used for internal verification of the nomogram model. The concordance index (C-index) was used to represent the prediction performance of the nomogram model, and the calibration graph method was used to visually represent its prediction conformity. The application value of the model was evaluated by decision curve analysis (DCA). RESULTS: The optimal cut-off value of ALI was 70.06, and the low ALI group (ALI < 70.06) showed a poor survival prognosis. In multivariate analyses, tumor location, pathological stage, neuroaggression, and ALI were independently associated with operable NSCLC-specific survival. The C index of OS predicted by the nomogram model was 0.928 (95% CI: 0.904-0.952). The bootstrap self-sampling method (B = 1000) was used for internal validation of the prediction model, and the calibration curve showed good agreement between the prediction and observation results of 1-year, 2-year, and 3-year OS. The ROC curves for 1-year, 2-year, and 3-year survival were plotted according to independent factors, and the AUC was 0.952 (95% CI: 0.925-0.979), 0.951 (95% CI: 0.916-0.985), and 0.939 (95% CI: 0.913-0.965), respectively. DCA shows that this model has good clinical application value. CONCLUSION: ALI can be used as a reliable indicator to evaluate the prognosis of patients with operable NSCLC, and through the construction of a nomogram model, it can facilitate better individualized treatment and prognosis assessment.

Association between immune-related adverse events and prognosis in patients with advanced non-small cell lung cancer: a systematic review and meta-analysis.

Background: The emergence of immune checkpoint inhibitors (ICIs) provides a variety of options for patients with advanced non-small-cell lung cancer (NSCLC). After the application of ICIs, the immune system of patients was highly activated, and immune-related adverse events (irAEs) could occur in some organ systems, and irAEs seemed to be associated with the survival prognosis of patients. Therefore, we evaluated the association between survival outcomes and irAEs in NSCLC patients and conducted a systematic review and meta-analysis. Methods: We conducted systematic reviews of PubMed, Embase, Cochrane, and Web of Science databases until December 2021. The forest map was constructed by combining the hazard ratio (HR) and 95% confidence interval (CI). I2 estimated the heterogeneity between studies. A meta-analysis was performed using R 4.2.1 software. Results: Eighteen studies included 4808 patients with advanced NSCLC. In pooled analysis, the occurrence of irAEs was found to be a favorable factor for improved prognosis (PFS: HR: 0.48, 95% CI: 0.41-0.55, P <0.01; OS: HR: 0.46, 95% CI: 0.42-0.52, P <0.01). In subgroup analyses, cutaneous irAE, gastrointestinal irAE, endocrine irAE and grade ≥3 irAEs were associated with improvements in PFS and OS, but pulmonary and hepatic irAEs were not. Conclusion: Existing evidence suggests that the occurrence of irAEs may be a prognostic biomarker for advanced NSCLC. However, further research is needed to explore the prospect of irAEs as a prognostic biomarker in patients undergoing immunotherapy. Systematic review registration: https://www.crd.york.ac.uk/PROSPEROFILES/405333_STRATEGY_20240502.pdf, identifier CRD42023405333.

Rapid weather changes are associated with daily hospital visitors for atrial fibrillation accompanied by abnormal ECG repolarization: a case-crossover study.

BACKGROUND: Atrial fibrillation (AF) is highly prevalent in the population, yet the factors contributing to AF events in susceptible individuals remain partially understood. The potential relationship between meteorological factors and AF, particularly with abnormal electrocardiograph (ECG) repolarization, has not been adequately studied. This case-crossover study aims to investigate the association between meteorological factors and daily hospital visits for AF with abnormal ECG repolarization in Shanghai, China. METHODS: The study cohort comprised 10,325 patients with ECG-confirmed AF who sought treatment at Shanghai Sixth People's Hospital between 2015 and 2018. Meteorological and air pollutant concentration data were matched with the patient records. Using a case-crossover design, we analyzed the association between meteorological factors and the daily count of hospital visitors for AF with abnormal ECG repolarization at our AF center. Lag analysis models were applied to examine the temporal relationship between meteorological factors and AF events. RESULTS: The analysis revealed statistically significant associations between AF occurrence and specific meteorological factors. AF events were significantly associated with average atmospheric pressure (lag 0 day, OR 0.9901, 95% CI 0.9825-0.9977, P < 0.05), average temperature (lag 1 day, OR 0.9890, 95% CI 0.9789-0.9992, P < 0.05), daily pressure range (lag 7 days, OR 1.0195, 95% CI 1.0079-1.0312, P < 0.01), and daily temperature range (lag 5 days, OR 1.0208, 95% CI 1.0087-1.0331, P < 0.01). Moreover, a significant correlation was observed between daily pressure range and daily temperature range with AF patients, particularly those with abnormal ECG repolarization, as evident in the case-crossover analysis. CONCLUSION: This study highlights a significant correlation between meteorological factors and daily hospital visits for AF accompanied by abnormal ECG repolarization in Shanghai, China. In addition, AF patients with abnormal ECG repolarization were found to be more vulnerable to rapid daily changes in pressure and temperature compared to AF patients without such repolarization abnormalities.

Intrinsic targeting of host RNA by Cas13 constrains its utility.

Cas13 can be used for the knockdown, editing, imaging or detection of RNA and for RNA-based gene therapy. Here by using RNA immunoprecipitation sequencing, transcriptome profiling, biochemical analysis, high-throughput screening and machine learning, we show that Cas13 can intrinsically target host RNA in mammalian cells through previously unappreciated mechanisms. Different from its known cis/trans RNA-cleavage activity, Cas13 can also cleave host RNA via mechanisms that are transcript-specific, independent of the sequence of CRISPR RNA and dynamically dependent on the conformational state of Cas13, as we show for several Cas13-family effectors encoded in one-vector and two-vector lentiviral systems. Moreover, host genes involved in viral processes and whose transcripts are intrinsically targeted by Cas13 contribute to constraining the lentiviral delivery and expression of Cas13. Our findings offer guidance for the appropriate use of lentiviral Cas13 systems and highlight the need for caution regarding intrinsic RNA targeting in Cas13-based applications.

CTLA-4 blockade induces a microglia-Th1 cell partnership that stimulates microglia phagocytosis and anti-tumor function in glioblastoma.

The limited efficacy of immunotherapies against glioblastoma underscores the urgency of better understanding immunity in the central nervous system. We found that treatment with αCTLA-4, but not αPD-1, prolonged survival in a mouse model of mesenchymal-like glioblastoma. This effect was lost upon the depletion of CD4+ T cells but not CD8+ T cells. αCTLA-4 treatment increased frequencies of intratumoral IFNγ-producing CD4+ T cells, and IFNγ blockade negated the therapeutic impact of αCTLA-4. The anti-tumor activity of CD4+ T cells did not require tumor-intrinsic MHC-II expression but rather required conventional dendritic cells as well as MHC-II expression on microglia. CD4+ T cells interacted directly with microglia, promoting IFNγ-dependent microglia activation and phagocytosis via the AXL/MER tyrosine kinase receptors, which were necessary for tumor suppression. Thus, αCTLA-4 blockade in mesenchymal-like glioblastoma promotes a CD4+ T cell-microglia circuit wherein IFNγ triggers microglia activation and phagocytosis and microglia in turn act as antigen-presenting cells fueling the CD4+ T cell response.

Metformin suppresses cardiac fibroblast proliferation under high-glucose conditions via regulating the mitochondrial complex I protein Grim-19 involved in the Sirt1/Stat3 signaling pathway.

Hyperglycemia associated with myocardial oxidative stress and fibrosis is the main cause of diabetic cardiomyopathy. Currently, no approved drug is available for preventing or treating diabetes-induced cardiac fibrosis. Metformin has been reported to improve glycemic control and ameliorate diabetic cardiomyopathy. This study aimed to investigate the effects and mechanism of metformin on diabetes-induced cardiac fibrosis and high glucose-induced proliferation of cardiac fibroblasts (CFs). In this study, db/db mice were treated with metformin [250 mg/kg⋅d, gavage]. CFs were cultured in high-glucose medium to mimic an in vitro diabetes model and then subjected to treatment with or without metformin. Cardiac fibrosis was analyzed using immunohistochemistry, Masson's trichrome staining, and Western blot analysis. Cell Counting Kit-8 (CCK-8) assays and cell colony formation assays were used to examine cell proliferation capacity. Transwell and scratch-wound assays were used to detect the migration ability of CFs. Retinoid-interferon-induced mortality-19 (Grim-19), sirtuin1 (Sirt1), and signal transducer and activator of transcription 3 (Stat3) were detected using Western blot analysis. The genes downstream of the Stat3 pathway were detected using quantitative reverse transcription PCR (qRT‒PCR). Metformin treatment markedly attenuated cardiac fibrosis in db/db mice and the proliferation and migration of CFs under high-glucose conditions. Mechanistically, we found an intersection between metformin and Grim-19 using bioinformatics. Metformin was found to suppress the expression of p-Stat3 and elevate the expression of mitochondrial complex I protein Grim-19 and Sirt1, thus inhibiting the proliferation and migration of CFs under high-glucose conditions. Our data suggested that metformin inhibited the proliferation and migration of CFs by regulating the expression of mitochondrial complex I Grim-19 protein involved in the Sirt1/Stat3 signaling pathway under high-glucose conditions, thus providing new ideas for treating diabetes-induced cardiac fibrosis.

Canonical BAF complex activity shapes the enhancer landscape that licenses CD8+ T cell effector and memory fates.

CD8+ T cells provide host protection against pathogens by differentiating into distinct effector and memory cell subsets, but how chromatin is site-specifically remodeled during their differentiation is unclear. Due to its critical role in regulating chromatin and enhancer accessibility through its nucleosome remodeling activities, we investigated the role of the canonical BAF (cBAF) chromatin remodeling complex in antiviral CD8+ T cells during infection. ARID1A, a subunit of cBAF, was recruited early after activation and established de novo open chromatin regions (OCRs) at enhancers. Arid1a deficiency impaired the opening of thousands of activation-induced enhancers, leading to loss of TF binding, dysregulated proliferation and gene expression, and failure to undergo terminal effector differentiation. Although Arid1a was dispensable for circulating memory cell formation, tissue-resident memory (Trm) formation was strongly impaired. Thus, cBAF governs the enhancer landscape of activated CD8+ T cells that orchestrates TF recruitment and activity and the acquisition of specific effector and memory differentiation states.

Multiomics atlas-assisted discovery of transcription factors enables specific cell state programming.

The same types of cells can assume diverse states with varying functionalities. Effective cell therapy can be achieved by specifically driving a desirable cell state, which requires the elucidation of key transcription factors (TFs). Here, we integrated epigenomic and transcriptomic data at the systems level to identify TFs that define different CD8 + T cell states in an unbiased manner. These TF profiles can be used for cell state programming that aims to maximize the therapeutic potential of T cells. For example, T cells can be programmed to avoid a terminal exhaustion state (Tex Term ), a dysfunctional T cell state that is often found in tumors or chronic infections. However, Tex Term exhibits high similarity with the beneficial tissue-resident memory T states (T RM ) in terms of their locations and transcription profiles. Our bioinformatic analysis predicted Zscan20 , a novel TF, to be uniquely active in Tex Term . Consistently, Zscan20 knock-out thwarted the differentiation of Tex Term in vivo , but not that of T RM . Furthermore, perturbation of Zscan20 programs T cells into an effector-like state that confers superior tumor and virus control and synergizes with immune checkpoint therapy. We also identified Jdp2 and Nfil3 as powerful Tex Term drivers. In short, our multiomics-based approach discovered novel TFs that enhance anti-tumor immunity, and enable highly effective cell state programming. One sentence summary: Multiomics atlas enables the systematic identification of cell-state specifying transcription factors for therapeutic cell state programming.

Tests and analyses on physical and mechanical properties of fresh black fungus in picking season.

This study determined the physical and mechanical characteristics of fresh black fungus during the harvesting season to provide basic data for the development of mechanical equipment for black fungus harvesting and processing. We have conducted a comprehensive test of black fungus cultivars "Heishan". The mono-factor separation force experiments of black fungus and black fungus virgulate medium were conducted. It was noted that the tension angle was an important factor affecting the separation force, which was mainly distributed between 1.06 and 3.65 N. Besides, the average value of Poisson's ratio of black fungus was measured to be 0.445 in the tensile test of black fungus leaves using image recognition and analysis techniques, with a test error within 2.5%; and the average value of tensile elastic modulus and shear elastic modulus of black fungus leaves was 0.947 MPa and 0.327 MPa, respectively; we also found that the average tensile strength at the root of black fungus was not significantly different from that at the leaf, which was around 0.436 MPa. In addition, it was obtained that the height and thickness dimensions of black fungus in the picking season conformed to a normal distribution, and concentrated around 34.39mm and 0.92mm respectively.

HMCES modulates the transcriptional regulation of nodal/activin and BMP signaling in mESCs.

Despite the fundamental roles of TGF-ß family signaling in cell fate determination in all metazoans, the mechanism by which these signals are spatially and temporally interpreted remains elusive. The cell-context-dependent function of TGF-ß signaling largely relies on transcriptional regulation by SMAD proteins. Here, we discover that the DNA repair-related protein, HMCES, contributes to early development by maintaining nodal/activin- or BMP-signaling-regulated transcriptional network. HMCES binds with R-SMAD proteins, co-localizing at active histone marks. However, HMCES chromatin occupancy is independent on nodal/activin or BMP signaling. Mechanistically, HMCES competitively binds chromatin to limit binding by R-SMAD proteins, thereby forcing their dissociation and resulting in repression of their regulatory effects. In Xenopus laevis embryo, hmces KD causes dramatic development defects with abnormal left-right axis asymmetry along with increasing expression of lefty1. These findings reveal HMCES transcriptional regulatory function in the context of TGF-ß family signaling.

A chemical-enhanced system for CRISPR-Based nucleic acid detection.

The CRISPR-based nucleic acid detection systems have shown great potential for point-of-care testing of viral pathogens, especially in the context of COVID-19 pandemic. Here we optimize several key parameters of reaction chemistry and develop a Chemical Enhanced CRISPR Detection system for nucleic acid (termed CECRID). For the Cas12a/Cas13a-based signal detection phase, we determine buffer conditions and substrate range for optimal detection performance, and reveal a crucial role of bovine serum albumin in enhancing trans-cleavage activity of Cas12a/Cas13a effectors. By comparing several chemical additives, we find that addition of L-proline can secure or enhance Cas12a/Cas13a detection capability. For isothermal amplification phase with typical LAMP and RPA methods, inclusion of L-proline can also enhance specific target amplification as determined by CRISPR detection. Using SARS-CoV-2 pseudovirus, we demonstrate CECRID has enhanced detection sensitivity over chemical additive-null method with either fluorescence or lateral flow strip readout. Thus, CECRID provides an improved detection power and system robustness, and helps to develop enhanced reagent formula or test kit towards practical application of CRISPR-based diagnostics.

How metabolism bridles cytotoxic CD8+ T cells through epigenetic modifications.

In the direct competition for metabolic resources between cancer cells and tumor-infiltrating CD8+ T cells, the latter are bound to lose out. These effector lymphocytes are therefore rendered exhausted or dysfunctional. Emerging insights into the mechanisms of T cell unresponsiveness in the tumor microenvironment (TME) point towards epigenetic mechanisms as crucial regulatory factors. In this review, we discuss the effects of characteristic components of the TME, i.e. glucose/amino acid dearth with elevated levels of reactive oxygen species (ROS), on DNA methylation and histone modifications in CD8+ T cells. We then take a closer look at the translational potential of epigenetic interventions that aim to improve current immunotherapeutic strategies, including the adoptive transfer of T cell receptor (TCR) or chimeric antigen receptor (CAR) engineered T cells.

A computational framework of host-based drug repositioning for broad-spectrum antivirals against RNA viruses.

RNA viruses are responsible for many zoonotic diseases that post great challenges for public health. Effective therapeutics against these viral infections remain limited. Here, we deployed a computational framework for host-based drug repositioning to predict potential antiviral drugs from 2,352 approved drugs and 1,062 natural compounds embedded in herbs of traditional Chinese medicine. By systematically interrogating public genetic screening data, we comprehensively cataloged host dependency genes (HDGs) that are indispensable for successful viral infection corresponding to 10 families and 29 species of RNA viruses. We then utilized these HDGs as potential drug targets and interrogated extensive drug-target interactions through database retrieval, literature mining, and de novo prediction using artificial intelligence-based algorithms. Repurposed drugs or natural compounds were proposed against many viral pathogens such as coronaviruses including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), flaviviruses, and influenza viruses. This study helps to prioritize promising drug candidates for in-depth evaluation against these virus-related diseases.

Transfer of cGAMP into Bystander Cells via LRRC8 Volume-Regulated Anion Channels Augments STING-Mediated Interferon Responses and Anti-viral Immunity.

The enzyme cyclic GMP-AMP synthase (cGAS) senses cytosolic DNA in infected and malignant cells and catalyzes the formation of 2'3'cGMP-AMP (cGAMP), which in turn triggers interferon (IFN) production via the STING pathway. Here, we examined the contribution of anion channels to cGAMP transfer and anti-viral defense. A candidate screen revealed that inhibition of volume-regulated anion channels (VRACs) increased propagation of the DNA virus HSV-1 but not the RNA virus VSV. Chemical blockade or genetic ablation of LRRC8A/SWELL1, a VRAC subunit, resulted in defective IFN responses to HSV-1. Biochemical and electrophysiological analyses revealed that LRRC8A/LRRC8E-containing VRACs transport cGAMP and cyclic dinucleotides across the plasma membrane. Enhancing VRAC activity by hypotonic cell swelling, cisplatin, GTPγS, or the cytokines TNF or interleukin-1 increased STING-dependent IFN response to extracellular but not intracellular cGAMP. Lrrc8e-/- mice exhibited impaired IFN responses and compromised immunity to HSV-1. Our findings suggest that cell-to-cell transmission of cGAMP via LRRC8/VRAC channels is central to effective anti-viral immunity.

T Cell Metabolism in a State of Flux.

Our knowledge of T cell metabolism relies primarily on studies performed in vitro that may not fully recapitulate physiological conditions in vivo. In this issue of Immunity, Ma et al. find that the in vivo environment dictates the metabolic phenotype of effector CD8+ T cells-particularly their glucose utilization.