Regulatory T (T _reg ) cells and cancer-associated fibroblasts (CAFs) jointly promote tumor immune tolerance and tumorigenesis. The molecular apparatus that drives T _reg cell and CAF coordination in the tumor microenvironment (TME) remains elusive. Interleukin 33 (IL-33) has been shown to enhance fibrosis and IL1RL1 ⁺ T _reg cell accumulation during tumorigenesis and tissue repair. We demonstrated that IL1RL1 signaling in T _reg cells greatly dampened the antitumor activity of both IL-33 and PD-1 blockade. Whole tumor single-cell RNA sequencing (scRNA-seq) analysis and blockade experiments revealed that the amphiregulin (AREG)–epidermal growth factor receptor (EGFR) axis mediated cross-talk between IL1RL1 ⁺ T _reg cells and CAFs. We further demonstrated that the AREG/EGFR axis enables T _reg cells to promote a profibrotic and immunosuppressive functional state of CAFs. Moreover, AREG mAbs and IL-33 concertedly inhibited tumor growth. Our study reveals a previously unidentified AREG/EGFR-mediated T _reg /CAF coupling that controls the bifurcation of fibroblast functional states and is a critical barrier for cancer immunotherapy.

T cell–stimulating cytokines and immune checkpoint inhibitors (ICI) are an ideal combination for increasing response rates of cancer immunotherapy. However, the results of clinical trials have not been satisfying. It is important to understand the mechanism of synergy between these two therapeutic modalities. Here, through integrated analysis of multiple single-cell RNA sequencing (scRNA-seq) datasets of human tumor-infiltrating immune cells, we demonstrate that IL21 is produced by tumor-associated T follicular helper cells and hyperactivated/exhausted CXCL13+CD4+ T cells in the human tumor microenvironment (TME). In the mouse model, the hyperactivated/exhausted CD4+ T cell–derived IL21 enhances the helper function of CD4+ T cells that boost CD8+ T cell–mediated immune responses during PD-1 blockade immunotherapy. In addition, we demonstrated that IL21’s antitumor activity did not require T-cell trafficking. Using scRNA-seq analysis of the whole tumor-infiltrating immune cells, we demonstrated that IL21 treatment in combination with anti-PD-1 blockade synergistically drives tumor antigen–specific CD8+ T cells to undergo clonal expansion and differentiate toward the hyperactive/exhausted functional state in the TME. In addition, IL21 treatment and anti-PD-1 blockade synergistically promote dendritic cell (DC) activation and maturation to mature DC as well as monocyte to type 1 macrophage (M1) differentiation in the TME. Furthermore, the combined treatment reprograms the immune cellular network by reshaping cell-cell communication in the TME. Our study establishes unique mechanisms of synergy between IL21 and PD-1–based ICI in the TME through the coordinated promotion of type 1 immune responses. Significance: This study reveals how cytokine and checkpoint inhibitor therapy can be combined to increase the efficacy of cancer immunotherapy.

Ischemic stroke is a leading cause of disability and mortality worldwide. Recently, increasing evidence implicates microRNAs (miRs) in the pathophysiology of ischemic stroke. Studies have shown that miR-15a/16-1 is abnormally expressed in brains after ischemic stroke, and its upregulation may increase ischemic damage. Given that sex and age are significant modifiers of stroke outcomes, here we investigated whether inhibiting miR-15a/16-1 with antagomirs mitigates cerebral ischemia/reperfusion (I/R) injury in a sex- and age-dependent manner. Young (3 months) and aged (18 months) male and female C57/BL mice underwent 1-h middle cerebral artery occlusion and 3–7 days reperfusion (tMCAO). We administered miR-15a/16-1 antagomir (30 pmol/g) or control antagomir (NC, 30 pmol/g) via tail vein 2 h post-MCAO. Neurobehavioral testing and infarct volume assessment were performed on days 3 and 7. Compared to controls, antagomir treatment significantly improved neurobehavioral outcomes and reduced infarct volume in tMCAO mice at day 7, with the effects being more pronounced in young mice. Notably, young female mice exhibited superior survival and sensorimotor function compared to young male mice. These results were also replicated in a permanent MCAO (pMCAO) mice model. This suggests miR-15a/16-1 antagomir and estradiol may synergistically regulate genes involved in neurovascular cell death, inflammation, and oxidative stress, with sex and age-dependent expression of miR-15a/16-1 and its targets likely underlying the observed variations. Overall, our findings identify miR-15a/16-1 antagomir as a promising therapeutic for ischemic stroke and suggest that sex and age should be considered when developing miR-based therapeutic strategies.

Background: Early assessment and management of cerebral edema and hematoma following aneurysmal subarachnoid hemorrhage (a-SAH) can significantly impact clinical cognitive outcomes. However, current clinical practices lack predictive models to identify early structural brain abnormalities affecting cognition. To address this gap, the authors propose the development of a predictive model termed the a-SAH Early Brain Edema/Hematoma Compression Neural (Structural Brain) Networks Score System (SEBE-HCNNSS). Methods: In this study, 202 consecutive patients with spontaneous a-SAH underwent initial computed tomography (CT) or MRI scans within 24 h of ictus with follow-up 2 months after discharge. Using logistic regression analysis (univariate and multivariate), the authors evaluated the association of clinically relevant factors and various traditional scale ratings with cognitive impairment (CI). Risk factors with the highest area under the curve (AUC) values were included in the multivariate analysis and least absolute shrinkage and selection operator (LASSO) analysis or Cox regression analysis. Results: A total of 177 patients were enrolled in the study, and 43 patients were classified with a high SEBE-HCNNSS grade (3–5). After a mean follow-up of 2 months, 121 individuals (68.36%) with a-SAH and three control subjects developed incident CI. The CT interobserver reliability of the SEBE-HCNNSS scale was high, with a Kappa value of 1. Furthermore, ROC analysis identified the SEBE-HCNNSS scale (OR 3.322, 95% CI: 2.312–7.237, P=0.00025) as an independent predictor of edema, CI, and unfavorable prognosis. These results were also replicated in a validation cohort. Conclusion: Overall, the SEBE-HCNNSS scale represents a simple assessment tool with promising predictive value for CI and clinical outcomes post-a-SAH. Our findings indicate its practical utility as a prognostic instrument for risk evaluation after a-SAH, potentially facilitating early intervention and treatment.

Detecting Alzheimer’s Disease (AD) at the earliest possible stage is key in advancing AD prevention and treatment but is challenged by normal aging processes in addition to other confounding neurodegenerative diseases. Recent genome-wide association studies (GWAS) have identified associated alleles, but it has been difficult to transition from non-coding genetic variants to underlying mechanisms of AD. Here, we sought to reveal functional genetic variants and diagnostic biomarkers underlying AD using machine learning techniques. We first developed a Random Forest (RF) classifier using microarray gene expression data sampled from the peripheral blood of 744 participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. After initial feature selection, 5-fold cross-validation of the 100-gene RF classifier achieved an accuracy of 99.04%. The high accuracy of the RF classifier supports the possibility of a powerful and minimally invasive tool for screening of AD. Next, unsupervised clustering was used to validate and identify relationships among differentially expressed genes (DEGs) the RF selected revealing 3 distinct AD clusters. Results suggest downregulation of global sulfatase and oxidoreductase activities in AD through mutations in SUMF1 and SMOX respectively. Then, we used Greedy Fast Causal Inference (GFCI) to find potential causes of AD within DEGs. In the causal graph, HLA-DPB1 and CYP4A11 emerge as hub genes, furthering the discussion of the immune system’s role in AD. Finally, we used Gene Set Enrichment Analysis (GSEA) to determine the biological pathways and processes underlying the DEGs that were highly correlated with AD. Cell activation in the immune system, glycosaminoglycan (GAG) binding, vascular dysfunction, oxidative stress, and the neuronal apoptotic process were revealed to be significantly enriched in AD. This study further advances the possibility of low-cost and noninvasive genetic screening for AD while also providing potential gene targets for further experimentation.

Background Early assessment and management of cerebral edema and hematoma following aneurysmal subarachnoid hemorrhage (a-SAH) can significantly impact clinical cognitive outcomes. However, current clinical practices lack predictive models to identify early structural brain abnormalities affecting cognition. To address this gap, we propose the development of a predictive model termed the a-SAH Early Brain Edema/Hematoma Compression Neural (Structural Brain) Networks Score System (SEBE-HCNNSS). Methods In this study, 202 consecutive patients with spontaneous a-SAH underwent initial computed tomography (CT) or magnetic resonance imaging (MRI) scans within 24 hours of ictus with follow-up 2 months after discharge. Using logistic regression analysis (univariate and multivariate), we evaluated clinically relevant factors and various traditional scale ratings for cognitive impairment (CI). Risk factors with the highest area under the curve (AUC) values were included in the multivariate analysis and least absolute shrinkage and selection operator (LASSO) analysis or Cox regression analysis. Results A total of 177 patients were enrolled in the study, and 43 patients were classified with a high SEBE-HCNNSS grade (3 to 5). After a mean follow-up of 2 months, 121 individuals (68.36%) with a-SAH and 3 control subjects developed incident CI. The CT inter-observer reliability of the SEBE-HCNNSS scale was high, with a Kappa value of 1. Furthermore, ROC analysis identified the SEBE-HCNNSS scale (OR 3.322, 95% CI 2.312-7.237, p = 0.00025) as an independent predictor of edema, CI, and unfavorable prognosis. These results were also replicated in a validation cohort. Conclusion Overall, the SEBE-HCNNSS scale represents a simple assessment tool with promising predictive value for CI and clinical outcomes post-a-SAH. Our findings indicate its practical utility as a prognostic instrument for risk evaluation after a-SAH, potentially facilitating early intervention and treatment.