Owing to ongoing recognition of pathogen-associated molecular patterns, immune activation and upregulation of IFN-stimulated genes (ISGs) are sustained in the chronically infected host. Albeit most ISGs are important effectors for containing viral replication, some might exert compensatory immune suppression to limit pathological dysfunctions, although the mechanisms are not fully understood. In this study, we report that the ISG lymphocyte Ag 6 complex, locus E (LY6E) is a negative immune regulator of monocytes. LY6E in monocytes negatively modulated CD14 expression and subsequently dampened the responsiveness to LPS stimulation in vitro. In the setting of chronic HIV infection, the upregulation of LY6E was correlated with reduced CD14 level on monocytes; however, the immunosuppressive effect of LY6E was not adequate to remedy the hyperresponsiveness of activated monocytes. Taken together, the regulatory LY6E pathway in monocytes represents one of negative feedback mechanisms that counterbalance monocyte activation, which might be caused by LPS translocation through the compromised gastrointestinal tract during persistent HIV-1 infection and may serve as a potential target for immune intervention.

Persistent immune activation during chronic human immunodeficiency virus type 1 (HIV-1) infection facilitates immune dysfunction and thereby fuels disease progression. The translocation of bacterial derivatives into blood and the hyperinflammatory responsiveness of monocytes have been considered important causative factors for persistent immune activation. Whether microRNAs (miRNAs) are involved in regulating monocyte-mediated inflammatory responses during chronic HIV-1 infection remains elusive. In this study, we show that miR-126-5p functions as a positive regulator of monocyte-mediated inflammatory responses. Significantly increased miRNA miR-126-5p and decreased cylindromatosis (CYLD) were observed in primary monocytes from chronic HIV-1 patients. Inhibition of miR-126-5p in monocytes from chronic HIV-1 patients attenuated the responsiveness of these cells to lipopolysaccharide (LPS) stimulation. Gain-of-function assays confirmed that miR-126-5p could downregulate CYLD, which in turn caused an upregulation of phosphorylation of JNK protein (pJNK) and enhanced inflammatory responses of monocytes to LPS stimulation. Overall, miR-126-5p upregulates the responsiveness of monocytes to LPS stimulation in chronic HIV-1 infection, and the suppression of miR-126-5p and the promotion of CYLD expression in primary monocytes may represent a practical immune intervention strategy to contain persistent inflammation in chronic HIV-1 infection. IMPORTANCE Monocyte-mediated hyperinflammatory responses during chronic HIV-1 infection are important causative factors driving AIDS progression; however, the underlying mechanism has not been fully addressed. We demonstrated that miR-126-5p, one of the most upregulated miRNAs during chronic HIV-1 infection, could enhance the inflammatory responses of monocytes to LPS by suppressing the inhibitory protein CYLD and thereby unleashing the expression of pJNK in the LPS/Toll-like receptor 4/mitogen-activated protein kinase pathway. This observation reveals a new mechanism for HIV-1 pathogenesis, which could be targeted by immune intervention.

Ovarian cancer (OC) is a type of malignant tumor with a consistently high mortality rate. The diagnosis of early-stage OC and identification of functional subsets in the tumor microenvironment are essential to the development of patient management strategies. However, the development of robust models remains unsatisfactory. We aimed to utilize artificial intelligence and single-cell analysis to address this issue. Two independent datasets were screened from the Gene Expression Omnibus (GEO) database and processed to obtain overlapping differentially expressed genes (DEGs) in stage II–IV vs. stage I diseases. Three explainable machine learning algorithms were integrated to construct models that could determine the tumor stage and extract important characteristic genes as diagnostic biomarkers. Correlations between cancer-associated fibroblast (CAF) infiltration and characteristic gene expression were analyzed using TIMER2.0 and their relationship with survival rates was comprehensively explored via the Kaplan–Meier plotter (KM-plotter) online database. The specific expression of characteristic genes in fibroblast subsets was investigated through single-cell analysis. A novel fibroblast subset signature was explored to predict immune checkpoint inhibitor (ICI) response and oncogene mutation through Tumor Immune Dysfunction and Exclusion (TIDE) and artificial neural network algorithms, respectively. We found that Support Vector Machine–Shapley Additive Explanations (SVM-SHAP), Extreme Gradient Boosting (XGBoost), and Random Forest (RF) successfully diagnosed early-stage OC (stage I). The area under the receiver operating characteristic curves (AUCs) of these models exceeded 0.990. Their overlapping characteristic gene, secreted frizzled-related protein 2 (SFRP2), was a risk factor that affected the overall survival of OC patients with stage II–IV disease (log-rank test: p < 0.01) and was specifically expressed in a fibroblast subset. Finally, the SFRP2⁺ fibroblast signature served as a novel predictor in evaluating ICI response and exploring pan-cancer tumor protein P53 (TP53) mutation (AUC = 0.853, 95% confidence interval [CI]: 0.829–0.877). In conclusion, the models based on SVM-SHAP, XGBoost, and RF enabled the early detection of OC for clinical decision making, and SFRP2⁺ fibroblast signature used in diagnostic models can inform OC treatment selection and offer pan-cancer TP53 mutation detection.

Viral hepatitis, caused by its etiology, hepatitis virus, is a public health problem globally. Among all infections caused by hepatitis-associated viruses, hepatitis B virus (HBV) infection remains the most serious medical concern. HBV infection particularly affects people in East Asia and Africa, the Mediterranean region, and Eastern Europe, with a prevalence rate of > 2%. Currently, approximately 1 billion people worldwide are infected with HBV, and nearly 30% of them experience chronic infection. Chronic HBV infection can lead to chronic hepatitis B (CHB), liver cirrhosis, and hepatocellular carcinoma (HCC), resulting in the related death of approximately 1 million people annually. Although preventative vaccines and antiviral therapies are currently available, there is no cure for this infection. Clinical testing is not only the gateway for diagnosis of HBV infection, but also crucial for judging the timing of medication, evaluating the effect of antiviral therapy, and predicting the risk of relapse after drug withdrawal in the whole follow-up management of hepatitis B infected persons. With advances in detection technology, it is now possible to measure various viral components in the blood to assess the clinical status of HBV infection. Serum viral products of HBV infection, such as HBV DNA, HBV RNA, hepatitis B surface antigen, hepatitis B e-antigen, and hepatitis B core-related antigen, are non-invasive indicators that are critical for the rapid diagnosis and management of related diseases. Improving the sensitivity of monitoring of these products is essential, and the development of corresponding detection technologies is pivotal in achieving this goal. This review aims to offer valuable insights into CHB infection and references for its effective treatment. We provide a comprehensive and systematic overview of classical and novel methods for detecting HBV serum viral products and discusses their clinical applications, along with the latest research progress in this field.

It remains poorly defined whether any human miRNAs play protective roles during HIV infection. Here, focusing on a unique cohort of HIV-infected former blood donors, we identified miR-31 (hsa-miR-31) by comparative miRNA profiling as the only miRNA inversely correlating with disease progression. We further validated this association in two prospective cohort studies. Despite conservation during evolution, hsa-miR-31, unlike its mouse counterpart (mmu-miR-31), was downregulated in human T cell upon activation. Our ex vivo studies showed that inhibiting miR-31 in naïve CD4+ T cells promoted a transcriptional profile with activation signature. Consistent with this skewing effect, miR-31 inhibition led to remarkably increased susceptibility to HIV infection. The suppressive nature of miR-31 in CD4+ T cell activation was pinpointed to its ability to decrease T-bet, the key molecule governing IFN-γ production and activation of CD4+ T cells, by directly targeting the upstream STAT1 transcriptional factor for downregulation, thus blunting Th1 response. Our results implicated miR-31 as a useful biomarker for tracking HIV disease progression and, by demonstrating its importance in tuning the activation of CD4+ T cells, suggested that miR-31 may play critical roles in other physiological contexts where the CD4+ T cell homeostasis needs to be deliberately controlled.

Background: Although immune microenvironment-related chemokines, extracellular matrix (ECM), and intrahepatic immune cells are reported to be highly involved in hepatitis B virus (HBV)-related diseases, their roles in diagnosis, prognosis, and drug sensitivity evaluation remain unclear. Here, we aimed to study their clinical use to provide a basis for precision medicine in hepatocellular carcinoma (HCC) via the amalgamation of artificial intelligence.Methods: High-throughput liver transcriptomes from Gene Expression Omnibus (GEO), NODE (https://www.bio.sino.org/node), the Cancer Genome Atlas (TCGA), and our in-house hepatocellular carcinoma patients were collected in this study. Core immunosignals that participated in the entire diseases course of hepatitis B were explored using the “Gene set variation analysis” R package. Using ROC curve analysis, the impact of core immunosignals and amino acid utilization related gene on hepatocellular carcinoma patient’s clinical outcome were calculated. The utility of core immunosignals as a classifier for hepatocellular carcinoma tumor tissue was evaluated using explainable machine-learning methods. A novel deep residual neural network model based on immunosignals was constructed for the long-term overall survival (LS) analysis. In vivo drug sensitivity was calculated by the “oncoPredict” R package.Results: We identified nine genes comprising chemokines and ECM related to hepatitis B virus-induced inflammation and fibrosis as CLST signals. Moreover, CLST was co-enriched with activated CD4+ T cells bearing harmful factors (aCD4) during all stages of hepatitis B virus pathogenesis, which was also verified by our hepatocellular carcinoma data. Unexpectedly, we found that hepatitis B virus-hepatocellular carcinoma patients in the CLST^highaCD4^high subgroup had the shortest overall survival (OS) and were characterized by a risk gene signature associated with amino acids utilization. Importantly, characteristic genes specific to CLST/aCD4 showed promising clinical relevance in identifying patients with early-stage hepatocellular carcinoma via explainable machine learning. In addition, the 5-year long-term overall survival of hepatocellular carcinoma patients can be effectively classified by CLST/aCD4 based GeneSet-ResNet model. Subgroups defined by CLST and aCD4 were significantly involved in the sensitivity of hepatitis B virus-hepatocellular carcinoma patients to chemotherapy treatments.Conclusion: CLST and aCD4 are hepatitis B virus pathogenesis-relevant immunosignals that are highly involved in hepatitis B virus-induced inflammation, fibrosis, and hepatocellular carcinoma. Gene set variation analysis derived immunogenomic signatures enabled efficient diagnostic and prognostic model construction. The clinical application of CLST and aCD4 as indicators would be beneficial for the precision management of hepatocellular carcinoma.