An angiogenesis-associated gene-based signature predicting prognosis and immunotherapy efficacy of head and neck squamous cell carcinoma patients.

OBJECTIVES: To develop a model that can assist in the diagnosis and prediction of prognosis for head and neck squamous cell carcinoma (HNSCC). MATERIALS AND METHODS: Data from TCGA and GEO databases were used to generate normalized gene expression data. Consensus Cluster Plus was used for cluster analysis and the relationship between angiogenesis-associated gene (AAG) expression patterns, clinical characteristics and survival was examined. Support vector machine (SVM) and least absolute shrinkage and selection operator (LASSO) analyzes and multiple logistic regression analyzes were performed to determine the diagnostic model, and a prognostic nomogram was constructed using univariate and multivariate Cox regression analyses. ESTIMATE, XCELL, TIMER, QUANTISEQ, MCPCOUNTER, EPIC, CIBERSORT-ABS, CIBERSORT algorithms were used to assess the immune microenvironment of HNSCC patients. In addition, gene set enrichment analysis, treatment sensitivity analysis, and AAGs mutation studies were performed. Finally, we also performed immunohistochemistry (IHC) staining in the tissue samples. RESULTS: We classified HNSCC patients into subtypes based on differences in AAG expression from TCGA and GEO databases. There are differences in clinical features, TME, and immune-related gene expression between two subgroups. We constructed a HNSCC diagnostic model based on nine AAGs, which has good sensitivity and specificity. After further screening, we constructed a prognostic risk signature for HNSCC based on six AAGs. The constructed risk score had a good independent prognostic significance, and it was further constructed into a prognostic nomogram together with age and stage. Different prognostic risk groups have differences in immune microenvironment, drug sensitivity, gene enrichment and gene mutation. CONCLUSION: We have constructed a diagnostic and prognostic model for HNSCC based on AAG, which has good performance. The constructed prognostic risk score is closely related to tumor immune microenvironment and immunotherapy response.

Exploration of potential shared gene signatures between periodontitis and multiple sclerosis.

BACKGROUND: Although periodontitis has previously been reported to be linked with multiple sclerosis (MS), but the molecular mechanisms and pathological interactions between the two remain unclear. This study aims to explore potential crosstalk genes and pathways between periodontitis and MS. METHODS: Periodontitis and MS data were obtained from the Gene Expression Omnibus (GEO) database. Shared genes were identified by differential expression analysis and weighted gene co-expression network analysis (WGCNA). Then, enrichment analysis for the shared genes was carried out by multiple methods. The least absolute shrinkage and selection operator (LASSO) regression was used to obtain potential shared diagnostic genes. Furthermore, the expression profile of 28 immune cells in periodontitis and MS was examined using single-sample GSEA (ssGSEA). Finally, real-time quantitative fluorescent PCR (qRT-PCR) and immune histochemical staining were employed to validate Hub gene expressions in periodontitis and MS samples. RESULTS: FAM46C, SLC7A7, LY96, CFI, DDIT4L, CD14, C5AR1, and IGJ genes were the shared genes between periodontitis, and MS. GO analysis revealed that the shared genes exhibited the greatest enrichment in response to molecules of bacterial origin. LASSO analysis indicated that CFI, DDIT4L, and FAM46C were the most effective shared diagnostic biomarkers for periodontitis and MS, which were further validated by qPCR and immunohistochemical staining. ssGSEA analysis revealed that T and B cells significantly influence the development of MS and periodontitis. CONCLUSIONS: FAM46C, SLC7A7, LY96, CFI, DDIT4L, CD14, C5AR1, and IGJ were the most important crosstalk genes between periodontitis, and MS. Further studies found that CFI, DDIT4L, and FAM46C were potential biomarkers in periodontitis and MS.

The role of non-coding RNAs in diabetes-induced osteoporosis.

Diabetes mellitus (DM) and osteoporosis are two major health care problems worldwide. Emerging evidence suggests that DM poses a risk for osteoporosis and can contribute to the development of diabetes-induced osteoporosis (DOP). Interestingly, some epidemiological studies suggest that DOP may be at least partially distinct from those skeletal abnormalities associated with old age or postmenopausal osteoporosis. The increasing number of DM patients who also have DOP calls for a discussion of the pathogenesis of DOP and the investigation of drugs to treat DOP. Recently, non-coding RNAs (ncRNAs) have received more attention due to their significant role in cellular functions and bone formation. It is worth noting that ncRNAs have also been demonstrated to participate in the progression of DOP. Meanwhile, nano-delivery systems are considered a promising strategy to treat DOP because of their cellular targeting, sustained release, and controlled release characteristics. Additionally, the utilization of novel technologies such as the CRISPR system has expanded the scope of available options for treating DOP. Hence, this paper explores the functions and regulatory mechanisms of ncRNAs in DOP and highlights the advantages of employing nanoparticle-based drug delivery techniques to treat DOP. Finally, this paper also explores the potential of ncRNAs as diagnostic DOP biomarkers.

Olmesartan alleviates SARS-CoV-2 envelope protein induced renal fibrosis by regulating HMGB1 release and autophagic degradation of TGF-ß1.

Background and aims: Renal damage in severe coronavirus disease 2019 (COVID-19) is highly associated with mortality. Finding relevant therapeutic candidates that can alleviate it is crucial. Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin-receptor blockers (ARBs) have been shown to be harmless to COVID-19 patients, but it remains elusive whether ACEIs/ARBs have protective benefits to them. We wished to determine if ACEIs/ARBs had a protective effect on the renal damage associated with COVID-19, and to investigate the mechanism. Methods: We used the envelope (E) protein of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) to induce COVID-19-like multiple organ damage and observed renal fibrosis. We induced the epithelial-mesenchymal transformation of HK-2 cells with E protein, and found that olmesartan could alleviate it significantly. The protective effects of olmesartan on E protein-induced renal fibrosis were evaluated by renal-function assessment, pathologic alterations, inflammation, and the TGF-ß1/Smad2/3 signaling pathway. The distribution of high-mobility group box (HMGB)1 was examined after stimulation with E protein and olmesartan administration. Results: E protein stimulated HMGB1 release, which triggered the immune response and promoted activation of TGF-ß1/Smad2/3 signaling: both could lead to renal fibrosis. Olmesartan regulated the distribution of HMGB1 under E protein stimulation. Olmesartan inhibited the release of HMGB1, and reduced the inflammatory response and activation of TGF-ß1/Smad2/3 signaling. Olmesartan increased the cytoplasmic level of HMGB1 to promote the autophagic degradation of TGF-ß1, thereby alleviating fibrosis further. Conclusion: Olmesartan alleviates E protein-induced renal fibrosis by regulating the release of HMGB1 and its mediated autophagic degradation of TGF-ß1.

Optimization of CRISPR-Cas system for clinical cancer therapy.

Cancer is a genetic disease caused by alterations in genome and epigenome and is one of the leading causes for death worldwide. The exploration of disease development and therapeutic strategies at the genetic level have become the key to the treatment of cancer and other genetic diseases. The functional analysis of genes and mutations has been slow and laborious. Therefore, there is an urgent need for alternative approaches to improve the current status of cancer research. Gene editing technologies provide technical support for efficient gene disruption and modification in vivo and in vitro, in particular the use of clustered regularly interspaced short palindromic repeats (CRISPR)-Cas systems. Currently, the applications of CRISPR-Cas systems in cancer rely on different Cas effector proteins and the design of guide RNAs. Furthermore, effective vector delivery must be met for the CRISPR-Cas systems to enter human clinical trials. In this review article, we describe the mechanism of the CRISPR-Cas systems and highlight the applications of class II Cas effector proteins. We also propose a synthetic biology approach to modify the CRISPR-Cas systems, and summarize various delivery approaches facilitating the clinical application of the CRISPR-Cas systems. By modifying the CRISPR-Cas system and optimizing its in vivo delivery, promising and effective treatments for cancers using the CRISPR-Cas system are emerging.

Emerging role for branched-chain amino acids metabolism in fibrosis.

Fibrosis is a common pathological feature of organ diseases resulting from excessive production of extracellular matrix, which accounts for significant morbidity and mortality. However, there is currently no effective treatment targeting fibrogenesis. Recently, metabolic alterations are increasingly considered as essential factors underlying fibrogenesis, and especially research on metabolic regulation of amino acids is flourishing. Among them, branched-chain amino acids (BCAAs) are the most abundant essential amino acids, including leucine, isoleucine and valine, which play significant roles in the substance and energy metabolism and their regulation. Dysregulation of BCAAs metabolism has been proven to contribute to numerous diseases. In this review, we summarize the metabolic regulation of fibrosis and the changes in BCAAs metabolism secondary to fibrosis. We also review the effects and mechanisms of the BCAAs intervention, and its therapeutic targeting in hepatic, renal and cardiac fibrosis, with a focus on the fibrosis in liver and associated hepatocellular carcinoma.

CHI3L1 Is a Liver-Enriched, Noninvasive Biomarker That Can Be Used to Stage and Diagnose Substantial Hepatic Fibrosis.

Liver fibrosis is a major disease that is primarily caused by hepatitis virus infections, toxins, and alcohol abuse. Diagnosing and staging liver fibrosis are critical in guiding the treatment of chronic liver diseases, according to several international and Chinese guidelines. Liver biopsy is the gold standard for diagnosing and staging liver fibrosis, but it is invasive and suffers from several limitations. Consequently, much research has focused on the search for a noninvasive serum biomarker of fibrosis. In this study, we determined that Chitinase 3-like 1 (CHI3L1) is an abundantly expressed liver gene whose expression is highly enriched in the liver. We then compared serum levels of CHI3L1 among patients with various stages of liver fibrosis, as determined by liver biopsies, and found that the CHI3L1 levels were able to differentiate early stages of liver fibrosis (S0-S2) from late stages of liver fibrosis (S3-S4). We further showed that CHI3L1 is a good marker of substantial fibrosis, with areas under the ROC curves (AUCs) of 0.94 for substantial (S2, S3, S4) fibrosis and 0.96 for advanced (S3, S4) fibrosis. Finally, we showed that CHI3L1 is superior to hyaluronic acid (HA), type III procollagen (PCIII), laminin (LN), and type IV collagen (CIV), which are also serum biomarkers of liver fibrosis, in identifying advanced liver fibrosis in patients with HBV-related liver fibrosis in China.