The emerging significance of mitochondrial targeted strategies in NAFLD treatment.

Nonalcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver disease worldwide, ranging from liver steatosis to nonalcoholic steatohepatitis, which ultimately progresses to fibrosis, cirrhosis, and hepatocellular carcinoma. Individuals with NAFLD have a higher risk of developing cardiovascular and extrahepatic cancers. Despite the great progress being made in understanding the pathogenesis and the introduction of new pharmacological targets for NAFLD, no drug or intervention has been accepted for its management. Recent evidence suggests that NAFLD may be a mitochondrial disease, as mitochondrial dysfunction is involved in the pathological processes that lead to NAFLD. In this review, we describe the recent advances in our understanding of the mechanisms associated with mitochondrial dysfunction in NAFLD progression. Moreover, we discuss recent advances in the efficacy of mitochondria-targeted compounds (e.g., Mito-Q, MitoVit-E, MitoTEMPO, SS-31, mitochondrial uncouplers, and mitochondrial pyruvate carrier inhibitors) for treating NAFLD. Furthermore, we present some medications currently being tested in clinical trials for NAFLD treatment, such as exercise, mesenchymal stem cells, bile acids and their analogs, and antidiabetic drugs, with a focus on their efficacy in improving mitochondrial function. Based on this evidence, further investigations into the development of mitochondria-based agents may provide new and promising alternatives for NAFLD management.

A novel predictive model for the recurrence of pediatric alopecia areata by bioinformatics analysis and a single-center prospective study.

Background: Alopecia areata (AA) is a disease featured by recurrent, non-scarring hair loss with a variety of clinical manifestations. The outcome of AA patients varies greatly. When they progress to the subtypes of alopecia totalis (AT) or alopecia universalis (AU), the outcome is unfavorable. Therefore, identifying clinically available biomarkers that predict the risk of AA recurrence could improve the prognosis for AA patients. Methods: In this study, we conducted weighted gene co-expression network analysis (WGCNA) and functional annotation analysis to identify key genes that correlated to the severity of AA. Then, 80 AA children were enrolled at the Department of Dermatology, Wuhan Children's Hospital between January 2020 to December 2020. Clinical information and serum samples were collected before and after treatment. And the serum level of proteins coded by key genes were quantitatively detected by ELISA. Moreover, 40 serum samples of healthy children from the Department of Health Care, Wuhan Children's Hospital were used for healthy control. Results: We identified four key genes that significantly increased (CD8A, PRF1, and XCL1) or decreased (BMP2) in AA tissues, especially in the subtypes of AT and AU. Then, the serum levels of these markers in different groups of AA patients were detected to validate the results of bioinformatics analysis. Similarly, the serum levels of these markers were found remarkedly correlated with the Severity of Alopecia Tool (SALT) score. Finally, a prediction model that combined multiple markers was established by conducting a logistic regression analysis. Conclusion: In the present study, we construct a novel model based on serum levels of BMP2, CD8A, PRF1, and XCL1, which served as a potential non-invasive prognostic biomarker for forecasting the recurrence of AA patients with high accuracy.

A novel liver zonation phenotype-associated molecular classification of hepatocellular carcinoma.

Background: Liver zonation is a unique phenomenon in which the liver exhibits distinct functions among hepatocytes along the radial axis of the lobule. This phenomenon can cause the sectionalized initiation of several liver diseases, including hepatocellular carcinoma (HCC). However, few studies have explored the zonation features of HCC. Methods: Four single-cell RNA sequencing datasets were used to identify hepatocyte-specific zonation markers. Integrative analysis was then performed with a training RNA-seq cohort (616 HCC samples) and an external validating microarray cohort (285 HCC samples) from the International Cancer Genome Consortium, The Cancer Genome Atlas, Gene Expression Omnibus, and EMBL's European Bioinformatics Institute for clustering using non-negative matrix factorization consensus clustering based on zonation genes. Afterward, we evaluated the prognostic value, clinical characteristics, transcriptome and mutation features, immune infiltration, and immunotherapy response of the HCC subclasses. Results: A total of 94 human hepatocyte-specific zonation markers (39 central markers and 55 portal markers) were identified for the first time. Subsequently, three subgroups of HCC, namely Cluster1, Cluster2, and Cluster3 were identified. Cluster1 exhibited a non-zonational-like signature with the worst prognosis. Cluster2 was intensively associated with a central-like signature and exhibited low immune infiltration and sensitivity toward immune blockade therapy. Cluster3 was intensively correlated with a portal-like signature with the best prognosis. Finally, we identified candidate therapeutic targets and agents for Cluster1 HCC samples. Conclusion: The current study established a novel HCC classification based on liver zonation signature. By classifying HCC into three clusters with non-zonational-like (Cluster1), central-like (Cluster2), and portal-like (Cluster3) features, this study provided new perspectives on the heterogeneity of HCC and shed new light on delivering precision medicine for HCC patients.

Dermoscopic features of children scabies.

Scabies is a common skin disorder, caused by the ectoparasite Sarcoptes scabiei. The scabies mites burrow is highly diagnostic but illegible by the naked eye, because it is tiny and may completely be obscured by scratch and crust. The classic technique is opening the end of an intact mite burrow with a sharp instrument and inspecting its contents in the light microscope under loupe vision. Dermatoscope is a new method to diagnose scabies, with the advantages of non-invasive and more sensitive. This study verified the characteristic manifestations of scabies under dermoscopy. Under the closer examination of the curvilinear scaly burrow, the scabies mite itself may be seen as a dark equilateral triangular structure, which is often referred to as a "jet with contrail." Besides, this study found that the positive detection rate of microscopic characteristic manifestations under the dermoscopy ordered by the external genitals, the finger seams and the trunk, which were statistically different (P-value < 0.05). Of note, this is the first study to explore the regional distribution of the characteristic dermoscopic manifestations of scabies. We are the first to propose to focus on examining the external genitalia and finger seams with dermoscopy.

RNA methylation regulators contribute to poor prognosis of hepatocellular carcinoma associated with the suppression of bile acid metabolism: a multi-omics analysis.

RNA methylation has been known to promote the initiation and progression of many types of cancer, including hepatocellular carcinoma (HCC). To fully understand the importance of this post-transcriptional modification in HCC, a thorough investigation that combines different patterns of RNA methylation is urgently needed. In this study, we investigated the regulators of the three most common types of RNA methylation: m6A, N1-methyladenosine (m1A) and 5-methylcytosine (m5C). Based on the genomic and proteomic data, we constructed a classifier consisting of seven RNA methylation regulators. This classifier performed well and robustly predicted the prognosis of HCC patients. By analysis using this classifier, we found that the primary bile acid biosynthesis pathway was mostly downregulated in high-risk HCC patients. Furthermore, we found that the gene expression patterns regulated by several bile acids were similar to those regulated by some well-defined anti-tumor compounds, indicating that bile acid metabolism plays a crucial role in the progression of HCC, and the related metabolites can be used as the potential agents for HCC treatments. Moreover, our study revealed a crosstalk between RNA methylation and bile acid regulators, demonstrating a novel mechanism of the downregulation of bile acid metabolism in HCC and providing new insights into how RNA methylation regulators affect the oncogenesis of HCC.

Prediction of the Risk of Alopecia Areata Progressing to Alopecia Totalis and Alopecia Universalis: Biomarker Development with Bioinformatics Analysis and Machine Learning.

BACKGROUND: Alopecia areata (AA) is an autoimmune disease typified by nonscarring hair loss with a variable clinical course. Although there is an increased understanding of AA pathogenesis and progress in its treatments, the outcome of AA patients remains unfavorable, especially when they are progressing to the subtypes of alopecia totalis (AT) or alopecia universalis (AU). Thus, identifying biomarkers that reflect the risk of AA progressing to AT or AU could lead to better interventions for AA patients. METHODS: In this study, we conducted bioinformatics analyses to select key genes that correlated to AU or AT based on the whole-genome gene expression of 122 human scalp skin biopsy specimens obtained from NCBI-GEO GSE68801. Then, we built a biomarker using 8 different machine learning (ML) algorithms based on the key genes selected by bioinformatics analyses. RESULTS: We identified 4 key genes that significantly increased (CD28) or decreased (HOXC13, KRTAP1-3, and GPRC5D) in AA tissues, especially in the subtypes of AT and AU. Besides, the predictive accuracy (area under the curve [AUC] value) of the prediction models for forecasting AA patients progressing to AT/AU models reached 90.7% (87.9%) by logistic regression, 93.8% (79.9%) by classification trees, 100.0% (76.3%) by random forest, 96.9% (76.3%) by support vector machine, 83.5% (79.9%) by K-nearest neighbors, 97.1% (87.3%) by XGBoost, and 93.3% (80.6%) by neural network algorithms for the training (internal validation) cohort. Besides, 2 molecule drugs, azacitidine and anisomycin, were identified by Cmap database. They might have the potential therapeutic effects on AA patients with high risk of progressing to AT/AU. CONCLUSIONS: In the present study, we conducted high accuracy models for predicting the risk of AA patients progressing to AT or AU, which may be important in facilitating personalized therapeutic strategies and clinical management for different AA patients.

Predicting Severe Renal and Gastrointestinal Involvement in Childhood Immunoglobulin A Vasculitis with Routine Laboratory Parameters.

BACKGROUND: Immunoglobulin A vasculitis (IgAV) is the most common vasculitis in children. Although childhood IgAV is generally considered as a self-limited disease, progressive course and poor prognosis could occur in some cases which mostly result from severe renal involvement and gastrointestinal (GI) involvement. METHODS: We performed a retrospective study of pediatric patients diagnosed as IgAV in our institution from 2016 to 2019. Patients were divided into groups based on the occurrence and severity of GI and renal involvement. Analysis of variance (ANOVA) and Kruskal-Wallis test were used to compare results of laboratory parameters among groups and prediction models were built by using logistic regression analysis. RESULTS: A total of 286 patients were enrolled. GI involvement occurred in 148 (51.7%) patients, 30 (20.3%) of which were severe cases. Renal involvement developed in 120 (42.0%) patients, 22 (18.3%) of which were severe cases. Compared with patients with only cutaneous manifestations, white blood cell (WBC) count, neutrophil-to-lymphocyte ratio (NLR), and D-dimer levels were higher in those with GI involvement, and D-dimer level was found to be positively associated with severity. Increased NLR and lower complement 3 (C3) were found in patients with renal involvement, but only C3 was relevant in distinguishing moderate and severe cases. The prediction model for severe renal involvement was: Logit (P) = 6.820 + 0.270 (age) + 0.508 (NLR) - 16.130 (C3), with an AUC of 0.914. The prediction model for severe GI involvement was: Logit (P) = -5.459 + 0.005 (WBC) + 1.355 (D-dimer) - 0.020 (NLR), with an AUC of 0.849. CONCLUSION: Our data suggest C3 to be an exclusive predictor for severe renal involvement and D-dimer level to be positively associated with the severity of GI involvement. Prediction models consisting of the above parameters were built for obtaining prognostic information in the early phase of IgAV.

Correlations of Serological Markers with Development of Systemic Involvement in Adult Immunoglobulin A Vasculitis: A Retrospective Study of 259 Patients in Central China.

OBJECTIVE: Although relatively rare, adult immunoglobulin A vasculitis (IgAV) can lead to severe complications and longer hospitalization, and result in poor prognosis, when compared to childhood IgAV. Hence, early identification and prevention for patients prone to develop systemic involvement are essential. The purpose of this study was to explore the correlations of common serological markers with the development of systemic involvement in adult IgAV. METHODS: A retrospective analysis was performed for adult IgAV patients, who were hospitalized in Wuhan Union Hospital between January 2016 and December 2019. A total of 259 patients were enrolled, and the pre-treatment serological markers were comprehensively assessed. RESULTS: In the present study, 49.0% and 33.2% of patients developed renal and gastrointestinal (GI) involvement, respectively. Furthermore, the elevated levels of white blood cells count, D-Dimer (D-D), C-reactive protein (CRP) and neutrophil granulocyte ratio (NE%) >60% were significantly associated with GI involvement in the univariate analysis, while the decrease in high density lipoprotein level, and the elevated D-D and CRP levels were significantly associated with renal involvement (P<0.05). Moreover, a prediction model that combined multiple markers was established by performing a logistic regression analysis, and this presented a more favorable value of prediction than the individual serological markers. CONCLUSION: The present study suggests that common serological markers have close correlations with systemic involvement in adult IgAV, and that the establishment of a prediction model for systemic involvement may be helpful in facilitating personalized therapeutic strategies and clinical management for IgAV patients.

Identification of Mitochondrial-Related Prognostic Biomarkers Associated With Primary Bile Acid Biosynthesis and Tumor Microenvironment of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the leading causes of tumor-associated deaths worldwide. Despite great progress in early diagnosis and multidisciplinary tumor management, the long-term prognosis of HCC remains poor. Currently, metabolic reprogramming during tumor development is widely observed to support rapid growth and proliferation of cancer cells, and several metabolic targets that could be used as cancer biomarkers have been identified. The liver and mitochondria are the two centers of human metabolism at the whole organism and cellular levels, respectively. Thus, identification of prognostic biomarkers based on mitochondrial-related genes (Mito-RGs)-the coding-genes of proteins located in the mitochondria-that reflect metabolic changes associated with HCC could lead to better interventions for HCC patients. In the present study, we used HCC data from The Cancer Genome Atlas (TCGA) database to construct a classifier containing 10 Mito-RGs (ACOT7, ADPRHL2, ATAD3A, BSG, FAM72A, PDK3, PDSS1, RAD51C, TOMM34, and TRMU) for predicting the prognosis of HCC by using 10-fold Least Absolute Shrinkage and Selection Operation (LASSO) cross-validation Cox regression. Based on the risk score calculated by the classifier, the samples were divided into high- and low-risk groups. Gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), t-distributed stochastic neighbor embedding (t-SNE), and consensus clusterPlus algorithms were used to identify metabolic pathways that were significantly different between the high- and low-risk groups. We further investigated the relationship between metabolic status and infiltration of immune cells into HCC tumor samples by using the Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) algorithm combined with the Tumor Immune Estimation Resource (TIMER) database. Our results showed that the classifier based on Mito-RGs could act as an independent biomarker for predicting survival of HCC patients. Repression of primary bile acid biosynthesis plays a vital role in the development and poor prognosis of HCC, which provides a potential approach to treatment. Our study revealed cross-talk between bile acid and infiltration of tumors by immune cells, which may provide novel insight into immunotherapy of HCC. Furthermore, our research may provide a novel method for HCC metabolic therapy based on modulation of mitochondrial function.

Corrigendum: Identification of Mitochondrial-Related Prognostic Biomarkers Associated With Primary Bile Acid Biosynthesis and Tumor Microenvironment of Hepatocellular Carcinoma.

[This corrects the article DOI: 10.3389/fonc.2021.587479.].

Corrigendum: Identification of Immune-Related Prognostic Genes and LncRNAs Biomarkers Associated With Osteosarcoma Microenvironment.

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Identification of Immune-Related Prognostic Genes and LncRNAs Biomarkers Associated With Osteosarcoma Microenvironment.

Osteosarcoma (OS) is the most common malignancy of the bone that occurs majorly in young people and adolescents. Although the survival of OS patients markedly improved by complete surgical resection and chemotherapy, the outcome is still poor in patients with recurrent and/or metastasized OS. Thus, identifying prognostic biomarkers that reflect the biological heterogeneity of OS could lead to better interventions for OS patients. Increasing studies have indicated the association between immune-related genes (IRGs) and cancer prognosis. In the present study, based on the data concerning OS obtained from TARGET (Therapeutically Applicable Research to Generate Effective Treatments) database, we constructed a classifier containing 12 immune-related (IR) long non-coding RNAs (lncRNAs) and 3 IRGs for predicting the prognosis of OS by using the least absolute shrinkage and selection operation Cox regression. Besides, based on the risk score calculated by the classifier, the samples were divided into high- and low-risk groups. We further investigated the tumor microenvironment of the OS samples by ESTIMATE and CIBERSORT algorithms between the two groups. Finally, we identified three small molecular drugs with potential therapeutic value for OS patients with high-risk score. Our results suggest that the IRGs and IR-lncRNAs-based classifier could be used as a reliable prognostic predictor for OS survival.