Screening of Genes Associated with Immune Infiltration of Discoid Lupus Erythematosus Based on Weighted Gene Co-expression Network Analysis.

Discoid lupus erythematosus (DLE) is a disorder of the immune system commonly seen in women of childbearing age. The pathophysiology and aetiology are still poorly understood, and no cure is presently available. Therefore, there is an urgent need to explore the underlying molecular mechanisms, as well as search for new therapeutic targets. Gene expression data from skin biopsies samples of DLE patients and healthy controls were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) between DLE and healthy control samples were identified by differential expression analysis. Samples were analysed using CIBERSORT to examine the proportion of immune infiltration. Weighted gene co-expression network analysis was used to screen for the module most relevant to immune infiltration. Candidate genes were uploaded to the TRRUST database to obtain the potential transcription factors regulating these genes. Protein-protein interaction (PPI) analysis was performed to obtain the hub genes most associated with immune infiltration among the candidate genes. A total of 273 DEGs were identified between the DLE and healthy control samples. The results of immunoinfiltration analysis showed that the abundances of resting memory CD4 T cells, activated memory CD4 T cells and M1 macrophages were significantly higher, while those of resting infiltration of plasma cells, regulatory T cells and dendritic cells were lower in DLE samples than in healthy control samples. Correlation analysis showed that ISG15, TRIM22, XAF1, IFIT2, OAS2, OAS3, OAS1, IFI44, IFI6, BST2, IFIT1 and MX2 were negatively correlated with the abundances of plasma cells, T-cell regulatory cells and resting dendritic cells and positively correlated with activated memory CD4 T cells and M1 macrophages. Our study shows that these hub genes may regulate DLE via immune-related pathways mediated by the infiltration of these immune cells.

Identification of mitochondrial-related genes as potential biomarkers for the subtyping and prediction of Alzheimer's disease.

Introduction: Alzheimer's disease (AD) is a progressive and debilitating neurodegenerative disorder prevalent among older adults. Although AD symptoms can be managed through certain treatments, advancing the understanding of underlying disease mechanisms and developing effective therapies is critical. Methods: In this study, we systematically analyzed transcriptome data from temporal lobes of healthy individuals and patients with AD to investigate the relationship between AD and mitochondrial autophagy. Machine learning algorithms were used to identify six genes-FUNDC1, MAP1LC3A, CSNK2A1, VDAC1, CSNK2B, and ATG5-for the construction of an AD prediction model. Furthermore, AD was categorized into three subtypes through consensus clustering analysis. Results: The identified genes are closely linked to the onset and progression of AD and can serve as reliable biomarkers. The differences in gene expression, clinical features, immune infiltration, and pathway enrichment were examined among the three AD subtypes. Potential drugs for the treatment of each subtype were also identified. Discussion: The findings observed in the present study can help to deepen the understanding of the underlying disease mechanisms of AD and enable the development of precision medicine and personalized treatment approaches.

Gene expression changes reveal the impact of the space environment on the skin of International Space Station astronauts.

BACKGROUND: The various types of ionizing radiation and altered gravity in the space environment present a risk to humans during space missions. Changes in the space environment lead to skin diseases, affecting the status of the aviators to fly. Therefore, it is important to explore the molecular-level changes in the skin during space missions. OBJECTIVES: Bioinformatics analysis of gene arrays from hair follicle tissue of 10 astronauts was performed to explore changes in gene expression before, during and after space missions. METHODS: First, STEM (Short Time-series Expression Miner) software was used to identify the expression patterns of hair follicle genes of astronauts pre-, in- and postflight. Gene Ontology Enrichment Analysis was then performed to explore the gene functions within the module. Protein-protein interaction network analysis was performed on skin-related genes. The transcriptional regulatory network within the module was constructed using the TRRUST database. The circadian rhythm-related genes within the module were screened using the MSigDB (Molecular Signatures Database). RESULTS: Based on differential expression analysis between the two groups, there were 327 differentially expressed genes after the astronauts entered space compared with preflight, and only 54 differentially expressed genes after returning to Earth. This outcome suggests that the expression of most genes can be recovered on return to the ground, but there are a small number of genes whose expression cannot be recovered in a short period of time. Based on time series analysis, 311 genes showed increased expression on entry into space and decreased expression on return to Earth. The genes of this expression pattern were associated with skin development, keratinocyte differentiation and cornification. Ten hub genes were identified as skin-related genes within the module, as well as nine transcription factors and three circadian genes. One hundred and seventy-nine genes decreased in expression after entry into space and increased on return to Earth. By reviewing the literature, we found that four of the genes, CSCD2, HP, CXCR1 and SSTR4, are associated with skin diseases. CONCLUSIONS: Through bioinformatics analysis, we found that the space environment affects skin keratinocyte differentiation, leading to skin barrier damage and inflammatory responses, and that this effect was decreased after return to Earth.

Rocuronium bromide suppresses esophageal cancer via blocking the secretion of C-X-C motif chemokine ligand 12 from cancer associated fibroblasts.

BACKGROUND: Cancer associated fibroblasts (CAFs) communicate metabolically with tumor genesis and development. Rocuronium bromide (RB) is reported to exert certain inhibitory effect on tumor. Here, we investigate the role of RB in esophageal cancer (EC) malignant progression. METHODS: Tumor xenograft models with EC cells were locally and systemically administrated with RB to detect the influence of different administrations on tumor progression. Mouse CAFs PDGFRα+/F4/80- were sorted by Flow cytometry with specific antibodies. CAFs were treated with RB and co-cultured with EC cells. The proliferation, invasion and apoptosis assays of EC cells were performed to detect the influences of RB targeting CAFs on EC cell malignant progression. Human fibroblasts were employed to perform these detections to confirm RB indirect effect on EC cells. The gene expression changes of CAFs response to RB treatment were detected using RNA sequencing and verified by Western blot, immunohistochemistry and ELISA. RESULTS: Tumors in xenograft mice were observed significantly inhibited by local RB administration, but not by systemic administration. Moreover EC cells did not show obvious change in viability when direct stimulated with RB in vitro. However, when CAFs treated with RB were co-cultured with EC cells, obvious suppressions were observed in EC cell malignancy, including proliferation, invasion and apoptosis. Human fibroblasts were employed to perform these assays and similar results were obtained. RNA sequencing data of human fibroblast treated with RB, and Western blot, immunohistochemistry and ELISA results all showed that CXCL12 expression was significantly diminished in vivo and in vitro by RB. EC cells direct treated with CXCL12 showed much higher malignancy. Moreover cell autophagy and PI3K/AKT/mTOR signaling pathway in CAFs were both suppressed by RB which can be reversed by Rapamycin pretreatment. CONCLUSIONS: Our data suggest that RB could repress PI3K/AKT/mTOR signaling pathway and autophagy to block the CXCL12 expression in CAFs, thereby weakening the CXCL12-mediated EC tumor progression. Our data provide a novel insight into the underlying mechanism of RB inhibiting EC, and emphasize the importance of tumor microenvironment (cytokines from CAFs) in modulating cancer malignant progression.

Feasibility of the novel vascular disrupting agent C118P for facilitating high-intensity focused ultrasound ablation of uterine fibroids.

OBJECTIVE: In this study, C118P, a novel vascular disrupting agent (VDA), was evaluated for its ability in improving the ablative effect of high-intensity focused ultrasound (HIFU) on uterine fibroids by reducing blood perfusion. METHODS: Eighteen female rabbits were infused with isotonic sodium chloride solution (ISCS), C118P or oxytocin for 30 min, and an HIFU ablation of the leg muscles was performed within the last 2 min. Blood pressure, heart rate and laser speckle flow imaging (LSFI) of the auricular blood vessels were recorded during perfusion. Ears with vessels, uterus and muscle ablation sites were collected and sliced for hematoxylin-eosin (HE) staining to compare vascular size, as well as nicotinamide adenine dinucleotide-tetrazolium reductase (NADH-TR) staining to observe necrosis after ablation. RESULTS: Analyses revealed that the perfusion of C118P or oxytocin steadily reduced blood perfusion in the ears to approximately half by the end of the perfusion, constricted the blood vessels of the ears and uterus, and improved HIFU ablation in the muscle tissues. C118P increased blood pressure and decreased heart rate. The degree of contraction of the auricular and uterine blood vessels was positively correlated. CONCLUSION: This study confirmed that C118P could reduce blood perfusion in various tissues and had a better synergistic effect with HIFU ablation of muscle (the same tissue type as fibroids) than did oxytocin. C118P could therefore possibly replace oxytocin in facilitating HIFU ablation of uterine fibroids; however, electrocardiographic monitoring is required.

Immune infiltration and diagnostic value of immune-related genes in periodontitis using bioinformatics analysis.

BACKGROUND AND OBJECTIVES: Periodontitis, which is a chronic inflammatory periodontal disease resulting in destroyed periodontal tissue, is the leading cause of tooth loss in adults. Many studies have found that inflammatory immune responses are involved in the risk of periodontal tissue damage. Therefore, we analyzed the association between immunity and periodontitis using bioinformatics methods to further understand this disease. MATERIALS AND METHODS: First, the expression profiles of periodontitis and healthy samples were downloaded from the GEO database, including a training dataset GSE16134 and an external validation dataset GSE10334. Then, differentially expressed genes were identified using the limma package. Subsequently, immune cell infiltration was calculated by using the CIBERSORT algorithm. We further identified genes linking periodontitis and immunity from the ImmPort and DisGeNet databases. In addition, some of them were selected to construct a diagnostic model via a logistic stepwise regression analysis. RESULTS AND CONCLUSIONS: Two hundred sixty differentially expressed genes were identified and found to be involved in responses to bacterial and immune-related processes. Subsequently, immune cell infiltration analysis demonstrates significant differences in the abundance of most immune cells between periodontitis and healthy samples, especially in plasma cells. These results suggested that immunity doses play a non-negligible role in periodontitis. Twenty-one genes linking periodontitis and immunity were further identified. And nine hub genes of them were identified that may be key genes involved in the development of periodontitis. Gene ontology analyses showed that these genes are involved in response to molecules of bacterial origin, cell chemotaxis, and response to chemokines. In addition, three genes of them were selected to construct a diagnostic model. And its good diagnostic performance was demonstrated by the receiver operating characteristic curves, with an area under the curve of 0.9424 for the training dataset and 0.9244 for the external validation dataset.

A prognostic and therapeutic hallmark developed by the integrated profile of basement membrane and immune infiltrative landscape in lung adenocarcinoma.

Basement membranes (BMs) are specialised extracellular matrices that maintain cellular integrity and resist the breaching of carcinoma cells for metastases while regulating tumour immunity. The tumour immune microenvironment (TME) is essential for tumour growth and the response to and benefits from immunotherapy. In this study, the BM score and TME score were constructed based on the expression signatures of BM-related genes and the presence of immune cells in lung adenocarcinoma (LUAD), respectively. Subsequently, the BM-TME classifier was developed with the combination of BM score and TME score for accurate prognostic prediction. Further, Kaplan-Meier survival estimation, univariate Cox regression analysis and receiver operating characteristic curves were used to cross-validate and elucidate the prognostic prediction value of the BM-TME classifier in several cohorts. Findings from functional annotation analysis suggested that the potential molecular regulatory mechanisms of the BM-TME classifier were closely related to the cell cycle, mitosis and DNA replication pathways. Additionally, the guiding value of the treatment strategy of the BM-TME classifier for LUAD was determined. Future clinical disease management may benefit from the findings of our research.

Construction of a novel miRNA regulatory network and identification of target genes in gestational diabetes mellitus by integrated analysis.

Backgrounds: Given the roles of microRNA (miRNA) in human diseases and the high incidence of gestational diabetes mellitus (GDM), the aim of the study was to examine miRNA signatures and crucial pathways, as well as possible biomarkers for GDM diagnosis. Methods: We conducted a two-stage study to explore functional miRNA and those target genes. Twelve participants (6 GDM and 6 non-GDM) were first enrolled and performed RNA sequencing analysis. The overlapped candidate genes were further screened in combination with differentially expressed genes (DEGs) of GEO datasets (GSE87295, GSE49524 and GSE19649) and potential target genes of DEMs. Candidate genes, critical pathways, small molecular compounds and regulatory networks were identified using bioinformatic analysis. The potential candidate genes were then investigated using the GEO dataset (GSE103552) of 19 participants in the validation stage (11 GDM and 8 non-GDM women). Results: Briefly, blood samples were sequenced interrogating 50 miRNAs, including 20 upregulated and 30 downregulated differentially expressed microRNAs(DEMs) in our internal screening dataset. After screening GEO databases, 123 upregulated and 70 downregulated genes were overlapped through DEGs of GEO datasets and miRNA-target genes. MiR-29b-1-5p-TGFB2, miR-142-3p-TGFB2, miR-9-5p-FBN2, miR-212-5p-FBN2, miR-542-3p-FBN1, miR-9-5p-FBN1, miR-508-3p-FBN1, miR-493-5p-THBS1, miR-29b-3p-COL4A1, miR-432-5p-COL5A2, miR-9-5p-TGFBI, miR-486-3p-SLC7A5 and miR-6515-5p-SLC1A5 were revealed as thirteen possible regulating pathways by integrative analysis. Conclusion: Overall, thirteen candidate miRNA-target gene regulatory pathways representing potentially novel biomarkers of GDM diseases were revealed. Ten chemicals were identified as putative therapeutic agents for GDM. This study examined a series of DEGs that are associated with epigenetic alternations of miRNA through an integrated approach and gained insight into biological pathways in GDM. Precise diagnosis and therapeutic targets of GDM would be further explored through putative genes in the future.

Effects of the Targeted Regulation of CCRK by miR-335-5p on the Proliferation and Tumorigenicity of Human Renal Carcinoma Cells.

Cell cycle-related kinase (CCRK) is most closely related to cyclin-dependent protein kinase, which may activate cyclin-dependent kinase 2 and is associated with the growth of human cancer cells. However, the expression and function of CCRK in the pathogenesis of clear cell renal cell cancer (ccRCC) are unclear. Herein, this research aimed to explore the potential mechanism of the targeted regulation of CCRK by miR-335-5p on the proliferation and tumorigenicity of human ccRCC cells. The results showed that CCRK was significantly overexpressed in ccRCC tissues and cells, and knockdown of the CCRK expression by shRNA inhibited cell proliferation in vitro and in vivo and enhanced cell apoptosis in vitro, which indicated that CCRK could be a potential target for antitumour drugs in the treatment of ccRCC. Moreover, miR-335-5p was found to bind directly to the 3' untranslated region of CCRK, was expressed at markedly low levels in ccRCC cells, and was closely associated with the tumour stage. The overexpression of CCRK partially reversed the inhibitory effects of miR-335-5p on the cell growth of ccRCC, which implied that miR-335-5p could serve as a promising tumour inhibitor for ccRCC. In summary, CCRK could serve as an alternative antitumour drug target, and miR-335-5p could be a promising therapeutic tumour inhibitor for ccRCC treatment.

The complete chloroplast genome of Strobilanthes crispus (Acanthaceae).

We reported and characterized the complete chloroplast genome sequence of Strobilanthes crispus Blume 1826. Strobilanthes crispus belongs to the Acanthaceae family and has a number of local names including Batuzin, Bayam Karang, Kotz Bellin, and Pekka Batu, which is native to Malaysian with diverse beneficial uses. Green leaves were determined using next-generation sequencing. We found that the entire chloroplast genome of S. crispus was 144,987 bp in length, included four segments, named a large single-copy (LSC) region (92,556 bp), a small single-copy (SSC) region (17,783 bp), and a pair inverted repeat regions (IRs) (17,324 bp in each), respectively. The chloroplast genome of S. crispus contained a total of 129 functional genes, including 84 protein-coding genes, 37 transfer RNAs (tRNAs), and eight ribosomal RNA (rRNA) genes. The phylogenetic tree reconstructed by nine chloroplast genomes reveals that S. crispus is most closely related to Strobilanthes bantonensis and Strobilanthes cusia.

Immunological and prognostic analysis of PSENEN in low-grade gliomas: An immune infiltration-related prognostic biomarker.

Metformin is widely used in the treatment of type 2 diabetes (T2D) and plays a role in antitumor and antiobesity processes. A recent study identified its direct molecular target, PEN2 (PSENEN). PSENEN is the minimal subunit of the multiprotein complex γ-secretase, which promotes the differentiation of oligodendrocyte progenitors into astrocytes in the central nervous system. This study was mainly based on gene expression data and clinical data from the TCGA and CGGA databases. Analysis of differential expression of PSENEN between tissues from 31 cancers and paracancerous tissues revealed that it had high expression levels in most cancers except 2 cancers. Using univariate Cox regression analysis and Kaplan-Meier survival analysis, a high expression level of PSENEN was shown to be a risk factor in low-grade gliomas (LGG). Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) analyses indicated that PSENEN is widely involved in immune-related signaling pathways in LGG. PSENEN expression level was significantly associated with TMB, MSI, tumor stemness index, and the expression levels of immunomodulatory genes in LGG. Finally, immune infiltration analysis revealed that PSENEN level was associated with the presence of various immune infiltrating cells, among which PSENEN was strongly associated with the presence of M2 macrophages and played a synergistic pro-cancer role. In conclusion, PSENEN may partially influence prognosis by modulating immune infiltration in patients with LGG, and PSENEN may be a candidate prognostic biomarker for determining prognosis associated with immune infiltration in LGG.

Corrigendum: Analysis of time series gene expression and DNA methylation reveals the molecular features of myocardial infarction progression.

[This corrects the article DOI: 10.3389/fcvm.2022.912454.].

The Long Noncoding RNA MEG3 Retains Epithelial-Mesenchymal Transition by Sponging miR-146b-5p to Regulate SLFN5 Expression in Breast Cancer Cells.

More and more studies have shown that long noncoding RNAs (lncRNAs) play essential roles in malignant tumors. The lncRNA MEG3 serves as a crucial molecule in breast cancer development, but the specific molecular mechanism needs to be further explored. We previously reported that Schlafen family member 5 (SLFN5) inhibits breast cancer malignant development by regulating epithelial-mesenchymal transition (EMT), invasion, and proliferation/apoptosis. Herein, we demonstrated that MEG3 was downregulated in pan-cancers and correlated with SLFN5 expression positively in breast cancer by bioinformatics analysis of TCGA and UCSC Xena data. Intervention with MEG3 positively affected SLFN5 expression in breast cancer cells. MEG3 repressed EMT and migration/invasion, similar to our previously reported functions of SLFN5 in breast cancer. Through bioinformatics analysis of starBase and LncBase data, 12 miRNAs were found to regulate both SLFN5 and MEG3, in which miR-146b-5p was confirmed to be regulated by MEG3 using MEG3 siRNA and overexpression method. MiR-146b-5p could bind to both SLFN5 3'UTR and MEG3, and inhibit their expression in a competing endogenous RNA mechanism, assayed by luciferase reporter and RNA pull down methods. Therefore, we conclude that MEG3 positively modulates SLFN5 expression by sponging miR-146b-5p and inhibits breast cancer development.

Corrigendum: Prognostic ferroptosis-related lncRNA signatures associated with immunotherapy and chemotherapy responses in patients with stomach cancer.

[This corrects the article DOI: 10.3389/fgene.2021.798612.].

Hub Genes, Diagnostic Model, and Predicted Drugs Related to Iron Metabolism in Alzheimer's Disease.

Alzheimer's disease (AD), the most common neurodegenerative disease, remains unclear in terms of its underlying causative genes and effective therapeutic approaches. Meanwhile, abnormalities in iron metabolism have been demonstrated in patients and mouse models with AD. Therefore, this study sought to find hub genes based on iron metabolism that can influence the diagnosis and treatment of AD. First, gene expression profiles were downloaded from the GEO database, including non-demented (ND) controls and AD samples. Fourteen iron metabolism-related gene sets were downloaded from the MSigDB database, yielding 520 iron metabolism-related genes. The final nine hub genes associated with iron metabolism and AD were obtained by differential analysis and WGCNA in brain tissue samples from GSE132903. GO analysis revealed that these genes were mainly involved in two major biological processes, autophagy and iron metabolism. Through stepwise regression and logistic regression analyses, we selected four of these genes to construct a diagnostic model of AD. The model was validated in blood samples from GSE63061 and GSE85426, and the AUC values showed that the model had a relatively good diagnostic performance. In addition, the immune cell infiltration of the samples and the correlation of different immune factors with these hub genes were further explored. The results suggested that these genes may also play an important role in immunity to AD. Finally, eight drugs targeting these nine hub genes were retrieved from the DrugBank database, some of which were shown to be useful for the treatment of AD or other concomitant conditions, such as insomnia and agitation. In conclusion, this model is expected to guide the diagnosis of patients with AD by detecting the expression of several genes in the blood. These hub genes may also assist in understanding the development and drug treatment of AD.

Analysis of Time Series Gene Expression and DNA Methylation Reveals the Molecular Features of Myocardial Infarction Progression.

Myocardial infarction (MI) is one of the deadliest diseases in the world, and the changes at the molecular level after MI and the DNA methylation features are not clear. Understanding the molecular characteristics of the early stages of MI is of significance for the treatment of the disease. In this study, RNA-seq and MeDIP-seq were performed on heart tissue from mouse models at multiple time points (0 h, 10 min, 1, 6, 24, and 72 h) to explore genetic and epigenetic features that influence MI progression. Analysis based on a single point in time, the number of differentially expressed genes (DEGs) and differentially methylated regions (DMRs) increased with the time of myocardial infarction, using 0 h as a control group. Moreover, within 10 min of MI onset, the cells are mainly in immune response, and as the duration of MI increases, apoptosis begins to occur. Analysis based on time series data, the expression of 1012 genes was specifically downregulated, and these genes were associated with energy metabolism. The expression of 5806 genes was specifically upregulated, and these genes were associated with immune regulation, inflammation and apoptosis. Fourteen transcription factors were identified in the genes involved in apoptosis and inflammation, which may be potential drug targets. Analysis based on MeDIP-seq combined with RNA-seq methodology, focused on methylation at the promoter region. GO revealed that the downregulated genes with hypermethylation at 72 h were enriched in biological processes such as cardiac muscle contraction. In addition, the upregulated genes with hypomethylation at 72 h were enriched in biological processes, such as cell-cell adhesion, regulation of the apoptotic signaling pathway and regulation of angiogenesis. Among these genes, the Tnni3 gene was also present in the downregulated model. Hypermethylation of Tnni3 at 72 h after MI may be an important cause of exacerbation of MI.

The Relationship between Sleep Duration and Stroke Risk: The Mediating Role of Physical Activity.

Background: This study aimed to investigate the mediating effect of physical activity (PA) on the relationship between average sleep duration and risk of stroke in suburban residents without stroke. Methods: A cross-sectional study was executed, and participants were recruited through a multistage, stratified, probability-proportional-to-size sampling method in this research. The stroke risk was measured using a risk assessment form for a high-risk stroke population. The PA score was calculated by the Physical Activity Rating Scale-3 (PARS-3). The average sleep duration was calculated by adding up night sleep and afternoon nap durations. A multiple linear regression analysis was conducted to identify the association between stroke risk, average sleep duration, and PA. The direct and indirect effects of average sleep duration on stroke risk were analyzed by using the PA in a mediation framework. Results: A total of 5312 suburban residents (average: 54.96 ± 12.21 years, 2970 women) participated in the study. After adjusting for covariates, relatively inappropriate sleep duration (<7 h/>8 h~9 h/>9 h) and stroke risk were significantly associated, compared with the moderate average sleep duration (7~8 h) (ß = 0.038, 95% CI: 0.024~0.128; ß = 0.078, 95% CI: 0.128~0.250; ß = 0.150, 95% CI: 0.390~0.549). The PA total score (indirect effect ab = 0.013, 95% CI: 0.003~0.022) partially mediated the relationship between the long average sleep duration and stroke risk, in which the activity intensity (ab = −0.015, 95% CI: −0.021~−0.008), the activity duration (ab = 0.043, 95% CI: 0.029~0.058), and the activity frequency (ab = 0.012, 95% CI: 0.004~0.020; ab = 0.037, 95% CI: 0.026~0.050) all played a mediating role in the different sleep duration. Conclusions: A significant relationship between a long average sleep duration and stroke risk factors among people without stroke was found in this study. The PA and its components partially mediated the association between a long average sleep duration and stroke risk. Suitable prevention methods and interventions for PA and sleep may reduce the risk of stroke.

A Pan-Cancer Analysis Reveals the Prognostic and Immunotherapeutic Value of ALKBH7.

Recent studies have identified a role for ALKBH7 in the occurrence and progression of cancer, and this protein is related to cellular immunity and immune cell infiltration. However, the prognostic and immunotherapeutic value of ALKBH7 in different cancers have not been explored. In this study, we observed high ALKBH7 expression in 17 cancers and low expression in 5 cancers compared to paired normal tissues. Although ALKBH7 expression did not correlate relatively significantly with the clinical parameters of age (6/33), sex (3/33) and stage (3/27) in the cancers studied, the results of the survival analysis reflect the pan-cancer prognostic value of ALKBH7. In addition, ALKBH7 expression was significantly correlated with the TMB (7/33), MSI (13/33), mDNAsi (12/33) and mRNAsi (13/33) in human cancers. Moreover, ALKBH7 expression was associated and predominantly negatively correlated with the expression of immune checkpoint (ICP) genes in many cancers. Furthermore, ALKBH7 correlated with infiltrating immune cells and ESTIMATE scores, especially in PAAD, PRAD and THCA. Finally, the ALKBH7 gene coexpression network is involved in the regulation of cellular immune, oxidative, phosphorylation, and metabolic pathways. In conclusion, ALKBH7 may serve as a potential prognostic pan-cancer biomarker and is involved in the immune response. Our pan-cancer analysis provides insight into the role of ALKBH7 in different cancers.

Identification of Ferroptosis-Related Biomarkers for Prognosis and Immunotherapy in Patients With Glioma.

Ferroptosis is a novel type of iron- and ROS-dependent cell death and is involved in various diseases. LncRNAs are involved and play important roles in the occurrence and development of several cancers. However, researches about the role of ferroptosis-related lncRNAs in glioma are relatively rare. Here, we identified nine ferroptosis-related lncRNAs and then constructed a prognostic model by the LASSO and Cox analysis. The model could predict overall survival with high sensitivity and specificity according to ROC curves. In addition, the cell cycle, p53 signaling, apoptosis, and oxidative phosphorylation pathways were obviously enriched in the pathogenesis of glioma by gene set enrichment analysis. A nomogram was constructed by integrating several independent prognostic clinicopathological features, and it could provide a valuable predictive tool for overall survival. Furthermore, a strong correlation between these nine lncRNAs and immunotherapy was found. Glioma patients in the high-risk group had higher TMB using somatic mutation data, different immune infiltration, and higher expression of immune checkpoints, indicating these patients might benefit from immune checkpoint inhibitor therapy. In summary, these nine ferroptosis-related lncRNAs were promising biomarkers for predicting overall survival and guiding immunotherapy or future immune checkpoint inhibitor development for glioma patients.

The Novel Regulatory Role of lncRNA-miRNA-mRNA Axis in Amyotrophic Lateral Sclerosis: An Integrated Bioinformatics Analysis.

Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative disease that primarily affects motor neurons, causing muscle atrophy, bulbar palsy, and pyramidal tract signs. However, the aetiology and pathogenesis of ALS have not been elucidated to date. In this study, a competitive endogenous RNA (ceRNA) network was constructed by analyzing the expression profiles of messenger RNAs (mRNAs) and long noncoding RNAs (lncRNAs) that were matched by 7 ALS samples and 4 control samples, and then a protein-protein interaction (PPI) network was constructed to identify the genes related to ALS. Gene Ontology (GO) was used to study the potential functions of differentially expressed mRNAs (DEmRNAs) in the ceRNA network. For the ALS and control groups, 247177 potential lncRNA-mRNA ceRNA relationship pairs were screened. Analysis of significant relationship pairs demonstrated that the PPI modules formed by the MALAT1-regulated SYNRG, ITSN2, PICALM, AP3B1, and AAK1 genes may play important roles in the pathogenesis of ALS, and these results may help to characterize the pathogenesis of ALS.