Genome-wide mutation profiling and related risk signature for prognosis of papillary renal cell carcinoma

The JAK-STAT signaling-related signature serves as a prognostic and predictive biomarker for renal cell carcinoma immunotherapy

Renal cell carcinoma (RCC) represents a significant portion of genitourinary cancers, marked by challenging prognosis and high metastasis rates. Immunotherapy has been applied in managing advanced renal cell carcinoma, but the therapeutic outcomes are unsatisfactory. In this study, we order to construct a Janus kinase/signal transduction and activator transcriptional (JAK/STAT)-related signature linked to kidney patient outcomes for better predicting the efficacy to immune checkpoint inhibitors (ICIs) and to provide guidance for effective combination therapy. We screened 25 differentially expressed genes (DEGs) that exhibited high expression in RCC samples and were enriched in the JAK-STAT signaling pathway. Among these genes, 11 key genes were identified and correlated with the expectation of Kidney Clear Cell Carcinoma (KIRC) patients and all these genes was significantly elevated in RCC tumor tissues and cancer cells compared to para-cancer tissues and normal renal cells. Utilizing these 11 genes, we divided RCC patients into high-risk and low-risk groups. We found a clear correlation between the clinicopathologic factors of KIRC patients and the JAK-STAT-related risk score. And the IHC results shown that the JAK3 and STAT4 expression of tumor was significantly higher than normal tissue in RCC patients, the level of JAK3 and STAT4 was positively related to the T stage of RCC patients. In addition, high-risk patients had a poorer prognosis and greater protumor immune cell infiltration, and benefitted less from immunotherapy than did low-risk patients. Furthermore, the JAK-STAT-related risk score can predict disease-free survival (DFS) in RCC patients according to the nomogram, which constructed in combination with other clinical features such as age, TNM-staging and stage. Our study demonstrated the JAK-STAT signaling pathway's important regulatory function in RCC tumor immunity. This insight not only enhances our ability to accurately predict the survival rate of RCC patients, but also underscores a potential therapeutic alternative for RCC, involving the combined targeting of the JAK-STAT pathway and immune checkpoints.

Identification of coagulation diagnostic biomarkers related to the severity of spinal cord injury

BACKGROUND

Blood always shows coagulation changes after spinal cord injury (SCI), and identifying these blood changes may be helpful for diagnosis and treatment of SCI. Nevertheless, studies to date on blood coagulation changes after SCI in humans are not comprehensive. Therefore, this study aims to identify blood coagulation diagnostic biomarkers and immune changes related to SCI and its severity levels.

METHODS

Human blood sequencing datasets were obtained from public databases. Differentially expressed coagulation-related genes were analyzed (DECRGs). Enrichment analysis and assessment of immune changes were conducted. Weighted gene co-expression network analysis, least absolute shrinkage and selection operator logistic regression were used to identify biomarkers. Validation for these biomarkers was performed. The correlation between biomarkers and immune cells was evaluated. Transcription factors, miRNA, lncRNA, and drugs that can regulate biomarkers were analyzed.

RESULTS

DECRGs associated with SCI and its different grades were identified, showing enrichment in altered coagulation and immune-related signaling pathways. ADAM9, CD55, and STAT4 were identified as coagulation diagnostic biomarkers for SCI. IRF4 and PABPC4 were identified as coagulation diagnostic biomarkers for American Spinal Injury Association Impairment Scale (AIS) A grade of SCI. GP9 was designated as a diagnostic biomarker for AIS D grade of SCI. Immune changes in blood of SCI and its different grades were observed. Correlation between diagnostic biomarkers and immune cells were identified. Transcription factors, miRNA, lncRNA, and drugs that can regulate diagnostic biomarker expression were discovered.

CONCLUSION

Therefore, detecting the expression of these putative diagnostic biomarkers and related immune changes may be helpful for predicting the severity of SCI. Uncovering potential regulatory mechanisms for biomarkers may be beneficial for further research.

Identification of Potential Biomarkers for Patients with DWI-Negative Ischemic Stroke

Ischemic stroke is the leading cause of long-term disability in adults, accounting for 80% of stroke cases. Diffusion weighted imaging (DWI) examination is the main test for acute ischemic stroke, but in recent years, several studies have shown that some patients show negative DWI examination after the onset of ischemic stroke with symptoms of significant neurological deficits. In this study, we investigated potential biomarkers related to immune metabolism in the peripheral blood of DWI-negative versus DWI-positive patients after ischemic stroke and explored their possible regulatory processes in ischemic stroke. The datasets related to ischemic stroke were downloaded from the GEO database, immune-related genes and metabolism-related genes were obtained from the ImmPort database and MSigDB database, respectively, and immune-related differential genes were obtained based on immune scores using the algorithm of the R software package "GSVA." Candidate genes were selected based on intersections, hub genes were screened using the algorithm in Cytoscape software, and finally, GeneMANIA analysis, GSEA enrichment analysis, subcellular localization, gene transcription factor and gene-drug interaction networks, and disease correlation analyses were performed for the hub genes. Five hub genes (GART, TYMS, PPAT, CTPS1, and PAICS) were obtained by PPI network analysis and software analysis. Among them, PPAT and PAICS may be the real hub genes with consistent and significantly differentiated results from the discovery and validation sets. The functions of these hub genes may be related to pathways such as nucleotide biosynthetic processes. The constructed hub gene ceRNA network showed that hsa-10a-5p is the key miRNA connecting PAICS and multiple lncRNAs in this study. Differential genes related to immunity and metabolism in DWI-negative and DWI-positive patients after IS were identified using bioinformatics analysis, and their pathways and related TF-RNAs, miRNAs, and lncRNAs were identified. These genes may be considered effective targets for the diagnosis and treatment of ischemic stroke.

Astaxanthin targets IL-6 and alleviates the LPS-induced adverse inflammatory response of macrophages

Numerous natural compounds are recognized for their anti-inflammatory properties attributed to antioxidant effects and the modulation of key inflammatory factors. Among them, astaxanthin (AST), a potent carotenoid antioxidant, remains relatively underexplored regarding its anti-inflammatory mechanisms and specific molecular targets. In this study, human monocytic leukemia cell-derived macrophages (THP-1) were selected as experimental cells, and lipopolysaccharides (LPS) served as inflammatory stimuli. Upon LPS treatment, the oxidative stress was significantly increased, accompanied by remarkable cellular damage. Moreover, LPSs escalated the expression of inflammation-related molecules. Our results demonstrate that AST intervention could effectively alleviate LPS-induced oxidative stress, facilitate cellular repair, and significantly attenuate inflammation. Further exploration of the anti-inflammatory mechanism revealed AST could substantially inhibit NF-κB translocation and activation, and mitigate inflammatory factor production by hindering NF-κB through the antioxidant mechanism. We further confirmed that AST exhibited protective effects against cell damage and reduced the injury from inflammatory cytokines by activating p53 and inhibiting STAT3. In addition, utilizing network pharmacology and in silico calculations based on molecular docking, molecular dynamics simulation, we identified interleukin-6 (IL-6) as a prominent core target of AST anti-inflammation, which was further validated by the RNA interference experiment. This IL-6 binding capacity actually enabled AST to curb the positive feedback loop of inflammatory factors, averting the onset of possible inflammatory storms. Therefore, this study offers a new possibility for the application and development of astaxanthin as a popular dietary supplement of anti-inflammatory or immunomodulatory function.

Exploring the mechanism of Jingshen Xiaoke decoction in treating T2DM mice based on network pharmacology and molecular docking

BACKGROUND

Jingshen Xiaoke decoction (JS) was prepared by studying the classic prescriptions of famous scholars in the past dynasties to prevent and treat diabetes. The related mechanism of JS against hyperlipidemia has yet to be revealed.

OBJECTIVE

To investigate the mechanism of action of JS in treating diabetes mellitus by using bioinformatics methods.

METHODS

A database was used to search the active ingredients and targets of the JS and targets for type 2 diabetes mellitus (T2DM). The protein interaction between the intersection targets, and the constructed the PPI network diagram was analyzed using the STRING database. Furthermore, the gene annotation tool DAVID was used to enrich the intersecting targets for the Gene ontology (GO) function and Kyoto encyclopedia of genes and genomes (KEGG) signaling pathway. Finally, Maestro software was used for molecular docking to verify the binding ability of the active ingredients to the core target genes.

RESULTS

A total of 45 active ingredients in JS were screened out corresponding to 239 effective targets, of which 64 targets were potential targets for treating T2DM. The analysis of PPI network diagram analysis revealed that the ingredients' active components are quercetin, β-sitosterol, stigmasterol, luteolin, and 7-Methoxy-2-methyl isoflavone. GO functional enrichment analysis indicated 186 biological processes (BP), 23 molecular functions (MF) and 13 cellular components (CC). KEGG pathway enrichment analysis revealed the enrichment of 59 signal pathways. The molecular docking results demonstrated that the active ingredients and core targets had a good docking affinity with a binding activity less than -7 kcal/mol. Finally, the western blotting illustrated that JS could up-regulate the liver PI3K/AKT-signaling pathway.

CONCLUSION

JS can regulate glucolipid metabolism, reduce the inflammatory response, improve insulin resistance and modulate the immune response through PI3K/AKT signaling pathway treating of T2DM and its complications effects.

Identification of key biomarkers of the glomerulus in focal segmental glomerulosclerosis and their relationship with immune cell infiltration based on WGCNA and the LASSO algorithm

OBJECTIVE

The aim of our study was to identify key biomarkers of glomeruli in focal glomerulosclerosis (FSGS) and analyze their relationship with the infiltration of immune cells.

METHODS

The expression profiles (GSE108109 and GSE200828) were obtained from the GEO database. The differentially expressed genes (DEGs) were filtered and analyzed by gene set enrichment analysis (GSEA). MCODE module was constructed. Weighted gene coexpression network analysis (WGCNA) was performed to obtain the core gene modules. Least absolute shrinkage and selection operator (LASSO) regression was applied to identify key genes. ROC curves were employed to explore their diagnostic accuracy. Transcription factor prediction of the key biomarkers was performed using the Cytoscape plugin IRegulon. The analysis of the infiltration of 28 immune cells and their correlation with the key biomarkers were performed.

RESULTS

A total of 1474 DEGs were identified. Their functions were mostly related to immune-related diseases and signaling pathways. MCODE identified five modules. The turquoise module of WGCNA had significant relevance to the glomerulus in FSGS. TGFB1 and NOTCH1 were identified as potential key glomerular biomarkers in FSGS. Eighteen transcription factors were obtained from the two hub genes. Immune infiltration showed significant correlations with T cells. The results of immune cell infiltration and their relationship with key biomarkers implied that NOTCH1 and TGFB1 were enhanced in immune-related pathways.

CONCLUSION

TGFB1 and NOTCH1 may be strongly correlated with the pathogenesis of the glomerulus in FSGS and are new candidate key biomarkers. T-cell infiltration plays an essential role in the FSGS lesion process.

An integrated bioinformatics approach to identify key biomarkers in the tubulointerstitium of patients with focal segmental glomerulosclerosis and construction of mRNA-miRNA-lncRNA/circRNA networks

OBJECTIVE

The purpose of this study was to identify potential biomarkers in the tubulointerstitium of focal segmental glomerulosclerosis (FSGS) and comprehensively analyze its mRNA-miRNA-lncRNA/circRNA network.

METHODS

The expression data (GSE108112 and GSE200818) were downloaded from the Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo/). Identification and enrichment analysis of differentially expressed genes (DEGs) were performed. the PPI networks of the DEGs were constructed and classified using the Cytoscape molecular complex detection (MCODE) plugin. Weighted gene coexpression network analysis (WGCNA) was used to identify critical gene modules. Least absolute shrinkage and selection operator regression analysis were used to screen for key biomarkers of the tubulointerstitium in FSGS, and the receiver operating characteristic curve was used to determine their diagnostic accuracy. The screening results were verified by quantitative real-time-PCR (qRT-PCR) and Western blot. The transcription factors (TFs) affecting the hub genes were identified by Cytoscape iRegulon. The mRNA-miRNA-lncRNA/circRNA network for identifying potential biomarkers was based on the starBase database.

RESULTS

A total of 535 DEGs were identified. MCODE obtained eight modules. The green module of WGCNA had the greatest association with the tubulointerstitium in FSGS. PPARG coactivator 1 alpha (PPARGC1A) was screened as a potential tubulointerstitial biomarker for FSGS and verified by qRT-PCR and Western blot. The TFs FOXO4 and FOXO1 had a regulatory effect on PPARGC1A. The ceRNA network yielded 17 miRNAs, 32 lncRNAs, and 50 circRNAs.

CONCLUSIONS

PPARGC1A may be a potential biomarker in the tubulointerstitium of FSGS. The ceRNA network contributes to the comprehensive elucidation of the mechanisms of tubulointerstitial lesions in FSGS.

Identification of hub genes and their correlation with immune infiltrating cells in membranous nephropathy: an integrated bioinformatics analysis

BACKGROUND

Membranous nephropathy (MN) is a chronic glomerular disease that leads to nephrotic syndrome in adults. The aim of this study was to identify novel biomarkers and immune-related mechanisms in the progression of MN through an integrated bioinformatics approach.

METHODS

The microarray data were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between MN and normal samples were identified and analyzed by the Gene Ontology analysis, the Kyoto Encyclopedia of Genes and Genomes analysis and the Gene Set Enrichment Analysis (GSEA) enrichment. Hub The hub genes were screened and identified by the weighted gene co-expression network analysis (WGCNA) and the least absolute shrinkage and selection operator (LASSO) algorithm. The receiver operating characteristic (ROC) curves evaluated the diagnostic value of hub genes. The single-sample GSEA analyzed the infiltration degree of several immune cells and their correlation with the hub genes.

RESULTS

We identified a total of 574 DEGs. The enrichment analysis showed that metabolic and immune-related functions and pathways were significantly enriched. Four co-expression modules were obtained using WGCNA. The candidate signature genes were intersected with DEGs and then subjected to the LASSO analysis, obtaining a total of 6 hub genes. The ROC curves indicated that the hub genes were associated with a high diagnostic value. The CD4+ T cells, CD8+ T cells and B cells significantly infiltrated in MN samples and correlated with the hub genes.

CONCLUSIONS

We identified six hub genes (ZYX, CD151, N4BP2L2-IT2, TAPBP, FRAS1 and SCARNA9) as novel biomarkers for MN, providing potential targets for the diagnosis and treatment.

Comprehensive Analyses Revealed Eight Immune Related Signatures Correlated With Aberrant Methylations as Prognosis and Diagnosis Biomarkers for Kidney Renal Papillary Cell Carcinoma

BACKGROUND

Kidney renal papillary cell carcinoma (KIRP) is a common type of renal cell carcinoma. DNA methylation plays an important role in the development of several cancers. The aim of our study was to identify differentially expressed genes associated with abnormal DNA methylation as biomarkers for predicting the outcome of KIRP.

METHOD

We downloaded KIRP methylation data, RNA sequencing (RNAseq) data, and their corresponding clinical information from the Cancer Genome Atlas (TCGA) database. ChAMP and DEGseq2 packages in R software were used to screen differentially methylated probes (DMPs) and differentially expressed genes (DEGs). Univariate and multivariate Cox regression analyses were used to identify suitable immune related genes correlated with aberrant methylations as prognosis biomarkers.

RESULTS

We identified 8 DEGs (Cysteine And Glycine Rich Protein 1 [CSRP1], major histocompatibility complex, Class II, DM Beta [HLA-DMB], LIF Receptor Subunit Alpha [LIFR], Leukotriene B4 receptor 2 [LTB4R2], Mitogen-Activated Protein Kinase Kinase Kinase 14 [MAP3K14], Nuclear Receptor Subfamily 2 Group F Member 1 [NR2F1], Secreted And Transmembrane 1 [SECTM1], and Vimentin [VIM]) that were independently associated with the overall survival (months) (OS) of KIRP. The time dependent area under the curve (AUC) for each receiver operating characteristic (ROC) of the risk assessment model at 1, 3, 5, and 10-years reached 0.8415, 0.8131, 0.7873, and 0.7667. The risk assessment model was correlated with several immune cells and factors. The AUC value of the diagnosis model using those 8 DEGs reached 0.99.

CONCLUSIONS

The risk assessment model constructed by those 8 DEGs was well able to predict the prognosis and diagnose of KIRP. However, whether the prognosis and diagnosis model could be applied in clinical practice requires further study.

A novel pyroptosis-related signature predicts prognosis and indicates immunotherapy in oral squamous cell carcinoma

BACKGROUND

Oral squamous cell carcinoma (OSCC) has been recognized as a frequently occurring oral malignant tumor. Pyroptosis plays an extremely important role in the occurrence and development of cancer, but the role of pyroptosis in OSCC remains unclear.

METHODS

OSCC-related data were obtained from the TCGA and GEO databases. A PSscore risk model was constructed through LASSO regression analysis. The GEO database was utilized as the validation set of the model. The "ESTIMATE" and "CIBERSORT" algorithms were utilized to additionally evaluate the relationship between the immune cell score and PSscore. TIDE and IPS algorithms were used to assess patient response to immunotherapy. In addition, Western blot analysis and MTT assay was used to further validate key genes.

RESULTS

Comprehensive bioinformatics analysis showed that a low-PSscore had a significant survival advantage, richer immune cell infiltration, more active immune-related pathways, higher TME scores, and lower tumor purity. The results of TIDE and IPS analysis indicated that the high-PSscore group had higher immune escape potential and was less sensitive to immunotherapy. In contrast, the low-PSscore group patients might be more sensitive to PD1 and CTLA4 + PD1 immunotherapy. Univariate and multivariate COX results indicated that PSscore was an independent prognostic factor in OSCC patients. Another important finding is that BAK1 is a potential target of OSCC and is related to the Nod-like receptor signaling pathway. Knockdown of BAK1 can significantly reduce the proliferation of OSCC cells.

CONCLUSION

The PSscore model could be utilized as a powerful prognostic indicator and can help in the development of new immunotherapies.

Identification of differential immune cells and related diagnostic genes in patients with diabetic retinopathy

BACKGROUND

Diabetic retinopathy (DR) is a frequent microvascular abnormality associated with diabetes mellitus. The loss of retinal immunity is an important underlying mechanism of the DR pathogenesis, including the change in retinal immunosuppressive characteristics and the blood-retinal barrier disturbances. Therefore, this investigation screens immune-associated biomarkers in the retina of DR patients.

METHODS

In this investigation, the differential expression genes (DEGs) were acquired from Gene Expression Omnibus data GSE102485. The relative expression of 22 immune cell types in each sample was calculated by CIBERSORT analysis based on gene expression profile. The core module closely associated with immune infiltration was also screened by weighted gene co-expression network analysis (WGCNA). The overlapping DEGs and module genes were the differentially expressed immune-related genes (DEIRGs). With the help of the genes/proteins (STRING) database and MCODE plug-in, the protein-protein interaction (PPI) network hub genes were screened. Furthermore, the miRNA-hub genes and transcription factor (TF)-hub gene regulatory network were used to explain the possible signal pathways in DR. The hub genes verification was carried out by Polymerase Chain Reaction. Lastly, select CSF1R and its related pathway factor p-ERK1/2 to verify their expression in RF/6A under normal and high glucose environments.

RESULTS

A total of 3583 principle DEGs, that enriched immune-related GO terms and infection-related pathways were identified. CIBERSORT analysis showed that naive B cells, M2 macrophages, eosinophils, and neutrophil infiltration were significantly different. After intersecting 3583 DEGs, 168 DEIRGs and 181 module genes were identified. Furthermore, 15 hub genes, TYROBP, FCGR3A, CD163, FCGR2A, PTPRC, TLR2, CD14, VSIG4, HCK, CSF1R, LILRB2, ITGAM, CTSS, CD86, and LY86, were identified via PPI network. The identified hub genes were up-regulated in DR and showed a high DR diagnostic value. Regulatory networks of the miRNA- and TF-hub genes can help understand the etiology of disease at the genetic level and optimize treatment strategy. CD14, VSIG4, HCK, and CSF1R were verified to be highly expressed in the vitreous of patients with DR. n RF/6A, CSF1R, and p-ERK1/2 were significantly overexpressed under high glucose conditions, with a statistically significant difference.

CONCLUSION

This investigation identified 15 genes (TYROBP, FCGR3A, CD163, FCGR2A, PTPRC, TLR2, CD14, VSIG4, HCK, CSF1R, LILRB2, ITGAM, CTSS, CD86, and LY86) as hub DR genes, which may serve as a new potential point for the diagnosis and treatment of DR. CSF1R/p-ERK1/2 signaling may promotes the development of retinal neovascularization.

Real-World Study on Chai-Shi-Jie-Du Granules for the Treatment of Dengue Fever and the Possible Mechanisms Based on Network Pharmacology

Objectives

Traditional Chinese medicine (TCM) is a widely used method for treating dengue fever in China. TCM improves the symptoms of patients with dengue, but there is no standard TCM prescription for dengue fever. This real-world study aimed to evaluate the effects of Chai-Shi-Jie-Du (CSJD) granules for the treatment of dengue fever and the underlying mechanisms.

Methods

We implemented a multicenter real-world study, an in vitro assay and network pharmacology analysis. Patients from 5 hospitals in mainland China who received supportive western treatment in the absence or presence of CSJD were assigned to the control and CSJD groups between 1 August and 31 December 2019. Propensity score matching (PSM) was performed to correct for biases between groups. The clinical data were compared and analyzed. The antidengue virus activity of CSJD was tested in Syrian baby hamster kidney (BHK) cells using the DENV2-NGC strain. Network pharmacological approaches along with active compound screening, target prediction, and GO and KEGG enrichment analyses were used to explore the underlying molecular mechanisms.

Results

137 pairs of patients were successfully matched according to age, sex, and the time from onset to presentation. The time to defervescence (1.7 days vs. 2.5 days, P < 0.05) and the disease course (4.1 days vs. 6.1 days, P < 0.05) were significantly shorter in the CSJD group than those in the control group. CSJD showed no anti-DENV2-NGC virus activity in BHK cells. Network pharmacology analysis revealed 108 potential therapeutic targets, and the top GO and KEGG terms were related to immunity, oxidative stress response, and the response to lipopolysaccharide.

Conclusions

CSJD granules exhibit high potential for the treatment of dengue fever, and the therapeutic mechanisms involved could be related to regulating immunity, moderating the oxidative stress response, and the response to lipopolysaccharide.

Construction of predictive ceRNA network and identification of the patterns of immune cells infiltrated in Graves ophthalmopathy

OBJECTIVES

Graves' ophthalmopathy (GO) is a multifactorial disease, and the mechanism of non coding RNA interactions and inflammatory cell infiltration patterns are not fully understood. This study aims to construct a competing endogenous RNA (ceRNA) network for this disease and clarify the infiltration patterns of inflammatory cells in orbital tissue to further explore the pathogenesis of GO.

METHODS

The differentially expressed genes were identified using the GEO2R analysis tool. The Kyoto encyclopedia of genes and genomes (KEGG) and gene ontology analysis were used to analyze differential genes. RNA interaction relationships were extracted from the RNA interactome database. Protein-protein interactions were identified using the STRING database and were visualized using Cytoscape. StarBase, miRcode, and DIANA-LncBase Experimental v.2 were used to construct ceRNA networks together with their interacted non-coding RNA. The CIBERSORT algorithm was used to detect the patterns of infiltrating immune cells in GO using R software.

RESULTS

A total of 114 differentially expressed genes for GO and 121 pathways were detected using both the KEGG and gene ontology enrichment analysis. Four hub genes (SRSF6, DDX5, HNRNPC,and HNRNPM) were extracted from protein-protein interaction using cytoHubba in Cytoscape, 104 nodes and 142 edges were extracted, and a ceRNA network was identified (MALAT1-MIR21-DDX5). The results of immune cell analysis showed that in GO, the proportions of CD8+ T cells and CD4+ memory resting T cells were upregulated and downregulated, respectively. The proportion of CD4 memory resting T cells was positively correlated with the expression of MALAT1, MIR21, and DDX5.

CONCLUSIONS

This study has constructed a ceRNA regulatory network (MALAT1-MIR21-DDX5) in GO orbital tissue, clarifying the downregulation of the proportion of CD4+ stationary memory T cells and their positive regulatory relationship with ceRNA components, further revealing the pathogenesis of GO.

Construction of gene subgroups of Crohn disease based on transcriptome data

BACKGROUND

The global prevalence of Crohn disease (CD), a chronic inflammatory disease of the intestine, has been increasing; however, the etiology and pathogenesis of this disease have not been fully elucidated. Therefore, in the present study, we aimed to better understand the molecular mechanisms underlying CD to aid the development of novel therapeutic strategies for this condition.

METHODS

Based on the transcriptome data from patients with CD, this study used an unsupervised learning method to construct gene co-expression molecular subgroups and the R and SPSS software to identify the biological, clinical, and genetic characteristics and signatures of each subgroup.

RESULTS

Two subgroups were analyzed. Compared to subgroup II, subgroup I consisted of older patients with a more limited range of disease presentation and had a higher number of smokers. The specific genes associated with this subgroup, including CDKN2B, solute carrier family 22 member 5, and phytanoyl-CoA 2-hydroxylase, can be targeted for managing intestinal dysbacteriosis. The number of patients showing infiltrating lesions was higher, the number of smokers was lower, and CD severity was worse in patients in subgroup II than those in subgroup I. The specific genes relevant to subgroup II included cluster of differentiation 44, tryptophanyl-tRNA synthetase, and interleukin 10 receptor, alpha subunit, which may be related to viral infection.

CONCLUSION

The present study segregated patients with CD into 2 subgroups; the findings reported herein provide a new theoretical basis for the diagnosis and treatment of CD and could aid a thorough identification of potential therapeutic targets for this disease.

Clinical plasma cells-related genes to aid therapy in colon cancer

The tumor immune microenvironment (TIME) of colon cancer (CC) has been associated with extensive immune cell infiltration (IMI). Increasing evidence demonstrated that plasma cells (PC) have an extremely important role in advance of antitumor immunity. Nonetheless, there is a lack of comprehensive analyses of PC infiltration in clinical prognosis and immunotherapy in CC. This study systematically addressed the gene expression model and clinical information of CC patients. Clinical samples were obtained from the TCGA (The Cancer Genome Atlas) databases. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), GSVA, and the MAlignant Tumors using Expression data (ESTIMATE) algorithm were employed to research the potential mechanism and pathways. Immunophenoscore (IPS) was obtained to evaluate the immunotherapeutic significance of risk score. Half maximal inhibitory concentration (IC50) of chemotherapeutic medicine was predicted by employing the pRRophetic algorithm. A total of 513 CC samples (including 472 tumor samples and 41 normal samples) were collected from the TCGA-GDC database. Significant black modules and 313 candidate genes were considered PC-related genes by accessing WGCNA. Five pivotal genes were established through multiple analyses, which revealed excellent prognostic. The underlying correlation between risk score with tumor mutation burden (TMB) was further explored. In addition, the risk score was obviously correlated with various tumor immune microenvironment (TIME). Also, risk CC samples showed various signaling pathways activity and different pivotal sensitivities to administering chemotherapy. Finally, the biological roles of the CD177 gene were uncovered in CC.

iRHOM2 regulates inflammation and endothelial barrier permeability via CX3CL1

Acute lung injury (ALI) is associated with increased lung inflammation and lung permeability. The present study aimed to determine the role of inactive rhomboid-like protein 2 (iRHOM2) in ALI in lipopolysaccharide (LPS)-induced pulmonary microvascular endothelial cell model. Human pulmonary microvascular endothelial cells (HPMVECs) were transfected with small interfering RNA targeting iRHOM2 and C-X3-C motif chemokine ligand 1 (CX3CL1) overexpression plasmids and treated with LPS. Cell viability was detected using a Cell Counting Kit-8 assay, while levels of TNFα, IL-1β, IL-6 and p65 were measured by reverse transcription-quantitative PCR and western blotting. Apoptosis levels were measured using a TUNEL assay. Endothelial barrier permeability was detected, followed by analysis of zonula occludens-1, vascular endothelial-cadherin and occludin by immunofluorescence staining or western blotting. The interaction of iRHOM2 and CX3CL1 was analyzed using an immune-coprecipitation assay. Through bioinformatics analysis, it was found that CX3CL1 was upregulated in the LPS group compared with the control. Kyoto Encyclopedia of Genes and Genomes pathway analysis demonstrated that the TNF signaling pathway affected by iRHOM2 and cytokine-cytokine receptor interaction, including CX3CL1, served a key role in ALI. HPMVECs treated with LPS exhibited a decrease in cell viability and an increase in inflammation, apoptosis and endothelial barrier permeability, while these effects were reversed by iRHOM2 silencing. However, CX3CL1 overexpression inhibited the effects of iRHOM2 silencing on LPS-treated HPMVECs. The present study demonstrated a novel role of iRHOM2 as a regulator that affects inflammation, apoptosis and endothelial barrier permeability; this was associated with CX3CL1.

Identification of immunodiagnostic blood biomarkers associated with spinal cord injury severity

Blood always shows some immune changes after spinal cord injury (SCI), and detection of such changes in blood may be helpful for diagnosis and treatment of SCI. However, studies to date on blood immune changes after SCI in humans are not comprehensive. Therefore, to obtain the characteristics of blood immune changes and immunodiagnostic blood biomarkers of SCI and its different grades, a human blood transcriptome sequencing dataset was downloaded and analyzed to obtain differentially expressed immune-related genes (DEIGs), related functions and signaling pathways related to SCI and its various grades. Characteristic biomarkers of SCI and its different grades were identified by using weighted gene coexpression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) logistic regression. Expression of biomarkers was verified through experiments. The area under the curve (AUC) of biomarkers was calculated to evaluate their diagnostic value, and differences in immune cell content were examined. In this study, 17 kinds of immune cells with different contents between the SCI group and healthy control (HC) group were identified, with 7 immune cell types being significantly increased. Differences in the content of immune cells between different grades of SCI and the HC group were also discovered. DEIGs were identified, with alteration in some immune-related signaling pathways, vascular endothelial growth factor signaling pathways, and axon guidance signaling pathways. The SCI biomarkers identified and those of American Spinal Injury Society Impairment Scale (AIS) A and AIS D of SCI have certain diagnostic sensitivity. Analysis of the correlation of immune cells and biomarkers showed that biomarkers of SCI, AIS A grade and AIS D grade correlated positively or negatively with some immune cells. CKLF, EDNRB, FCER1G, SORT1, and TNFSF13B can be used as immune biomarkers for SCI. Additionally, GDF11and HSPA1L can be used as biomarkers of SCI AIS A grade; PRKCA and CMTM2 can be used as biomarkers of the SCI AIS D grade. Detecting expression of these putative biomarkers and changes in related immune cells may be helpful for predicting the severity of SCI.

Kaempferol has potential anti-coronavirus disease 2019 (COVID-19) targets based on bioinformatics analyses and pharmacological effects on endotoxin-induced cytokine storm

COVID-19 has infected 272 million patients and caused 5.33 million deaths around the world, and it remains the main global threat. Previous studies revealed that Chinese traditional medicine is an effective treatment for COVID-19 infection. This study aims to reveal the pharmacological effects of kaempferol, which is the active component of Radix Bupleuri and Tripterygii Radix, and potential mechanisms for the treatment of COVID-19. Here, we employed the bioinformatics methods to filter the anti-COVID-19 candidate genes of kaempferol, which mainly enriched in inflammation (TNF, JUN, etc.) and virus infection (AKT1, JNK, etc.). The Transcription levels of AKT1, JNK and JUN were significantly reduced by kaempferol treatment in the LPS-activated macrophages. In addition, kaempferol reduced the secretion of inflammatory factors by LPS-stimulated macrophages, inhibited MAPK/NF-κB signaling and regulated macrophage polarization to M2 type in vitro, and suppressed endotoxin-induced cytokine storm and improved survival in mice. Molecular docking analysis demonstrated that kaempferol was probable to bind the COVID-19 protein 5R84 and formatted hydrogen bond with the residues, the free binding energy of which was lower than the original ligand. In summary, our current work indicates that kaempferol has anti-COVID-19 potential through the reduction of COVID-19-induced body dysfunction and molecule-protein interaction, and bioinformatics results clarify that some of these key target genes might serve as potential molecular markers for detecting COVID-19.

Copper Death Inducer, FDX1, as a Prognostic Biomarker Reshaping Tumor Immunity in Clear Cell Renal Cell Carcinoma

BACKGROUND

Progress in the diagnosis and treatment of clear cell renal cell carcinoma (ccRCC) has significantly prolonged patient survival. However, ccRCC displays an extreme heterogenous characteristic and metastatic tendency, which limit the benefit of targeted or immune therapy. Thus, identifying novel biomarkers and therapeutic targets for ccRCC is of great importance.

METHOD

Pan cancer datasets, including the expression profile, DNA methylation, copy number variation, and single nucleic variation, were introduced to decode the aberrance of copper death regulators (CDRs). Then, FDX1 was systematically analyzed in ccRCC to evaluate its impact on clinical characteristics, prognosis, biological function, immune infiltration, and therapy response. Finally, in vivo experiments were utilized to decipher FDX1 in ccRCC malignancy and its role in tumor immunity.

RESULT

Copper death regulators were identified at the pancancer level, especially in ccRCC. FDX1 played a protective role in ccRCC, and its expression level was significantly decreased in tumor tissues, which might be regulated via CNV events. At the molecular mechanism level, FDX1 positively regulated fatty acid metabolism and oxidative phosphorylation. In addition, FDX1 overexpression restrained ccRCC cell line malignancy and enhanced tumor immunity by increasing the secretion levels of IL2 and TNFγ.

CONCLUSIONS

Our research illustrated the role of FDX1 in ccRCC patients' clinical outcomes and its impact on tumor immunity, which could be treated as a promising target for ccRCC patients.

Identification of Oxidative Stress-Related Biomarkers in Diabetic Kidney Disease

Background

Diabetic kidney disease (DKD) is a leading cause of end-stage renal disease throughout the world. In kidney disease, oxidative stress has been linked to both antioxidant depletions and increased reactive oxygen species (ROS) production. Thus, the objective of this study was to identify biomarkers related to oxidative stress in DKD.

Methods

The gene expression profile of the DKD was extracted from the Gene Expression Omnibus (GEO) database. The identification of the differentially expressed genes (DEGs) was performed using the "limma" R package, and weighted gene coexpression network analysis (WGCNA) was used to find the gene modules that were most related to DKD. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed using "Org.Hs.eg.db" R package. The protein-protein interaction (PPI) network was constructed using the STRING database. The hub genes were identified by the Molecular Complex Detection (MCODE) plug-in of Cytoscape software. The diagnostic capacity of hub genes was verified using the receiver operating characteristic (ROC) curve. Correlations between diagnostic genes were analyzed using the "corrplot" package. In addition, the miRNA gene transcription factor (TF) network was used to explain the regulatory mechanism of hub genes in DKD.

Results

DEGs analysis and WGCNA-identified 160 key genes were identified in DKD patients. Among them, nine oxidative stress-related genes were identified as candidate hub genes for DKD. Using the PPI network, five hub genes, NR4A2, DUSP1, FOS, JUN, and PTGS2, were subsequently identified. All the hub genes were downregulated in DKD and had a high diagnostic value of DKD. The regulatory mechanism of hub genes was analyzed from the miRNA gene-TF network.

Conclusion

Our study identified NR4A2, DUSP1, FOS, JUN, and PTGS2 as hub genes of DKD. These genes may serve as potential therapeutic targets for DKD patients.

Vitamin D protects silica particles induced lung injury by promoting macrophage polarization in a KLF4-STAT6 manner

Silicosis is one of the severest occupational diseases worldwide, manifesting as infiltration of inflammatory cells, excessive secretion of pro-inflammatory mediators and pulmonary diffuse fibrosis. Macrophages polarization to M2 is one of the major strategies that attenuates inflammatory response. Our previous study found that vitamin D could protect against silica-induced lung injury by damping the secretion of pro-inflammatory cytokines. Here we further identified that vitamin D attenuated silica particles-induced lung inflammation by regulating macrophage polarization in a KLF4-STAT6 manner. Myeloid-specific Stat6 knockout (cKO) mice were generated for in vivo studies. Primary macrophages purified from bronchoalveolar lavage fluid (BALF) of wildtype or Stat6 cKO mice and differentiated THP-1 cells were used for in vitro studies. Vitamin D was found to promote alveolar macrophage polarizing to M2 phenotype through the STAT6 signaling pathway, as demonstrated by worse lung inflammation and ablated protection of vitamin D in silica particles-instilled Stat6 cKO mice. Mechanismly, vitamin D upregulated KLF4 expression in the alveolar macrophage, which synergistically activated STAT6. Additionally, KLF4 was found to upregulate macrophages autophagy, which protected them from silica particles-induced oxidative stress and cell apoptosis. The protective effects of vitamin D were dismissed by silencing KLF4. Our study demonstrates the potential mechanism of vitamin D-mediated macrophage polarization and reveals the therapeutic application of vitamin D in inflammatory disease.

EPM2A acts as a protective factor in prostate cancer, evidence from a real-world patient cohort

EPM2A encodes a dual specificity phosphatase and has been proven to be a potential biomarker in several cancers but has not been mentioned in prostate cancer (PCA). We investigated the prognostic and therapeutic value of EPM2A in PCA. The TCGA-PRAD cohort was collected to evaluate the differential expression, prognostic value, immunocyte infiltration and drug sensitivity of EPM2A in PCA. We constructed a nomogram model to predict the recurrence probability for PCA patients. Immunohistochemistry was used to validate the different transcript levels of EPM2A between tumor and normal tissues. A real-world AHMU-PC cohort was employed for validation. The results showed decreased expression of EPM2A in 95.65% of tumor tissues and was related to their prognosis, especially PCA (p = 0.008, HR = 0.57, 95% CI: 0.371–0.863). Further multiple analysis by adjusting clinical features revealed that EPM2A acted as an independent prognostic factor (p = 0.014, HR = 0.589, 95% CI: 0.386–0.898). Pathway enrichment analysis showed variable signaling activation between high EPM2A expression patients (HEXP) and low EPM2A expression patients (LEXP). The HEXP group contained higher infiltration of immunocytes than the LEXP group, as well as high levels of PD-1, PD-L1 and PD-L2, while LEXP patients were more sensitive to cisplatin, paclitaxel and bicalutamide therapy. The nomogram containing the EPM2A group, T stage and Gleason score showed a preferable prognostic value (AUC = 0.755; Hosmer‒Lemeshow, p = 0.486). In validation, we confirmed the lower transcript level of EPM2A in PCA than in normal tissues (120.5 ± 2.159 vs. 138.3 ± 1.83, p = 0.035) and correlated it with the expression level of PD-1 (R = 0.283). Among the 66 patients from the AHMU-PC cohort, we further validated the function of EPM2A in PCA patients. HEXP patients had longer recurrence-free survival times (1207 ± 110 vs. 794.2 ± 97.02, p = 0.0063) and favorable prognoses (HR: 0.417, 95% CI: 0.195–0.894, p = 0.0245). Collectively, we identified the prognostic value of EPM2A in PCa via a bioinformatics method. Patients with higher EPM2A may be more sensitive to immunotherapy, and patients with lower EPM2A were more suitable for bicalutamide, cisplatin and paclitaxel therapy.

Identification of hub genes related to the innate immune response activated during spinal cord injury

Spinal cord injury (SCI) often leads to sensory and motor dysfunction. Two major factors that hinder spinal cord repair are local inflammation and glial scar formation after SCI, and thus appropriate immunotherapy may alleviate damage. To characterize changes in gene expression that occur during SCI and thereby identify putative targets for immunotherapy, here we analyzed the dataset GSE5296 (containing one control group and six SCI groups at different timepoints) to identify differentially-expressed genes. Functional enrichment analysis was performed and a protein-protein interaction network was created to identify possible hub genes. Finally, we performed quantitative PCR to verify changes in gene expression. The CIBERSORT algorithm was used to analyze innate immune cell infiltration patterns. The dataset GSE162610 (containing one control group and three SCI groups at different timepoints) was analyzed to evaluate innate immune cell infiltration at the single-cell level. The dataset GSE151371 (containing one control group [n = 10] and an SCI group [n = 38]) was used to detect the expression of hub genes in the blood from SCI patients. Differentially-expressed innate immune-related genes at each timepoint were identified, and the functions and related signaling pathways of these genes were examined. Six hub genes were identified and verified. We then analyzed the expression characteristics of these hub genes and characteristics of innate immune infiltration in SCI; finally, we examined ligand expression in the context of the CCL signaling pathway and COMPLEMENT signaling pathway networks. This study reveals the characteristics of innate immune cell infiltration and temporal expression patterns of hub genes, and may aid in the development of immunotherapies for SCI.

Single-cell quantitative proteomic analysis of human oocyte maturation revealed high heterogeneity in in vitro matured oocytes

Oocyte maturation is pertinent to the success of in vitro maturation (IVM), which is used to overcome female infertility, and produced over 5000 live births worldwide. However, the quality of human IVM oocytes has not been investigated at single-cell proteome level. Here, we quantified 2094 proteins in human oocytes during in vitro and in vivo maturation (IVO) by single-cell proteomic analysis and identified 176 differential proteins between IVO and germinal vesicle oocytes and 45 between IVM and IVO oocytes including maternal effect proteins, with potential contribution to the clinically observed decreased fertilization, implantation, and birth rates using human IVM oocytes. IVM and IVO oocytes showed separate clusters in principal component analysis, with higher inter-cell variability among IVM oocytes, and have little correlation between mRNA and protein changes during maturation. The patients with the most aberrantly expressed proteins in IVM oocytes had the lowest level of estradiol per mature follicle on trigger day. Our data provide a rich resource to evaluate effect of IVM on oocyte quality and study mechanism of oocyte maturation.

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Single-cell proteomic profiling of human oocytes matured in vitro and in vivo.

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Low correlation between protein and mRNA levels during human oocyte maturation.

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In vitro matured (IVM) oocytes exhibit higher heterogeneity at the proteome level.

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45 differentially expressed proteins between IVM and in vivo matured (IVO) oocytes.

Bioinformatics-Based Approach for Exploring the Immune Cell Infiltration Patterns in Alzheimer's Disease and Determining the Intervention Mechanism of Liuwei Dihuang Pill

Traditional Chinese medicine (TCM) compounds have recently garnered attention for the regulation of immune cell infiltration and the prevention and treatment of Alzheimer's disease (AD). The Liuwei Dihuang Pill (LDP) has potential in this regard; however, its specific molecular mechanism currently remains unclear. Therefore, we adopted a bioinformatics approach to investigate the infiltration patterns of different types of immune cells in AD and explored the molecular mechanism of LDP intervention, with the aim of providing a new basis for improving the clinical immunotherapy of AD patients. We found that M1 macrophages showed significantly different degrees of infiltration between the hippocampal tissue samples of AD patients and healthy individuals. Four immune intersection targets of LDP in the treatment of AD were identified; they were enriched in 206 biological functions and 30 signaling pathways. Quercetin had the best docking effect with the core immune target PRKCB. Our findings suggest that infiltrated immune cells may influence the course of AD and that LDP can regulate immune cell infiltration through multi-component, multi-target, and multi-pathway approaches, providing a new research direction regarding AD immunotherapy.

Development and Validation of a Prognostic Classifier Based on Lipid Metabolism-Related Genes for Breast Cancer

Background

The changes of lipid metabolism have been implicated in the development of many tumors, but its role in breast invasive carcinoma (BRCA) remains to be fully established. Here, we attempted to ascertain the prognostic value of lipid metabolism-related genes in BRCA.

Methods

We obtained RNA expression data and clinical information for BRCA and normal samples from public databases and downloaded a lipid metabolism-related gene set. Ingenuity Pathway Analysis (IPA) was applied to identify the potential pathways and functions of Differentially Expressed Genes (DEGs) related to lipid metabolism. Subsequently, univariate and multivariate Cox regression analyses were utilized to construct the prognostic gene signature. Functional enrichment analysis of prognostic genes was achieved by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Kaplan-Meier analysis, Receiver Operating Characteristic (ROC) curves, clinical follow-up results were employed to assess the prognostic potency. Potential compounds targeting prognostic genes were screened by Connectivity Map (CMap) database and a prognostic gene-drug interaction network was constructed using Comparative Toxicogenomics Database (CTD). Furthermore, we separately validated the selected marker genes in BRCA samples and human breast cancer cell lines (MCF-7, MDA-MB-231).

Results

IPA and functional enrichment analysis demonstrated that the 162 lipid metabolism-related DEGs we obtained were involved in many lipid metabolism and BRCA pathological signatures. The prognostic classifier we constructed comprising SDC1 and SORBS1 can serve as an independent prognostic marker for BRCA. CMap filtered 37 potential compounds against prognostic genes, of which 16 compounds could target both two prognostic genes were identified by CTD. The functions of the two prognostic genes in breast cancer cells were verified by cell function experiments.

Conclusion

Within this study, we identified a novel prognostic classifier based on two lipid metabolism-related genes: SDC1 and SORBS1. This result highlighted a new perspective on the metabolic exploration of BRCA.

PCMT1 Is a Potential Prognostic Biomarker and Is Correlated with Immune Infiltrates in Breast Cancer

Background

Protein-L-isoaspartate (D-aspartate) O-methyltransferase (PCMT1) is involved in the occurrence and development of a variety of malignant tumors. However, the prognostic value of PCMT1 in breast cancer remains unclear.

Methods

Based on the Cancer Genome Atlas database, we assessed the correlation between the expression of PCMT1 and prognosis, immune invasion, and tumor mutation burden in a variety of cancers. The expression level, mutation, immune correlation, and coexpression of PCMT1 in breast cancer were studied using the following databases: UALCAN database, Human Protein Atlas database, cBioPortal database, TIMER database, and LinkedOmics database. Kaplan–Meier Plotter was used for survival analysis. Receiver operating characteristic (ROC) curves and nomograms were drawn using the R software package. P < 0.05 was considered statistically significant.

Results

Pancancer analysis showed that PCMT1 is highly expressed in a variety of cancers and is significantly related to the prognosis of a variety of cancers. PCMT1 is significantly related to the tumor mutation burden of a variety of cancers. PCMT1 is significantly high in breast cancer, and it is significantly related to the abundance of immune infiltration. Survival analysis revealed that high PCMT1 expression is significantly associated with shorter overall survival (OS), relapse-free survival (RFS), and postprogression survival (PPS) in breast cancer patients. ROC curves and nomograms verify the effectiveness of PCMT1 as a prognostic biomarker for breast cancer.

Conclusions

PCMT1 can be used as a potential prognostic biomarker of breast cancer, and it is significantly related to the abundance of breast cancer immune infiltration.

Molecular Characterization, Tumor Microenvironment Association, and Drug Susceptibility of DNA Methylation-Driven Genes in Renal Cell Carcinoma

Accumulating evidence suggests that DNA methylation has essential roles in the development of renal cell carcinoma (RCC). Aberrant DNA methylation acts as a vital role in RCC progression through regulating the gene expression, yet little is known about the role of methylation and its association with prognosis in RCC. The purpose of this study is to explore the DNA methylation-driven genes for establishing prognostic-related molecular clusters and providing a basis for survival prediction. In this study, 5,198 differentially expressed genes (DEGs) and 270 DNA methylation-driven genes were selected to obtain 146 differentially expressed DNA methylation-driven genes (DEMDGs). Two clusters were distinguished by consensus clustering using 146 DEMDGs. We further evaluated the immune status of two clusters and selected 106 DEGs in cluster 1. Cluster-based immune status analysis and functional enrichment analysis of 106 DEGs provide new insights for the development of RCC. To predict the prognosis of patients with RCC, a prognostic model based on eight DEMDGs was constructed. The patients were divided into high-risk groups and low-risk groups based on their risk scores. The predictive nomogram and the web-based survival rate calculator (http://127.0.0.1:3496) were built to validate the predictive accuracy of the prognostic model. Gene set enrichment analysis was performed to annotate the signaling pathways in which the genes are enriched. The correlation of the risk score with clinical features, immune status, and drug susceptibility was also evaluated. These results suggested that the prognostic model might be a promising prognostic tool for RCC and might facilitate the management of patients with RCC.

Identification of Survival-Specific Genes in Clear Cell Renal Cell Carcinoma Using a Customized Next-Generation Sequencing Gene Panel

Purpose: Although mutations are associated with carcinogenesis, little is known about survival-specific genes in clear cell renal cell carcinoma (ccRCC). We developed a customized next-generation sequencing (NGS) gene panel with 156 genes. The purpose of this study was to investigate whether the survival-specific genes we found were present in Korean ccRCC patients, and their association with clinicopathological findings. Materials and Methods: DNA was extracted from the formalin-fixed, paraffin-embedded tissue of 22 ccRCC patients. NGS was performed using our survival-specific gene panel with an Illumina MiSeq. We analyzed NGS data and the correlations between mutations and clinicopathological findings and also compared them with data from the Cancer Genome Atlas-Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) and Renal Cell Cancer-European Union (RECA-EU). Results: We found a total of 100 mutations in 37 of the 156 genes (23.7%) in 22 ccRCC patients. Of the 37 mutated genes, 11 were identified as clinicopathologically significant. Six were novel survival-specific genes (ADAMTS10, CARD6, NLRP2, OBSCN, SECISBP2L, and USP40), and five were top-ranked mutated genes (AKAP9, ARID1A, BAP1, KDM5C, and SETD2). Only CARD6 was validated as an overall survival-specific gene in this Korean study (p = 0.04, r = −0.441), TCGA-KIRC cohort (p = 0.0003), RECA-EU (p = 0.0005). The 10 remaining gene mutations were associated with clinicopathological findings; disease-free survival, mortality, nuclear grade, sarcomatoid component, N-stage, sex, and tumor size. Conclusions: We discovered 11 survival-specific genes in ccRCC using data from TCGA-KIRC, RECA-EU, and Korean patients. We are the first to find a correlation between CARD6 and overall survival in ccRCC. The 11 genes, including CARD6, NLRP2, OBSCN, and USP40, could be useful diagnostic, prognostic, and therapeutic markers in ccRCC.

Identification of a five-miRNA signature as a novel potential prognostic biomarker in patients with nasopharyngeal carcinoma

Background

MicroRNAs (miRNAs) are involved in the prognosis of nasopharyngeal carcinoma (NPC). This study used clinical data and expression data of miRNAs to develop a prognostic survival signature for NPC patients to detect high-risk subject.

Results

We identified 160 differentially expressed miRNAs using RNA-Seq data from the GEO database. Cox regression model consisting of hsa-miR-26a, hsa-let-7e, hsa-miR-647, hsa-miR-30e, and hsa-miR-93 was constructed by the least absolute contraction and selection operator (LASSO) in the training set. All the patients were classified into high-risk or low-risk groups by the optimal cutoff value of the 5-miRNA signature risk score, and the two risk groups demonstrated significant different survival. The 5-miRNA signature showed high predictive and prognostic accuracies. The results were further confirmed in validation and external validation set. Results from multivariate Cox regression analysis validated 5-miRNA signature as an independent prognostic factor. A total of 13 target genes were predicted to be the target genes of miRNA target genes. Both PPI analysis and KEGG analysis networks were closely related to tumor signaling pathways. The prognostic model of mRNAs constructed using data from the dataset GSE102349 had higher AUCs of the target genes and higher immune infiltration scores of the low-risk groups. The mRNA prognostic model also performed well on the independent immunotherapy dataset Imvigor210.

Conclusions

This study constructed a novel 5-miRNA signature for prognostic prediction of the survival of NPC patients and may be useful for individualized treatment of NPC patients.

Identification of Hub Genes and Immune Cell Infiltration Characteristics in Alzheimer's Disease

The purpose of this study was to identify hub genes closely correlated with Alzheimer's disease (AD) and their association with immune cell infiltration. In this work, 119 overlapping differentially expressed genes (DEGs) were obtained from GSE5281 and GSE122063 datasets through differential expression analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the 119 DEGs, revealing some important biological functions and key pathways. AD immune cell infiltration analysis revealed a significant difference in the proportion of immune cells between the AD group and the control group. Finally, correlation analysis between target hub genes and immune cells indicated that GFAP had a positive or negative correlation with some specific immune cells. Our results provided useful clues, which will help to explain the molecular mechanism of AD and search for precise prognostic markers and potential therapeutic targets.

Upregulation of autophagy in M2 macrophage by vitamin D alleviates crystalline silica-induced pulmonary inflammatory damage

Crystalline silica (CS) is a universal environmental pollutant, which causes a typical inflammatory lung injury. Vitamin D shows huge potential against particles-induced lung injury, while little known about the molecular mechanism involved in macrophage autophagy. In this study, we aim to identify the protective effects of vitamin D on CS caused lung inflammatory injury and clarify the detail mechanism. After exposure to CS (3 mg/mice in 50 μl PBS), wildtype and Atg7^flox/flox Lyz2-cre mice were treated with or without vitamin D₃ (40,000 IU/kg). The results indicated that exposure to CS caused an obvious lung injury, manifesting as pathological structural changes, macrophage-dominated inflammatory cell infiltration and increased pro-inflammatory cytokines. Remarkably, these damages were more serious in Atg7^flox/flox Lyz2-cre mice. Vitamin D was found to inverse CS-induced inflammatory cell infiltration and restored anti-inflammatory M2 macrophages by inducing autophagy, which attenuated lung injury, as determined by decreased levels of apoptosis and inflammatory response. While, this effects of vitamin D were slashed in Atg7^flox/flox Lyz2-cre mice. This study reveals the adverse effect of CS on lung tissue and the protective mechanism of vitamin D involved in M2 macrophages autophagy, which attenuates CS-caused lung injury.

Regulation of decorin by ursolic acid protects against non-alcoholic steatohepatitis

Non-alcoholic steatohepatitis (NASH) has become a global health issue, which poses additional financial burden to public health care. However, no specific pharmacological therapy is recommended in current guidelines. Ursolic acid (UA) has been proven to perform multiple biological activities, thereby having a broad application prospect in healthcare field. Thus, this current research was conducted to investigate the protective mechanisms of UA on NASH. Integrative genomic analyses were performed to identify characteristic genes for NASH, and human proteomics chip was applied to seek out differentially binding proteins for UA. The combining bioinformatic analyses revealed 529 and 502 differentially expressed genes for NASH and UA, respectively. And further enrichment analyses indicated that IGF-IR signaling pathway was intimately involved in the therapeutic effects of UA on NASH. Experimental studies displayed that UA up-regulated the decorin expression to activate IGF-IR signaling as well as to inhibit HIF-1 signaling, resulting in alleviation on metabolic dysfunction, liver steatosis, inflammation and hypoxia in high-fat-fed mice. And additionally, these results were confirmed by lipotoxic and decorin-interference cell model. Taken together, we found that UA could regulate IGF-IR and HIF-1 signaling pathways via decorin to provide dual protective functions on metabolic dysfunction and liver hypoxia, and therefore turned to be an effective option for the treatment of NASH.

Expression, prognosis value, and immune infiltration of lncRNA ASB16-AS1 identified by pan-cancer analysis

Long non-coding RNA known as ASB16 antisense RNA1 (ASB16-AS1) has been proven to be an oncogene, and the relationship between ASB16-AS1 and immunity is still under studied. This study aims to explore the expression and prognostic potential of ASB16-AS1, and to visualize the relationship between ASB16-AS1 expression and immune infiltration in pan-cancer analysis. We clarified ASB16-AS1 expression patterns and its relationship with prognosis through multi-platform and multi-database sources. We also verified the function of ASB16-AS1 in liver hepatocellular carcinoma (LIHC). A  variety of immune cell content evaluation methods were used to mutually verify the correlation between ASB16-AS1 and immune infiltration. Finally, the relationships between ASB16-AS1 and molecular characteristics were further explored. In terms of comprehensive analysis, compared with non-tumor tissues, ASB16-AS1 was highly expressed in tumor tissues, and indicated the value of poor prognosis in multiple cancer types. Functional assays, such as counting kit-8 assay, transwell assay and scratch-wound assay verified that high ASB16-AS1 expression promoted tumor progression in LIHC. ASB16-AS1 was positively correlated with B cells, T cells CD4+ and T cells CD8+ in most cancer types, and negatively correlated with macrophages, dendritic cells and neutrophils in some cancer types. In addition, there were different interaction modes between ASB16-AS1 and molecular features, such as the relationship with oncogenic signaling pathways, showing that the high ASB16-AS1 expression was related to alterations in oncogenic signaling pathways. Our study emphasizes that ASB16-AS1 is a potential pan-cancer prognostic marker, whichs is associated with the immune infiltration in multiple cancer types.

A novel prognostic cancer-related lncRNA signature in papillary renal cell carcinoma

Background

Papillary renal cell carcinoma (pRCC) ranks second in renal cell carcinoma and the prognosis of pRCC remains poor. Here, we aimed to screen and identify a novel prognostic cancer-related lncRNA signature in pRCC.

Methods

The RNA-seq profile and clinical feature of pRCC cases were downloaded from TCGA database. Significant cancer-related lncRNAs were obtained from the Immlnc database. Differentially expressed cancer-related lncRNAs (DECRLs) in pRCC were screened for further analysis. Cox regression report was implemented to identify prognostic cancer-related lncRNAs and establish a prognostic risk model, and ROC curve analysis was used to evaluate its precision. The correlation between RP11-63A11.1 and clinical characteristics was further analyzed. Finally, the expression level and role of RP11-63A11.1 were studied in vitro.

Results

A total of 367 DECRLs were finally screened and 26 prognostic cancer-related lncRNAs were identified. Among them, ten lncRNAs (RP11-573D15.8, LINC01317, RNF144A-AS1, TFAP2A-AS1, LINC00702, GAS6-AS1, RP11-400K9.4, LUCAT1, RP11-63A11.1, and RP11-156L14.1) were independently associated with prognosis of pRCC. These ten lncRNAs were incorporated into a prognostic risk model. In accordance with the median value of the riskscore, pRCC cases were separated into high and low risk groups. Survival analysis indicated that there was a significant difference on overall survival (OS) rate between the two groups. The area under curve (AUC) in different years indicated that the model was of high efficiency in prognosis prediction. RP11-63A11.1 was mainly expressed in renal tissues and it correlated with the tumor stage, T, M, N classifications, OS, PFS, and DSS of pRCC patients. Consistent with the expression in pRCC tissue samples, RP11-63A11.1 was also down-regulated in pRCC cells. More importantly, up-regulation of RP11-63A11.1 attenuated cell survival and induced apoptosis.

Conclusions

Ten cancer-related lncRNAs were incorporated into a powerful model for prognosis evaluation. RP11-63A11.1 functioned as a cancer suppressor in pRCC and it might be a potential therapeutic target for treating pRCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02247-6.

A construction and comprehensive analysis of ceRNA networks and infiltrating immune cells in papillary renal cell carcinoma

Background

As the second most common malignancy in adults, papillary renal cell carcinoma (PRCC) has shown an increasing trend in both incidence and mortality. Effective treatment for advanced metastatic PRCC is still lacking. In this study, we aimed to establish competitive endogenous RNA (ceRNA) networks related to PRCC tumorigenesis, and analyze the specific role of differentially expressed ceRNA components and infiltrating immune cells in tumorigenesis.

Methods

CeRNA networks were established to identify the key ceRNAs related to PRCC tumorigenesis based on the 318 samples from The Cancer Genome Atlas database (TCGA), including 285 PRCC and 33 normal control samples. The R package, “CIBERSORT,” was used to evaluate the infiltration of 22 types of immune cells. Then we identified the significant ceRNAs and immune cells, based on which two nomograms were obtained for predicting the prognosis in PRCC patients. Finally, we investigated the co‐expression of PRCC‐specific immune cells and core ceRNAs via Pearson correlation test.

Results

COL1A1, H19, ITPKB, LDLR, TCF4, and WNK3 were identified as hub genes in ceRNA networks. Four prognostic‐related tumor‐infiltrating immune cells, including T cells CD4 memory resting, Macrophages M1, and Macrophages M2 were revealed. Pearson correlation test indicated that Macrophage M1 was negatively related with COL1A1 (p < 0.01) and LDLR (p < 0.01), while Macrophage M2 was positively related with COL1A1 (p < 0.01), TCF4 (p < 0.01), and H19 (p = 0.032). Two nomograms were conducted with favorable accuracies (area under curve of 1‐year survival: 0.935 and 0.877; 3‐year survival: 0.849 and 0.841; and 5‐year survival: 0.818 and 0.775, respectively).

Conclusion

The study constructed two nomograms suited for PRCC prognosis predicting. Moreover, we concluded that H19‐miR‐29c‐3p‐COL1A1 axis might promote the polarization of M2 macrophages and inhibit M1 macrophage activation through Wnt signaling pathway, collaborating to promote PRCC tumorigenesis and lead to poor overall survival of PRCC patients.

Bio-informatics and in Vitro Experiments Reveal the Mechanism of Schisandrin A Against MDA-MB-231 cells

Schisandrin A (SchA) has been reported to have good anti-cancer effects. However, its anti-cancer mechanism in breast cancer remains unknown. This study aimed to explore the mechanism of SchA in breast cancer treatment using bio-informatics analysis and in vitro experiments. The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Gene Cards, and PharmMapper databases were used to screen the candidate targets of SchA against MDA-MB-231 cells selected as the tested cell line through MTT analysis. The functions and pathways of the targets were identified using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and further analyzed using DAVID 6.8.1 database. Network pharmacology analysis revealed 77 candidate targets, 31 signal pathways, and 208 GO entries (P < 0.05). The targets regulated serine-type endopeptidase and protein tyrosine kinase activities, thereby promoting the migration and inhibiting the apoptosis of MDA-MB-231 cells. Comprehensive analysis of the ‘Protein–Protein Interaction’ (PPI) and ‘Component-Targets-Pathways’ (C-T-P) networks constructed using Cytoscape 3.7.1 software revealed four core targets: EGFR, PIK3R1, MMP9 and Caspase 3. Their docking scores with SchA were subsequently investigated through molecular docking. The wound healing, Hoechst 33342/PI, and western blot assays confirmed that SchA significantly down-regulated EGFR, PIK3R1, and MMP9, but up-regulated cleaved-caspase 3, thus inhibiting the migration and promoting the apoptosis of MDA-MB-231 cells. Reckoning the findings of the study, SchA is a potential adjuvant treatment for breast cancer.

Obscurin: A multitasking giant in the fight against cancer

Giant obscurins (720-870 kDa), encoded by OBSCN, were originally discovered in striated muscles as cytoskeletal proteins with scaffolding and regulatory roles. Recently though, they have risen to the spotlight as key players in cancer development and progression. Herein, we provide a timely prudent synopsis of the expanse of OBSCN mutations across 16 cancer types. Given the extensive work on OBSCN's role in breast epithelium, we summarize functional studies implicating obscurins as potent tumor suppressors in breast cancer and delve into an in silico analysis of its mutational profile and epigenetic (de)regulation using different dataset platforms and sophisticated computational tools. Lastly, we formally describe the OBSCN-Antisense-RNA-1 gene, which belongs to the long non-coding RNA family and discuss its potential role in modulating OBSCN expression in breast cancer. Collectively, we highlight the escalating involvement of obscurins in cancer biology and outline novel potential mechanisms of OBSCN (de)regulation that warrant further investigation.

De novo generation of macrophage from placenta-derived hemogenic endothelium

Macrophages play pivotal roles in immunity, hematopoiesis, and tissue homeostasis. In mammals, macrophages have been shown to originate from yolk-sac-derived erythro-myeloid progenitors and aorta-gonad-mesonephros (AGM)-derived hematopoietic stem cells. However, whether macrophages can arise from other embryonic sites remains unclear. Here, using single-cell RNA sequencing, we profile the transcriptional landscape of mouse fetal placental hematopoiesis. We uncover and experimentally validate that a CD44⁺ subpopulation of placental endothelial cells (ECs) exhibits hemogenic potential. Importantly, lineage tracing using the newly generated Hoxa13 reporter line shows that Hoxa13-labeled ECs can produce placental macrophages, named Hofbauer cell (HBC)-like cells. Furthermore, we identify two subtypes of HBC-like cells, and cell-cell interaction analysis identifies their potential roles in angiogenesis and antigen presentation, separately. Our study provides a comprehensive understanding of placental hematopoiesis and highlights the placenta as a source of macrophages, which has important implications for both basic and translational research.

HMGCS2 in metabolic pathways was associated with overall survival in hepatocellular carcinoma: A LASSO-derived study

This integrated bioinformatic study aimed to investigate potential prognostic candidates in hepatocellular carcinoma (HCC). In the GSE14520, GSE101685, and The Cancer Genome Atlas (TCGA) datasets, differentially expressed genes (DEGs) were identified and functional pathways of common DEGs were enriched. The least absolute shrinkage and selection operator (LASSO) model was used to screen the potential parameters associated with overall survival (OS) in HCC patients. Metabolic pathways were the most significantly enriched functional pathways of common DEGs in these three datasets. After LASSO model analysis, HMGCS2, UGP2, BCLC staging and TNM staging were screened as potential prognostic candidates for OS in HCC patients in GSE14520. HMGCS2 in the metabolic pathway was significantly downregulated in tumor tissues and peripheral blood mononuclear cells in HCC patients (all p < 0.05). Cox regression model indicated that HMGCS2 might be associate with OS in HCC patients in GSE14520 and in the TCGA (p = 0.029 and p = 0.05, respectively). Kaplan-Meier analysis demonstrated that HMGCS2 downregulation in tumors contributed to an unfavorable OS in HCC patients, both in GSE14520 and in the TCGA (p = 0.0001 and p = 0.0002, respectively). Additionally, HMGCS2 was significantly downregulated in HCC patients with high alpha-fetoprotein (AFP), main tumor size >5 cm, multinodular, advanced tumor staging including BCLC, TNM and CLIP (all p < 0.05). HMGCS2 was involved in metabolic pathways, and downregulated HMGCS2 in tumors was associated with unfavorable OS in HCC patients.

Identification of 5-methylcytosine-related signature for predicting prognosis in ovarian cancer

BACKGROUND

Ovarian cancer is one of the most common malignancies often resulting in a poor prognosis. 5-methylcytosine (m5C) is a common epigenetic modification with roles in eukaryotes. However, the expression and function of m5C regulatory factors in ovarian cancer remained unclear.

RESULTS

Two molecular subtypes with different prognostic and clinicopathological features were identified based on m5C regulatory factors. Meanwhile, functional annotation showed that in the two subtypes, 452 differentially expressed genes were significantly related to the malignant progression of ovarian cancer. Subsequently, four m5C genes were screened to construct a risk marker predictive of overall survival and indicative of clinicopathological features of ovarian cancer, also the robustness of the risk marker was verified in external dataset and internal validation set. multifactorial cox regression analysis and nomogram demonstrated that risk score was an independent prognostic factor for ovarian cancer prognosis.

CONCLUSION

In conclusion, our results revealed that m5C-related genes play a critical role in tumor progression in ovarian cancer. Further detection of m5C methylation could provide a novel targeted therapy for treating ovarian cancer.

CD2 Is a Novel Immune-Related Prognostic Biomarker of Invasive Breast Carcinoma That Modulates the Tumor Microenvironment

Female breast cancer (BCa) is the most commonly occurring cancer worldwide. The tumor microenvironment (TME) plays an essential role in tumor invasion, angiogenesis, unlimited proliferation, and even immune escape, but we know little about the TME of BCa. In this study, we aimed to find a TME-related biomarker for BCa, especially for invasive breast carcinoma (BRCA), that could predict prognosis and immunotherapy efficacy. Based on RNA-seq transcriptome data and the clinical characteristics of 1222 samples (113 normal and 1109 tumor samples) from The Cancer Genome Atlas (TCGA) database, we used the ESTIMATE algorithm to calculate the ImmuneScore and StromalScore and then identified differentially expressed genes (DEGs) between the high and low ImmuneScore groups and the high and low StromalScore groups. Thereafter, a protein–protein interaction (PPI) network analysis and univariate Cox regression analyses of overall survival were used to identify potential key genes. Five candidate genes were identified, comprising CD2, CCL19, CD52, CD3E, and ITK. Thereafter, we focused on CD2, analyzing CD2 expression and its association with survival. CD2 expression was associated with tumor size (T stage) to some extent, but not with overall TNM stage, lymph node status (N stage), or distant metastasis (M stage). High CD2 expression was associated with longer survival. METABRIC data were used to validate the survival result (n = 276). Gene set enrichment analysis (GSEA) showed that the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways that were significantly associated with high CD2 expression were mainly immune-related pathways. Furthermore, CD2 expression was correlated with 16 types of tumor-infiltrating immune cells (TICs). Hence, CD2 might be a novel biomarker in terms of molecular typing, and it may serve as a complementary approach to TNM staging to improve clinical outcome prediction for BCa patients.

Radiomic profiling of clear cell renal cell carcinoma reveals subtypes with distinct prognoses and molecular pathways

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Radiomics profile of clear cell renal cell carcinoma is heterogeneity.

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Multi-scale Radiogenomics could link molecular features and images.

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Radiomic subtypes could be used for risk stratification.

Background

To identify radiomic subtypes of clear cell renal cell carcinoma (ccRCC) patients with distinct clinical significance and molecular characteristics reflective of the heterogeneity of ccRCC.

Methods

Quantitative radiomic features of ccRCC were extracted from preoperative CT images of 160 ccRCC patients. Unsupervised consensus cluster analysis was performed to identify robust radiomic subtypes based on these features. The Kaplan–Meier method and chi-square test were used to assess the different clinicopathological characteristics and gene mutations among the radiomic subtypes. Subtype-specific marker genes were identified, and gene set enrichment analyses were performed to reveal the specific molecular characteristics of each subtype. Moreover, a gene expression-based classifier of radiomic subtypes was developed using the random forest algorithm and tested in another independent cohort (n = 101).

Results

Radiomic profiling revealed three ccRCC subtypes with distinct clinicopathological features and prognoses. VHL, MUC16, FBN2, and FLG were found to have different mutation frequencies in these radiomic subtypes. In addition, transcriptome analysis revealed that the dysregulation of cell cycle-related pathways may be responsible for the distinct clinical significance of the obtained subtypes. The prognostic value of the radiomic subtypes was further validated in another independent cohort (log-rank P = 0.015).

Conclusion

In the present multi-scale radiogenomic analysis of ccRCC, radiomics played a central role. Radiomic subtypes could help discern genomic alterations and non-invasively stratify ccRCC patients.

Comprehensive analysis of genomic mutation signature and tumor mutation burden for prognosis of intrahepatic cholangiocarcinoma

Background

Intrahepatic cholangiocarcinoma (iCCA) is a highly lethal malignancy of the biliary tract. Analysis of somatic mutational profiling can reveal new prognostic markers and actionable treatment targets. In this study, we explored the utility of genomic mutation signature and tumor mutation burden (TMB) in predicting prognosis in iCCA patients.

Methods

Whole-exome sequencing and corresponding clinical data were collected from the ICGC portal and cBioPortal database to detect the prognostic mutated genes and determine TMB values. To identify the hub prognostic mutant signature, we used Cox regression and Lasso feature selection. Mutation-related signature (MRS) was constructed using multivariate Cox regression. The predictive performances of MRS and TMB were assessed using Kaplan–Meier (KM) analysis and receiver operating characteristic (ROC). We performed a functional enrichment pathway analysis using gene set enrichment analysis (GSEA) for mutated genes. Based on the MRS, TMB, and the TNM stage, a nomogram was constructed to visualize prognosis in iCCA patients.

Results

The mutation landscape illustrated distributions of mutation frequencies and types in iCCA, and generated a list of most frequently mutated genes (such as Tp53, KRAS, ARID1A, and IDH1). Thirty-two mutated genes associated with overall survival (OS) were identified in iCCA patients. We obtained a six-gene signature using the Lasso and Cox method. AUCs for the MRS in the prediction of 1-, 3-, and 5-year OS were 0.759, 0.732, and 0.728, respectively. Kaplan–Meier analysis showed a significant difference in prognosis for patients with iCCA having a high and low MRS score (P < 0.001). GSEA was used to show that several signaling pathways, including MAPK, PI3K-AKT, and proteoglycan, were involved in cancer. Conversely, survival analysis indicated that TMB was significantly associated with prognosis. GSEA indicated that samples with high MRS or TMB also showed an upregulated expression of pathways involved in tumor signaling and the immune response. Finally, the predictive nomogram (that included MRS, TMB, and the TNM stage) demonstrated satisfactory performance in predicting survival in patients with iCCA.

Conclusions

Mutation-related signature and TMB were associated with prognosis in patients with iCCA. Our study provides a valuable prognostic predictor for determining outcomes in patients with iCCA.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-07788-7.

Using Elevated Cholesterol Synthesis as a Prognostic Marker in Wilms' Tumor: A Bioinformatic Analysis

Background

Wilms tumor is the most common renal malignancy of children. Identifying factors that could predict the prognosis of patients with Wilms tumor is clinically meaningful. Many studies found tumors with elevated cholesterol synthesis that are featured with dismal prognosis. Even in some clinical trials, people with excessive dietary cholesterol intake and high plasma low-density lipoprotein levels are observed to have increased risk for cancer. However, the role of cholesterol biosynthesis in Wilms tumor has not yet been well clarified.

Methods

RNA sequencing transcriptome data and all corresponding clinicopathological information used in our study were downloaded from the TARGET database. High-throughput sequencing (Fragments Per Kilobase of transcript per Million fragments mapped) data sets of 130 tumor samples and 6 normal samples were obtained for further analysis.

Results

Wilms tumor samples with higher activity of cholesterol synthesis are characterized with worse overall survival (P < 0.05). In addition, Wilms tumor samples with mitigated activity of cholesterol synthesis are featured with better dendritic cell (DC) function and cytolytic activity (P < 0.05). Furthermore, we constructed a prognosis model based on differential expressed cholesterol synthesis-related genes (DECSG), which could predict the OS of patients with Wilms tumor accurately. KEGG and GO analysis of differential expressed genes between tumor samples with high and low cholesterol synthesis indicated that DECSGs are highly enriched in “mitosis nuclear division,” “nuclear division,” “chromosome segregation,” “cell cycle,” “Spliceosome,” and “RNA transport.”

Conclusions

In conclusion, our study reported increased cholesterol synthesis in Wilms tumor predicts a worse prognosis and mitigated cytolytic activity, DC function, and MHC I signature in the tumor microenvironment. We also constructed a prognosis model for predicting the OS of patients with good accuracy, which is promising in clinical translation. Future studies should focus on the detailed mechanism that caused increasing cholesterol which promotes tumor progression and undermines patients' survival.

Integrated analysis of the molecular mechanisms in idiopathic pulmonary fibrosis

Rationale: Idiopathic pulmonary fibrosis (IPF) is one of the most aggressive forms of idiopathic interstitial pneumonia. Some miRNAs may be associated with IPF and may affect the occurrence and development of IPF in various pathways. Many miRNAs and genes that may be involved in the development of IPF have been discovered using chip and high throughput technologies. Methods: We analyzed one miRNA and four mRNA databases. We identified hub genes and pathways related to IPF using GO, KEGG enrichment analysis, gene set variation analysis (GSVA), PPI network construction, and hub gene analysis. A comprehensive analysis of differentially expressed miRNAs (DEMs), predicted miRNA target genes, and differentially expressed genes (DEGs) led to the creation of a miRNA-mRNA regulatory network in IPF. Results: We found 203 DEGs and 165 DEMs that were associated with IPF. The findings of enrichment analyses showed that these DEGs were mainly involved in antimicrobial humoral response, antimicrobial humoral immune response mediated by antimicrobial peptide, extracellular matrix organization, cell killing, and organ or tissue specific immune response. The VEGFA, CDH5, and WNT3A genes overlapped between hub genes and the miRNA-mRNA regulatory network. The miRNAs including miR-199b-5p, miR-140-5p, miR-199a-5p, miR-125A-5p, and miR-107 that we predicted would regulate the VEGFA, CDH5, and WNT3A genes, which were also associated with IPF or other fibrosis-related diseases. GSVA indicated that metabolic processes of UTP and IMP, immune response, regulation of Th2 cell cytokine production, and positive regulation of NK cell-mediated immunity are associated with the pathogenesis and treatment of IPF. These pathways also interact with VEGFA, CDH5, and WNT3A. Conclusion: These findings provide a new research direction for the diagnosis and treatment of IPF.

Development and Validation of an Individualized Immune-Related Gene Pairs Prognostic Signature in Papillary Renal Cell Carcinoma

Papillary renal carcinoma (PRCC) is one of the important subtypes of kidney cancer, with a high degree of heterogeneity. At present, there is still a lack of robust and accurate biomarkers for the diagnosis, prognosis and treatment selection of PRCC. Considering the important role of tumor immunity in PRCC, we aim to construct a signature based on immune-related gene pairs (IRGPs) to estimate the prognostic of patients with PRCC. We obtained gene expression profiling and clinical information of patients with PRCC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), which were divided into discovery (n = 287) and validation (n = 28) cohorts, respectively. By univariate analysis, multivariate Cox analysis, and least absolute shrinkage and selection operator (Lasso) analysis, we selected 14 IRGPs with a panel of 22 unique genes to construct the prognostic signature. According to the signature, we stratified patients into high-risk group and low-risk group. In both discovery and validation cohorts, the results of Kaplan-Meier analysis showed that there were significant differences in OS between the two groups (p < 0.001). Combined with multiple clinical and pathological factors, the results of multivariate analyses confirmed that this signature was an independent predictor of OS (HR, 3.548; 95%CI, 2.096-6.006; p < 0.001). The results of immune infiltration analysis demonstrated that the abundance of multiple tumor-infiltration lymphocytes such as CD8 + T cells, Tregs, and T follicular cell helper were significantly higher in the high-risk group. Functional analysis showed that multiple immune-related signaling pathways were enriched in the high-risk group. In conclusion, we successfully established an individualized prognostic IRGPs signature, which can accurately assess and predict the OS of patients with PRCC.

Three-gene risk model in papillary renal cell carcinoma: a robust likelihood-based survival analysis

Background: Papillary renal cell carcinoma (PRCC) accounts for 15% of all renal cell carcinomas. The molecular mechanisms of renal papillary cell carcinoma remain unclear, and treatments for advanced disease are limited.

Result: We built the computing model as follows: Risk score = 1.806 * TPX2 - 0.355 * TXNRD2 - 0.805 * SLC6A20. The 3-year AUC of overall survival was 0.917 in the training set (147 PRCC samples) and 0.760 in the test set (142 PRCC samples). Based on the robust model, M2 macrophages showed positive correlation with risk score, while M1 macrophages were the opposite. PRCC patients with low risk score showed higher tumor mutation burden. TPX2 is a risk factor, and co-expression factors were enriched in cell proliferation and cancer-related pathways. Finally, the proliferation and invasion of PRCC cell line were decreased in the TPX2 reduced group, and the differential expression was identified. TPX2 is a potential risk biomarker which involved in cell proliferation in PRCC.

Conclusion: We conducted a study to develop a three gene model for predicting prognosis in patients with papillary renal cell carcinoma. Our findings may provide candidate biomarkers for prognosis that have important implications for understanding the therapeutic targets of papillary renal cell carcinoma.

Method: Gene expression matrix and clinical data were obtained from TCGA (The Cancer Genome Atlas), GSE26574, GSE2048, and GSE7023. Prognostic factors were identified using “survival” and “rbsurv” packages, and a risk score was constructed using Multivariate Cox regression analysis. The co-expression networks of the factors in model were constructed using the “WGCNA” package. The co-expression genes of factors were enriched and displayed the biological process. Based on this robust risk model, immune cells infiltration proportions and tumor mutation burdens were compared between risk groups. Subsequently, using the PRCC cell line, the role of TPX2 was determined by Cell proliferation assay, 5-Ethynyl-20-deoxyuridine assay and Transwell assay.

Development of an immunogenomic landscape for the competing endogenous RNAs network of peri-implantitis

BACKGROUND

Peri-implantitis is an inflammation that occurs around the implant, resulting in varying degrees of inflammatory damage to the soft and hard tissues. The characteristic criterion is the loss of the supporting bone in an inflammatory environment. However, the specific mechanisms and biomarkers involved in peri-implantitis remain to be further studied. Recently, competing endogenous RNAs (ceRNA) and immune microenvironment have been found to play a more important role in the inflammatory process. In our study, we analyzed the expression of immune related microRNAs (miRNAs), long noncoding RNAs (lncRNAs) and message RNAs (mRNAs) in peri-implantitis by analyzing GSE33774 and GSE57631.

METHODS

In this study, we explored the expression profile data of immune-related lncRNAs, miRNAs and mRNAs, and constructed immune-related ceRNA network involved in the pathogenesis of peri-implantitis. In addition, the CIBERSORT was used to evaluate the content of immune cells in normal tissues and peri-implantitis to detect the immune microenvironment of peri-implantitis.

RESULTS

In the analysis, 14 DElncRNAs, 16 DEmiRNAs, and 18 DEmRNAs were used to establish an immune related ceRNA network and the immune infiltration patterns associated with peri-implantitis was discovered. Through the mutual verification of the two datasets, we found that GSK3B and miR-1297 may have important significance in the immune microenvironment and pathogenesis of peri-implantitis and GSK3B was closely related to four types of immune cells, especially with the highest correlation with resting mast cells (P = 0.0003).

CONCLUSIONS

Through immune-related ceRNA network, immune-related genes (IRGs) and immune cell infiltration can further comprehensively understand the pathogenesis of peri-implantitis, which built up an immunogenomic landscape with clinical significance for peri-implantitis.

Therapeutic mechanism of Toujie Quwen granules in COVID-19 based on network pharmacology

Background

Chinese medicine Toujie Quwen granule (TJQW) has proven to be effective in the treatment of mild coronavirus disease 2019 (COVID-19) cases by relieving symptoms, slowing the progression of the disease, and boosting the recovery of patients. But the bioactive compounds and potential mechanisms of TJQW for COVID-19 prevention and treatment are unclear. This study aimed to explore the potential therapeutic mechanism of TJQW in coronavirus disease 2019 (COVID-19) based on an integrated network pharmacology approach.

Methods

TCMSP were used to search and screen the active ingredients in TJQW. The Swiss TargetPrediction was used to predict the potential targets of active ingredients. Genes co-expressed with ACE2 were considered potential therapeutic targets on COVID-19. Venn diagram was created to show correlative targets of TJQW against COVID-19. Cytoscape was used to construct a “drug-active ingredient-potential target” network, STRING were used to construct protein-protein interaction network, and cytoHubba performed network topology analysis. Enrichment of biological functions and signaling pathways of core targets was performed by using the clusterProfiler package in R software and ClueGO with CluePedia plugins in Cytoscape.

Results

A total of 156 active ingredients were obtained through oral bioavailability and drug-likeness screenings. Two hundred twenty-seven potential targets of TJQW were related to COVID-19. The top ten core targets are EGFR, CASP3, STAT3, ESR1, FPR2, F2, BCL2L1, BDKRB2, MPO, and ACE. Based on that, we obtained 19 key active ingredients: umbelliprenin, quercetin, kaempferol, luteolin, praeruptorin E, stigmasterol, and oroxylin A. And the enrichment analysis obtained multiple related gene ontology functions and signaling pathways. Lastly, we constructed a key network of “drug-component-target-biological process-signaling pathway”. Our findings suggested that TJQW treatment for COVID-19 was associated with elevation of immunity and suppression of inflammatory stress, including regulation of inflammatory response, viral process, neutrophil mediated immunity, PI3K-Akt signaling pathway, MAPK signaling pathway, Jak-STAT signaling pathway, Complement and coagulation cascades, and HIF-1 signaling pathway.

Conclusions

Our study uncovered the pharmacological mechanism underlying TJQW treatment for COVID-19. These results should benefit efforts for people around the world to gain more knowledge about Chinese medicine TJQW in the treatment of this vicious epidemic COVID-19, and help to address this pressing problem currently facing the world.