CDC6 is a prognostic biomarker and correlated with immune infiltrates in glioma

TGIF2 is a potential biomarker for diagnosis and prognosis of glioma

Background

TGFB-induced factor homeobox 2 (TGIF2), a member of the Three-Amino-acid-Loop-Extension (TALE) superfamily, has been implicated in various malignant tumors. However, its prognostic significance in glioma, impact on tumor immune infiltration, and underlying mechanisms in glioma development remain elusive.

Methods

The expression of TGIF2 in various human normal tissues, normal brain tissues, and gliomas was investigated using HPA, TCGA, GTEx, and GEO databases. The study employed several approaches, including Kaplan-Meier analysis, ROC analysis, logistic regression, Cox regression, GO analysis, KEGG analysis, and GSEA, to explore the relationship between TGIF2 expression and clinicopathologic features, prognostic value, and potential biological functions in glioma patients. The impact of TGIF2 on tumor immune infiltration was assessed through Estimate, ssGSEA, and Spearman analysis. Genes coexpressed with TGIF2 were identified, and the protein-protein interaction (PPI) network of these coexpressed genes were constructed using the STRING database and Cytoscape software. Hub genes were identified using CytoHubba plugin, and their clinical predictive value was explored. Furthermore, in vitro experiments were performed by knocking down and knocking out TGIF2 using siRNA and CRISPR/Cas9 gene editing, and the role of TGIF2 in glioma cell invasion and migration was analyzed using transwell assay, scratch wound-healing assay, RT-qPCR, and Western blot.

Results

TGIF2 mRNA was found to be upregulated in 21 cancers, including glioma. High expression of TGIF2 was associated with malignant phenotypes and poor prognosis in glioma patients, indicating its potential as an independent prognostic factor. Furthermore, elevated TGIF2 expression positively correlated with cell cycle regulation, DNA synthesis and repair, extracellular matrix (ECM) components, immune response, and several signaling pathways that promote tumor progression. TGIF2 showed correlations with Th2 cells, macrophages, and various immunoregulatory genes. The hub genes coexpressed with TGIF2 demonstrated significant predictive value. Additionally, in vitro experiments revealed that knockdown and knockout of TGIF2 inhibited glioma cell invasion, migration and suppressed the epithelial-mesenchymal transition (EMT) phenotype.

Conclusion

TGIF2 emerges as a potential biomarker for glioma, possibly linked to tumor immune infiltration and EMT.

Prognostic value and immune landscapes of immunogenic cell death-associated lncRNAs in lung adenocarcinoma

Immunogenic cell death (ICD) has been demonstrated to activate T cells to kill tumor cells, which is closely related to tumor development, and long noncoding RNAs (lncRNAs) are also involved. However, it is not known whether ICD-related lncRNAs are associated with the development of lung adenocarcinoma (LUAD). We downloaded ICD-related genes from GeneCards and the transcriptome statistics of LUAD patients from The Cancer Genome Atlas (TCGA) and subsequently developed and verified a predictive model. A successful model was used together with other clinical features to construct a nomogram for predicting patient survival. To further study the mechanism of tumor action and to guide therapy, we performed enrichment analysis, tumor microenvironment analysis, somatic mutation analysis, drug sensitivity analysis and real-time quantitative polymerase chain reaction (RT-qPCR) analysis. Nine ICD-related lncRNAs with significant prognostic relevance were selected for model construction. Survival analysis demonstrated that overall survival was substantially shorter in the high-risk group than in the low-risk group (P < 0.001). This model was predictive of prognosis across all clinical subgroups. Cox regression analysis further supported the independent prediction ability of the model. Ultimately, a nomogram depending on stage and risk score was created and showed a better predictive performance than the nomogram without the risk score. Through enrichment analysis, the enriched pathways in the high-risk group were found to be primarily associated with metabolism and DNA replication. Tumor microenvironment analysis suggested that the immune cell concentration was lower in the high-risk group. Somatic mutation analysis revealed that the high-risk group contained more tumor mutations (P = 0.00018). Tumor immune dysfunction and exclusion scores exhibited greater sensitivity to immunotherapy in the high-risk group (P < 0.001). Drug sensitivity analysis suggested that the predictive model can also be applied to the choice of chemotherapy drugs. RT-qPCR analysis also validated the accuracy of the constructed model based on nine ICD-related lncRNAs. The prognostic model constructed based on the nine ICD-related lncRNAs showed good application value in assessing prognosis and guiding clinical therapy.

Molecular and clinical characterization of ANG expression in gliomas and its association with tumor-related immune response

Background

Angiogenin (ANG) has been widely reported as a crucial molecular regulator in multiple malignancies. However, its role in gliomagenesis remains unclear. This study aimed to investigate the molecular and clinical characterization of ANG expression at transcriptome level and the association with glioma-related immune response.

Methods

A total of 301 glioma samples with mRNA microarray data (CGGA301) was obtained from the official website of CGGA project for yielding preliminary results, followed by validation in two independent RNAseq datasets, including TCGA with 697 samples and CGGA325 with 325 patients. Moreover, CGGA single-cell RNAseq (scRNAseq) data were analyzed to identify differential and dynamic ANG expression in different cells. Immunohistochemistry was performed to evaluate ANG protein expression across different WHO grades in a tissue microarray (TMA). Figure generation and statistical analysis were conducted using R software.

Results

ANG expression was associated with clinical features, malignant phenotypes, and genomic alterations. Based on significantly correlated genes of ANG, subsequent gene ontology (GO) and gene set enrichment analysis (GSEA) concordantly pointed to the significant association of ANG in immune-related biological processes. Moreover, ANG showed robust correlations with canonical immune checkpoint molecules, including PD1 signaling, CTLA4, TIM3, and B7H3. Gene sets variation analysis (GSVA) found that ANG was particularly associated with activities of macrophages and antigen presentation cells (APCs) in both LGG and GBM across different datasets. Furthermore, the higher-ANG milieu seemed to recruit monocyte-macrophage lineage and dendritic cells into the glioma microenvironment. According to scRNAseq analysis, ANG was mainly expressed by neoplastic cells and tumor-associated macrophages (TAMs) and was correlated with the initiation and progression of tumor cells and the polarization of TAMs. Finally, Kaplan-Meier plots demonstrated that higher expression of ANG was significantly correlated with shorter survival in gliomas. Cox regression analysis further confirmed ANG as an independent predictor of prognosis for gliomas of all three datasets.

Conclusion

ANG is significantly correlated with a range of malignant and aggressive characteristics in gliomas and reveals considerable prognostic value for glioma patients. ANG seems to be primarily associated with immune activities of macrophages and APCs in gliomas. Furthermore, ANG is mainly expressed in neoplastic cells and TAMs and is involved in the initiation and progression of neoplastic cells as well as macrophage polarization.

Identified RP2 as a prognostic biomarker for glioma, facilitating glioma pathogenesis mainly via regulating tumor immunity

Glioma is the most common primary intracranial tumor in the central nervous system, with a high degree of malignancy and poor prognosis, easy to recur, difficult to cure. The mutation of Retinitis Pigmentosa 2 (RP2) can cause retinitis pigmentosa, it is a prognostic factor of osteosarcoma, however, its role in glioma remains unclear. Based on the data from TCGA and GTEx, we identified RP2 as the most related gene for glioma by WGCNA, and used a series of bioinformatics analyses including LinkedOmics, GSCA, CTD, and so on, to explore the expression of RP2 in glioma and the biological functions it is involved in. The results showed that RP2 was highly expressed in glioma, and its overexpression could lead to poor prognosis. In addition, the results of enrichment analysis showed that RP2 was highly correlated with cell proliferation and immune response. And then, we found significant enrichment of Macrophages among immune cells. Furthermore, our experiments have confirmed that Macrophages can promote the development of glioma by secreting or influencing the secretion of some cytokines. Moreover, we investigated the influence of RP2 on the immunotherapy of glioma and the role of m6A modification in the influence of RP2 on glioma. Ultimately, we determined that RP2 is an independent prognostic factor that is mainly closely related to immune for glioma.

Effect of gut microbiome regulated Taohong Siwu Decoction metabolism on glioma cell phenotype

Introduction

To establish a new model for exploring the mechanism of the gut microbiome and drug metabolism, we explored whether Taohong Siwu Decoction acts after metabolism by intestinal flora under the premise of clarifying the interaction between intestinal flora and drug metabolism.

Methods

Taohong Siwu Decoction (TSD) was fed to germ-free mice and conventional mice, respectively. The serum from both groups of mice was removed and co-cultured with glioma cells in vitro. The co-cultured glioma cells were compared separately for changes at the RNA level using RNA-seq technology. The genes of interest in the comparison results were selected for validation.

Results

The differences in the phenotypic alterations of glioma cells between serum from TSD-fed germ-free mice and normal mice were statistically significant. In vitro experiments showed that Taohong Siwu Decoction-fed normal mouse serum-stimulated glioma cells, which inhibited proliferation and increased autophagy. RNA-seq analysis showed that TSD-fed normal mouse serum could regulate CDC6 pathway activity in glioma cells. The therapeutic effect of TSD is significantly influenced by intestinal flora.

Conclusion

The treatment of tumors by TSD may be modulated by intestinal flora. We established a new method to quantify the relationship between intestinal flora and the regulation of TSD efficacy through this study.

Quantitative proteomics study on the changes of egg white of yellow preserved primary chicken eggs soaked in alkali solution

In order to investigate the changes of egg white of primary chicken eggs after being soaked in alkali solution, the tandem mass tags (TMT)-labeled quantitative proteomic technology combined with bioinformatics was conducted in this study. The results indicated that 100 differentially expressed proteins (DEPs) in yellow preserved primary egg white (YPPEW), 75 of which were highly and significantly correlated with the quality traits of YPPEW (| r | ≥ 0.9000, P < 0.01). Most of DEPs were involved in cellular processes by binding in extracellular space. Six pathways revealed the potential anti-inflammatory, anti-virus, anti-cancer and neuromodulatory mechanism of YPPEW. The current research provided a theoretical basis for the further study on YPPEW.

Long Non-Coding RNA BNIP3 Inhibited the Proliferation of Bovine Intramuscular Preadipocytes via Cell Cycle

The intramuscular fat (or marbling fat) content is an essential economic trait of beef cattle and improves the flavor and palatability of meat. Several studies have highlighted the correlation between long non-coding RNAs (lncRNAs) and intramuscular fat development; however, the precise molecular mechanism remains unknown. Previously, through a high-throughput sequencing analysis, we found a lncRNA and named it a long non-coding RNA BNIP3 (lncBNIP3). The 5' RACE and 3' RACE explored 1945 bp total length of lncBNIP3, including 1621 bp of 5'RACE, and 464 bp of 3'RACE. The nucleoplasmic separation and FISH results explored the nuclear localization of lncBNIP3. Moreover, the tissue expression of lncBNIP3 was higher in the longissimus dorsi muscle, followed by intramuscular fat. Furthermore, down-regulation of lncBNIP3 increased the 5-Ethynyl-2'- deoxyuridine (EdU)-EdU-positive cells. The flow cytometry results showed that the number of cells in the S phase was significantly higher in preadipocytes transfected with si-lncBNIP3 than in the control group (si-NC). Similarly, CCK8 results showed that the number of cells after transfection of si-lncBNIP3 was significantly higher than in the control group. In addition, the mRNA expressions of proliferative marker genes CyclinB1 (CCNB1) and Proliferating Cell Nuclear Antigen (PCNA) in the si-lncBNIP3 group were significantly higher than in the control group. The Western Blot (WB) results also showed that the protein expression level of PCNA transfection of si-lncBNIP3 was significantly higher than in the control group. Similarly, the enrichment of lncBNIP3 significantly decreased the EdU-positive cells in the bovine preadipocytes. The results of flow cytometry and CCK8 assay also showed that overexpression of lncBNIP3 inhibited the proliferation of bovine preadipocytes. In addition, the overexpression of lncBNIP3 significantly inhibited the mRNA expressions of CCNB1 and PCNA. The WB results showed that the overexpression of lncBNIP3 significantly inhibited the expression of the CCNB1 protein level. To further explore the mechanism of lncBNIP3 on the proliferation of intramuscular preadipocytes, RNA-seq was performed after interference with si-lncBNIP3, and 660 differentially expressed genes (DEGs) were found, including 417 up-regulated DEGs and 243 down-regulated DEGs. The KEGG pathway analysis showed that the cell cycle was the most significant pathway for the functional enrichment of DEGs, followed by the DNA replication pathway. The RT-qPCR quantified the expression of twenty DEGs in the cell cycle. Therefore, we speculated that lncBNIP3 regulated intramuscular preadipocyte proliferation through the cell cycle and DNA replication pathways. To further confirm this hypothesis, the cell cycle inhibitor Ara-C was used to inhibit DNA replication of the S phase in intramuscular preadipocytes. Herein, Ara-C and si-lncBNIP3 were simultaneously added to the preadipocytes, and the CCK8, flow cytometry, and EdU assays were performed. The results showed that the si-lncBNIP3 could rescue the inhibitory effect of Ara-C in the bovine preadipocyte proliferation. In addition, lncBNIP3 could bind to the promoter of cell division control protein 6 (CDC6), and down-regulation of lncBNIP3 promoted the transcription activity and the expression of CDC6. Therefore, the inhibitory effect of lncBNIP3 on cell proliferation might be understood through the cell cycle pathway and CDC6 expression. This study provided a valuable lncRNA with functional roles in intramuscular fat accumulation and revealed new strategies for improving beef quality.

High throughput sequencing revealed enhanced cell cycle signaling in SLE patients

The multi-system involvement and high heterogeneity of systemic lupus erythematosus (SLE) pose great challenges to its diagnosis and treatment. The purpose of the current study is to identify genes and pathways involved in the pathogenesis of SLE. High throughput sequencing was performed on the PBMCs from SLE patients. We conducted differential gene analysis, gene ontology (GO) analysis, kyoto encyclopedia of genes and genomes (KEGG) analysis, and quantitative real-time PCR (qRT-PCR) verification. Protein-protein interaction (PPI) analysis, alternative splicing analysis, and disease correlation analysis were conducted on some key pathogenic genes as well. Furthermore, si-CDC6 was used for transfection and cell proliferation was monitored using a cell counting kit-8 (CCK-8) assay. We identified 2495 differential genes (1494 upregulated and 1001 downregulated) in SLE patients compared with healthy controls. The significantly upregulated genes were enriched in the biological process-related GO terms of the cell cycle, response to stress, and chromosome organization. KEGG enrichment analysis revealed 7 significantly upregulated pathways including SLE, alcoholism, viral carcinogenesis, cell cycle, proteasome, malaria, and transcriptional misregulation in cancer. We successfully verified some differential genes on the SLE pathway and the cell cycle pathway. CDC6, a key gene in the cell cycle pathway, had remarkably higher MXE alternative splicing events in SLE patients than that in controls, which may explain its significant upregulation in SLE patients. We found that CDC6 participates in the pathogenesis of many proliferation-related diseases and its levels are positively correlated with the severity of SLE. Knockdown of CDC6 suppressed the proliferation of Hela cells and PBMCs from SLE patients in vitro. We identified SLE-related genes and their alternative splicing events. The cell cycle pathway and the cell cycle-related biological processes are over-activated in SLE patients. We revealed a higher incidence of MXE events of CDC6, which may lead to its high expression in SLE patients. Upregulated cell cycle signaling and CDC6 may be related to the hyperproliferation and pathogenesis of SLE.

CCNF is a potential pancancer biomarker and immunotherapy target

Background

CCNF catalyzes the transfer of ubiquitin molecules from E2 ubiquitin-conjugating enzymes to target proteins, thereby regulating the G1/S or G2/M transition of tumor cells. Thus far, CCNF expression and its potential as a pancancer biomarker and immunotherapy target have not been reported.

Methods

TCGA datasets and the R language were used to analyze the pancancer gene expression, protein expression, and methylation levels of CCNF; the relationship of CCNF expression with overall survival (OS), recurrence-free survival (RFS), immune matrix scores, sex and race; and the mechanisms for posttranscriptional regulation of CCNF.

Results

CCNF expression analysis showed that CCNF mRNA expression was higher in cancer tissues than in normal tissues in the BRCA, CHOL, COAD, ESCA, HNSC, LUAD, LUSC, READ, STAD, and UCEC; CCNF protein expression was also high in many cancer tissues, indicating that it could be an important predictive factor for OS and RFS. CCNF overexpression may be caused by CCNF hypomethylation. CCNF expression was also found to be significantly different between patients grouped based on sex and race. Overexpression of CCNF reduces immune and stromal cell infiltration in many cancers. Posttranscriptional regulation analysis showed that miR-98-5p negatively regulates the expression of the CCNF gene.

Conclusion

CCNF is overexpressed across cancers and is an adverse prognostic factor in terms of OS and RFS in many cancers; this phenomenon may be related to hypomethylation of the CCNF gene, which could lead to cancer progression and worsen prognosis. In addition, CCNF expression patterns were significantly different among patients grouped by sex and race. Its overexpression reduces immune and stromal cell infiltration. miR-98-5p negatively regulates CCNF gene expression. Hence, CCNF is a potential pancancer biomarker and immunotherapy target.

Role of estrogen receptor signaling pathway-related genes in diffuse large B-cell lymphoma and identification of key targets via integrated bioinformatics analysis and experimental validation

Diffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous malignancy. Epidemiologically, the incidence of DLBCL is higher in men, and the female sex is a favorable prognostic factor, which can be explained by estrogen. This study aimed to explore the potential targets of the estrogen receptor (ER) signaling pathway and provide a meaningful way to treat DLBCL patients. Datasets were obtained from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs). Representative gene sets estrogen receptor pathways, and growth regulatory pathways were identified based on Gene Set Enrichment Analysis (GSEA) analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for function and pathway analysis. STRING and Cytoscape were used to construct the interaction network, and the MCODE plug-in performed the module analysis. GEPIA, TCGA, and LOGpc databases were used for expression and predictive analysis. The Human Protein Atlas (HPA) database was used to analyze the protein expression levels, cBioPortal was used to explore genetic alterations, and ROC analysis and prognostic assessment were used to predict the diagnostic value of genes. Finally, BJAB cells were treated with ER inhibitor fulvestrant and specific shRNA, and the expression of hub genes was verified by RT-qPCR. We identified 81 overlapping DEGs and CDC6, CDC20, KIF20A, STIL, and TOP2A as novel biomarkers affecting the prognosis of DLBCL. In addition, the STAT and KRAS pathways are considered potential growth regulatory pathways. These results hold promise for new avenues for the treatment of DLBCL patients.

Screening for Biomarkers for Progression from Oral Leukoplakia to Oral Squamous Cell Carcinoma and Evaluation of Diagnostic Efficacy by Multiple Machine Learning Algorithms

The aim of the study is to identify key genes during the progression from oral leukoplakia (OL) to oral squamous cell carcinoma (OSCC) and predict effective diagnoses. Weighted gene co-expression network analysis (WGCNA) and differential expression analysis were performed to identify seven genes associated with the progression from OL to OSCC. Twelve machine learning algorithms including k-nearest neighbor (KNN), neural network (NNet), and extreme gradient boosting (XGBoost) were used to construct multi-gene models, which revealed that each model had good diagnostic efficacy. The functional mechanism or the pathways associated with these genes were evaluated using enrichment analysis, subtype clustering, and immune infiltration analysis. The enrichment analysis revealed that the genes enriched were associated with the cell cycle, cell division, and intracellular energy metabolism. The immunoassay results revealed that the genes primarily affected the infiltration of proliferating T cells and macrophage polarization. Finally, a nomogram and Kaplan-Meier survival analysis were used to predict the prognostic efficacy of key genes in OSCC patients. The results showed that genes could predict the prognosis of the patients, and patients in the high-risk group had a poor prognosis. Our study identified that the seven key genes, including DHX9, BCL2L12, RAD51, MELK, CDC6, ANLN, and KIF4A, were associated with the progression from OL to OSCC. These genes had good diagnostic efficacy and could be used as potential biomarkers for the prognosis of OSCC patients.