Pan-Cancer Analysis Identifies CHD5 as a Potential Biomarker for Glioma.

The chromodomain helicase DNA binding domain 5 (CHD5) is required for neural development and plays an important role in the regulation of gene expression. Although CHD5 exerts a broad tumor suppressor effect in many tumor types, its specific functions regarding its expression levels, and impact on immune cell infiltration, proliferation and migration in glioma remain unclear. Here, we evaluated the role of CHD5 in tumor immunity in a pan-cancer multi-database using the R language. The Cancer Genome Atlas (TCGA), Genotype Tissue Expression (GTEx), and Cancer Cell Lines Encyclopedia (CCLE) datasets were utilized to determine the role of CHD5 in 33 types of cancers, including the expression level, prognosis, tumor progression, and immune microenvironment. Furthermore, we explored the effect of CHD5 on glioma proliferation and migration using the cell counting kit 8 (CCK-8) assay, transwell assays and western blot analysis. The findings from our pan-cancer analysis showed that CHD5 was differentially expressed in the tumor tissues as compared to the normal tissues. Survival analysis showed that CHD5 was generally associated with the prognosis of glioblastoma (GBM), low Grade Glioma (LGG) and neuroblastoma, where the low expression of CHD5 was associated with a worse prognosis in glioma patients. Then, we confirmed that the expression level of CHD5 was associated with tumor immune infiltration and tumor microenvironment, especially in glioma. Moreover, si-RNA mediated knockdown of CHD5 promoted the proliferation and migration of glioma cells in vitro. In conclusion, CHD5 was found to be differentially expressed in the pan-cancer analysis and might play an important role in antitumor immunity. CHD5 is expected to be a potential tumor prognostic marker, especially in glioma.

Identify potential miRNA-mRNA regulatory networks contributing to high-risk neuroblastoma.

Neuroblastoma (NB) is a common tumor in children, usually in the retroperitoneum. After various treatments, low- and intermediate-risk patients have achieved good results, but the prognosis of high-risk patients is still very poor. Therefore, it is necessary to find new effective targets for the treatment of high-risk patients. In this study, comprehensive bioinformatics analysis was used to identify the differentially expressed genes (DEG and DEM) between high-risk patients and non-high-risk patients, and it was identified that ADRB2 may affect the survival status of high-risk patients due to miR -30a-5p regulation. The GSE49710, GSE73517, and GSE121513 datasets were downloaded from the Gene Expression Synthesis (GEO) database, and DEG and DEM were selected. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were applied to the selected DEGs. The STRING database and Cytoscape software were used to construct protein-protein interaction (PPI) networks and perform modular analysis of the DEGs. The TARGET data set containing information on overall survival days were used for the prognostic analysis of central genes. We identified a total of 255 DEGs from GSE49710 and GSE73517, and 193 DEMs from GSE121513. We identified the 5 most important central genes from the PPI network, performed a prognostic analysis in the target data set, and verified their expression using RT-qPCR to select the most important ADRB2 gene to predict miRNA. Integrating the differential miRNA predicted by miRDB and miRSystem and GSE121513 between the targeted miRNA and the prognosis, miR-30a-5p was finally identified as the targeted miRNA of ADRB2.

Causal association of plasma circulating metabolites with nephritis: a Mendelian randomization study.

Background: Nephritis is a pivotal catalyst in chronic kidney disease (CKD) progression. Although epidemiological studies have explored the impact of plasma circulating metabolites and drugs on nephritis, few have harnessed genetic methodologies to establish causal relationships. Methods: Through Mendelian randomization (MR) in two substantial cohorts, spanning large sample sizes, we evaluated over 100 plasma circulating metabolites and 263 drugs to discern their causal effects on nephritis risk. The primary analytical tool was the inverse variance weighted (IVW) analysis. Our bioinformatic scrutiny of GSE115857 (IgA nephropathy, 86 samples) and GSE72326 (lupus nephritis, 238 samples) unveiled anomalies in lipid metabolism and immunological characteristics in nephritis. Thorough sensitivity analyses (MR-Egger, MR-PRESSO, leave-one-out analysis) were undertaken to verify the instrumental variables' (IVs) assumptions. Results: Unique lipoprotein-related molecules established causal links with diverse nephritis subtypes. Notably, docosahexaenoic acid (DHA) emerged as a protective factor for acute tubulointerstitial nephritis (ATIN) (OR1 = 0.84, [95% CI 0.78-0.90], p1 = 0.013; OR2 = 0.89, [95% CI 0.82-0.97], p2 = 0.007). Conversely, multivitamin supplementation minus minerals notably increased the risk of ATIN (OR = 31.25, [95% CI 9.23-105.85], p = 0.004). Reduced α-linolenic acid (ALA) levels due to lipid-lowering drugs were linked to both ATIN (OR = 4.88, [95% CI 3.52-6.77], p < 0.001) and tubulointerstitial nephritis (TIN) (OR = 7.52, [95% CI 2.78-20.30], p = 0.042). While the non-renal drug indivina showed promise for TIN treatment, the use of digoxin, hydroxocobalamin, and liothyronine elevated the risk of chronic tubulointerstitial nephritis (CTIN). Transcriptome analysis affirmed that anomalous lipid metabolism and immune infiltration are characteristic of IgA nephropathy and lupus nephritis. The robustness of these causal links was reinforced by sensitivity analyses and leave-one-out tests, indicating no signs of pleiotropy. Conclusion: Dyslipidemia significantly contributes to nephritis development. Strategies aimed at reducing plasma low-density lipoprotein levels or ALA supplementation may enhance the efficacy of existing lipid-lowering drug regimens for nephritis treatment. Renal functional status should also be judiciously considered with regard to the use of nonrenal medications.

HMGCS2 serves as a potential biomarker for inhibition of renal clear cell carcinoma growth.

3-Hydroxymethylglutaryl-CoA synthase 2 (HMGCS2) is the rate-limiting enzyme for ketone body synthesis, and most current studies focus on mitochondrial maturation and metabolic reprogramming. The role of HMGCS2 was evaluated in a pan-cancer multi-database using R language, and HMGCS2 was lowly expressed or not differentially expressed in all tumor tissues compared with normal tissues. Correlation analysis of clinical case characteristics, genomic heterogeneity, tumor stemness, and overall survival revealed that HMGCS2 is closely related to clear cell renal cell carcinoma (KIRC). Single-cell sequencing data from normal human kidneys revealed that HMGCS2 is specifically expressed in proximal tubular cells of normal adults. In addition, HMGCS2 is associated with tumor immune infiltration and microenvironment, and KIRC patients with low expression of HMGCS2 have worse prognosis. Finally, the results of cell counting kit 8 assays, colony formation assays, flow cytometry, and Western blot analysis suggested that upregulation of HMGCS2 increased the expression of key tumor suppressor proteins, inhibited the proliferation of clear cell renal cell carcinoma cells and promoted cell apoptosis. In conclusion, HMGCS2 is abnormally expressed in pan-cancer, may play an important role in anti-tumor immunity, and is expected to be a potential tumor prognostic marker, especially in clear cell renal cell carcinoma.

HPGDS is a novel prognostic marker associated with lipid metabolism and aggressiveness in lung adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) is the most common respiratory globallywith a poor prognosis. Lipid metabolism is extremely important for the occurrence and development of cancer. However, the role of genes involved in lipid metabolism in LUAD development is unclear. We aimed to identify the abnormal lipid metabolism pathway of LUAD, construct a novel prognostic model of LUAD, and discover novel biomarkers involved in lipid metabolism in LUAD. Methods: Based on differentially expressed genes involved in lipid metabolism in LUAD samples from The Cancer Genome Atlas (TCGA), abnormal lipid metabolism pathways in LUAD were analyzed. The lasso penalized regression analysis was performed on the TCGA cohort (training set) to construct a risk score formula. The predictive ability of the risk score was validated in the Gene Expression Omnibus (GEO) dataset (validation set) using Kaplan-Meier analysis and ROC curves. Finally, based on CRISPR gene editing technology, hematopoietic prostaglandin D synthase (HPGDS) was knocked out in A549 cell lines, the changes in lipid metabolism-related markers were detected by western blotting, and the changes in cell migration were detected by transwell assay. Results: Based on the differential genes between lung cancer tissue and normal tissue, we found that the arachidonic acid metabolism pathway is an abnormal lipid metabolism pathway in both lung adenocarcinoma and lung squamous cell carcinoma. Based on the sample information of TCGA and abnormally expressed lipid metabolism-related genes, a 9-gene prognostic risk score was successfully constructed and validated in the GEO dataset. Finally, we found that knockdown of HPGDS in A549 cell lines promoted lipid synthesis and is more invasive than in control cells. Rescue assays showed that ACSL1 knockdown reversed the pro-migration effects of HPGDS knockdown. The knockdown of HPGDS promoted migration response by upregulating the expression of the lipid metabolism key enzymes ACSL1 and ACC. Conclusion: The genes involved in lipid metabolism are associated with the occurrence and development of LUAD. HPGDS can be a therapeutic target of a potential lipid metabolism pathway in LUAD, and the therapeutic target of lipid metabolism genes in LUAD should be studied further.

Expression of ADRB2 in children with neuroblastoma and its influence on prognosis.

Objective: Neuroblastoma (NB), originating from sympathetic spinal tissue, is a serious threat to the life of children. Especially in the high-risk group, an overall five-year survival rate less than 50% indicates an extremely poor clinical outcome. Here, the expression the of ß-2 adrenergic (ADRB2) receptor gene in tumor tissues of children with NB was detected and the correlation between its expression and clinical characteristics and prognosis was analyzed. Methods: Forty-five tumor tissue samples and forty-eight paraffin sections of NB were obtained from Children's Hospital of Chongqing Medical University from 2015 to 2021. Real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) was utilized to detect the expression of ADRB2 at the mRNA level and immunohistochemistry (IHC) at the protein level. Results: For the RT-qPCR, the analysis showed that the expression of ADRB2 in the high-risk group was significantly lower (P = 0.0003); in addition, there were also statistically significant differences in Shimada classification (P = 0.0025) and N-MYC amplification (P = 0.0011). Survival prognosis analysis showed that the prognosis was better with high ADRB2 expression (P = 0.0125), and the ROC curve showed that ADRB2 has a certain accuracy in predicting prognosis (AUC = 0.707, CI: 0.530-0.884). Moreover, the expression of ADRB2, N-MYC amplification and bone marrow metastasis were the factors that independently affected prognosis, and at the protein level, the results showed that the differential expression of ADRB2 was conspicuous in risk (P = 0.0041), Shimada classification (P = 0.0220) and N-MYC amplification (P = 0.0166). In addition, Kaplan-Meier curves showed that the prognosis in the group with high expression of ADRB2 was better (P = 0.0287), and the ROC curve showed that the score of ADRB2 had poor accuracy in predicting prognosis (AUC = 0.662, CI: 0.505-0.820). Conclusion: ADRB2 is a protective potential biomarker and is expected to become a new prognostic biomolecular marker of NB.

Single-cell landscape analysis reveals distinct regression trajectories and novel prognostic biomarkers in primary neuroblastoma.

Neuroblastoma (NB), which is the most common pediatric extracranial solid tumor, varies widely in its clinical presentation and outcome. NB has a unique ability to spontaneously differentiate and regress, suggesting a potential direction for therapeutic intervention. However, the underlying mechanisms of regression remain largely unknown, and more reliable prognostic biomarkers are needed for predicting trajectories for NB. We performed scRNA-seq analysis on 17 NB clinical samples and three peritumoral adrenal tissues. Primary NB displayed varied cell constitution, even among tumors of the same pathological subtype. Copy number variation patterns suggested that neuroendocrine cells represent the malignant cell type. Based on the differential expression of sets of related marker genes, a subgroup of neuroendocrine cells was identified and projected to differentiate into a subcluster of benign fibroblasts with highly expressed CCL2 and ZFP36, supporting a progressive pathway of spontaneous NB regression. We also identified prognostic markers (STMN2, TUBA1A, PAGE5, and ETV1) by evaluating intra-tumoral heterogeneity. Lastly, we determined that ITGB1 in M2-like macrophages was associated with favorable prognosis and may serve as a potential diagnostic marker and therapeutic target. In conclusion, our findings reveal novel mechanisms underlying regression and potential prognostic markers and therapeutic targets of NB.

A five metastasis-related long noncoding RNA risk signature for osteosarcoma survival prediction.

BACKGROUND: Osteosarcoma is a highly malignant and common bone tumour with an aggressive disease course and a poor prognosis. Previous studies have demonstrated the relationship between long noncoding RNAs (lncRNAs) and tumorigenesis, metastasis, and progression. METHODS: We utilized a large cohort from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database osteosarcoma project to identify potential lncRNAs related to the overall survival of patients with osteosarcoma by using univariate and multivariate Cox proportional hazards regression analyses. Kaplan-Meier curves were generated to evaluate the overall survival difference between patients in the high-risk group and the low-risk group. A time-dependent receiver operating characteristic curve (ROC) was employed, and the area under the curve (AUC) of ROC was measured to assess the sensitivity and specificity of the multi-lncRNA signature. RESULTS: Five lncRNAs (RP11-128N14.5, RP11-231|13.2, RP5-894D12.4, LAMA5-AS1, RP11-346L1.2) were identified, and a five-lncRNA signature was constructed. The AUC for predicting 5-year survival was 0.745, which suggested good performance of the five-lncRNA signature. In addition, functional enrichment analysis of the five-lncRNA-correlated protein-coding genes (PCGs) was performed to show the biological function of the five lncRNAs. Additionally, PPI network suggested RTP1 is a potential biomarker that regulates the prognosis of osteosarcoma. CONCLUSIONS: We developed a five-lncRNA signature as a potential prognostic indicator for osteosarcoma.

Identification of MYCN-Related Gene as a Potential Biomarker for Neuroblastoma Prognostic Model by Integrated Analysis and Quantitative Real-Time PCR.

Neuroblastoma (NB) has the highest incidence of all extracranial solid tumors in children and is highly lethal. This study aims to establish a prognostic model of NB with MYCN-related genes. We determined the gene expression profiles of 900 NB samples from the UCSC database and four Gene Expression Omnibus (GEO) data sets, and performed a comprehensive bioinformatics analysis and clinical sample verification. After univariate Cox regression, least absolute shrinkage and selection operator (Lasso), and multivariate Cox regression analyses, four (AKR1C1, CHD5, PDE4DIP, and PRKACB) genes were finally selected and used to construct a risk score prognostic model. In the UCSC data set, the high-risk group exhibited a significantly worse prognosis than the low-risk group. In addition, the nomogram, which includes prognostic markers and clinical factors, demonstrates high prognostic value. Finally, the differential expression of the four genes in the model was verified by quantitative real-time PCR in clinical tissues. These findings of MYCN-related genes provide a new and reliable prognostic model for NB related to MYCN.