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.
Abstract Prostaglandin D2 Synthase (PTGDS) is an enzyme responsible for synthesizing prostaglandin D2. Despite its crucial role, PTGDS remains relatively understudied in tumor therapy, lacking comprehensive pan cancer analyses. Leveraging multi omics data integration, this study elucidates PTGDS's widespread dysregulation across various cancers and its correlation with patient survival. Moreover, PTGDS exhibits significant associations with stem cell scores, microenvironmental scores, microsatellite instability (MSI), tumor mutational burden (TMB), and methylation status in diverse tumor types. Additionally, immune correlations with PTGDS are evident across most cancers, with single cell transcriptome data indicating predominant associations with natural killer cells and macrophages. Notably, experimental validation reveals PTGDS's role in inhibiting lung adenocarcinoma cell A549 proliferation, linked to fatty acid degradation and cell cycle regulation. In summary, PTGDS demonstrates prognostic potential, influences pan cancer tumor immunity, and acts as a tumor suppressor in lung adenocarcinoma (LUAD).
Abstract BackgroundDue to the extremely high mortality rate of children with high-risk Neuroblastoma (NB), there is an urgent need for new indicators to further classify children in the high-risk group for more precise treatment. The purpose of our research is to explore the immune-related genes in NB in the high-risk group, and to further identify and develop a prognostic nomogram based on immune IRG signatures. MethodsThrough bioinformatics analysis to explore the abnormal expression of immune-related genes in the high-risk group. Cox regression and the least absolute shrinkage and selection operator (LASSO) analysis were conducted to identify the immune and overall survival (OS) related mRNA. The accuracy of the risk score is evaluated by Kaplan-Meier method and receiver operating characteristics (ROC) analysis, which is used to build a nomogram in combination with other clinical characteristics.. Quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to detect the accuracy of our results. ResultsA total of 127 common differentially expressed immune genes were found between the high-risk group and the non-high-risk group of the two data sets. Four immune-related genes (IRG) related to prognosis were identified and a risk score was established. Kaplan–Meier survival analysis and time-dependent ROC analysis showed that the 4-IRG risk score has satisfactory predictive potential and achieved consistency in the verification of external data sets. Subsequently, the risk score combined with clinical characteristics draws a nomogram. The reliability of the results was verified on 29 cases of NB tissues by qRT-PCR. ConclusionsOverall, we have developed a powerful multi-gene classifier that can effectively classify NB patients into low- and high-risk groups with poor prognosis, and draw a nomogram for children in the high-risk group. This feature can help select high-risk patients who need more aggressive adjuvant target therapy or immunotherapy.
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.
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.
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.
Abstract Background ：Due to the extremely high mortality rate of children with high-risk Neuroblastoma (NB), there is an urgent need for new indicators to further classify children in the high-risk group for more precise treatment. The purpose of our research is to explore the immune-related genes in NB in the high-risk group, and to further identify and develop a prognostic nomogram based on immune IRG signatures. Methods： Through bioinformatics analysis to explore the abnormal expression of immune-related genes in the high-risk group. Cox regression and the least absolute shrinkage and selection operator (LASSO) analysis were conducted to identify the immune and overall survival (OS) related mRNA. The accuracy of the risk score is evaluated by Kaplan-Meier method and receiver operating characteristics (ROC) analysis, which is used to build a nomogram in combination with other clinical characteristics.. Quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to detect the accuracy of our results. Results： A total of 127 common differentially expressed immune genes were found between the high-risk group and the non-high-risk group of the two data sets. Four immune-related genes (IRG) related to prognosis were identified and a risk score was established. Kaplan–Meier survival analysis and time-dependent ROC analysis showed that the 4-IRG risk score has satisfactory predictive potential and achieved consistency in the verification of external data sets. Subsequently, the risk score combined with clinical characteristics draws a nomogram. The reliability of the results was verified on 29 cases of NB tissues by qRT-PCR. Conclusions： Overall, we have developed a powerful multi-gene classifier that can effectively classify NB patients into low- and high-risk groups with poor prognosis, and draw a nomogram for children in the high-risk group. This feature can help select high-risk patients who need more aggressive adjuvant target therapy or immunotherapy.
Abstract 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.
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.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.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.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.
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