Search

Purpose: Disulfidptosis is a novel type of cell death induced by disulphide stress that depends on the accumulation of cystine disulphide, causing cytotoxicity and triggering cell death. However, the direct prognostic effect and regulatory mechanism of disulfidptosis-related genes in bladder urothelial carcinoma (BLCA) remain unclear. Methods: To explore the role of 10 disulfidptosis-related genes, the multiomic data of 10 genes were comprehensively analysed. Next, based on seven disulfidptosis-related differentially expressed genes, a novel disulfidptosis-related gene score was developed to help predict the prognosis of BLCA. Immunohistochemistry, EDU, Real-time PCR and western blot were used to verify the model. Results: Significant functional differences were found between the high- and low-risk score groups, and samples with a higher risk score were more malignant. Furthermore, the tumour exclusion and Tumour Immune Dysfunction and Exclusion scores of the high-risk score group were higher than those of the low-risk score group. The risk score was positively correlated with the expression of immune checkpoints. Drug sensitivity analyses revealed that the low-risk score group had a higher sensitivity to cisplatin, doxorubicin, docetaxel and gemcitabine than the high-risk score group. Moreover, the expression of the TM4SF1 was positively correlated with the malignancy degree of BLCA, and the proliferation ability of BLCA cells was reduced after knockdown TM4SF1. Conclusion: The present study results suggest that disulfidptosis-related genes influence the prognosis of BLCA through their involvement in immune cell infiltration. Thus, these findings indicate the role of disulfidptosis in BLCA and its potential regulatory mechanisms. [ABSTRACT FROM AUTHOR]

Background: Notch signaling is a key regulator of immune cell differentiation and linked to autoimmune diseases, tumorigenesis and tumor-induced immunomodulation. An abnormally activated Notch signaling pathway contributes to almost all of the key features of cancer, including tumor angiogenesis, stemness, and epithelial-mesenchymal transition. Consequently, we investigated Notch pathway-related genes for developing prognostic marker and assessing immune status in bladder cancer. Methods: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized to analyze RNA-seq data for bladder cancer. Cluster subtypes were identified using the NMF algorithm. In order to establish a prognostic risk signature, the least absolute shrinkage and selection operator (Lasso) and Cox regression analysis was utilized. GSEA was carried out to investigate the molecular mechanisms. Immune cell infiltration levels in bladder cancer were calculated using the CIBERSORT algorithm. External clinical tissue samples were used to validate the expression levels of signature genes. Results: Based on the NMF algorithm, bladder cancer samples were divided into two cluster subtypes and displayed different survival outcome and immune microenvironment. A six-gene risk signature (DTX3L, CNTN1, ENO1, GATA3, MAGEA1, and SORBS2) was independent for prognosis and showed good stability. The infiltration of immune cells and clinical variables were significantly different among the risk groups of patients. Response to immunotherapy also differed between different risk groups. Furthermore, the mRNA expression levels of the signature genes were verified in tissue samples by qRT-PCR. Conclusion: We established a 6-gene signature associated with Notch pathway in bladder cancer to effectively predict prognosis and reflect immune microenvironment status. [ABSTRACT FROM AUTHOR]

Background. Despite the constant iteration of small-molecule inhibitors and immune checkpoint inhibitors, PRAD (prostate adenocarcinoma) patients with distant metastases and biochemical recurrence maintain a poor survival outcome along with an increasing morbidity in recent years. N7-Methylguanine, a new-found type of RNA modification, has demonstrated an essential role in tumor progression but has hardly been studied for its effect on prostate carcinoma. The current study aimed to seek m7G (N7-methylguanosine) related prognostic biomarkers and potential targets for PRAD treatment. Methods. 42 genes related to m7G were collected from former literatures and GSEA (Gene Set Enrichment Analysis) website. Then, RNA-seq (RNA sequencing) and clinical data from TCGA-PRAD (The Cancer Genome Atlas-Prostate) cohort were retrieved to screen the differentially expressed m7G genes to further construct a multivariate Cox prognostic model for PRAD. Next, GSE116918, a prostate cancer cohort acquired from GEO (Gene Expression Omnibus) database, was analyzed for the external validation group to assess the ability to predict BFFS (biochemical failure-free survival) of our m7G prognostic signature. Kaplan-Meier, ROC (receiver operator characteristic), AUC (areas under ROC curve), and calibration curves were adopted to display the performance of this prognostic signature. In addition, immune infiltration analysis was implemented to evaluate the effect of these m7G genes on immunoinfiltrating cells. Correlation with drug susceptibility of the m7G signature was also analyzed by matching drug information in CellMiner database. Results. The m7G-related prognostic signature, including three genes (EIF3D, EIF4A1, LARP1) illustrated superior prognostic ability for PRAD in both training and validation cohorts. The 5-year AUC were 0.768 for TCGA-PRAD and 0.608 for GSE116918. It can well distinguish patients into different risk groups of biochemical recurrence (p =1e-04 for TCGA-PRAD and p =0.0186 for GSE116918). Immune infiltration analysis suggested potential regulation of m7G genes on neutrophils and dendritic cells in PRAD. Conclusions. A m7G-related prognostic signature was constructed and validated in the current study, giving new sights of m7G methylation in predicting the prognostic and improving the treatment of PRAD. [ABSTRACT FROM AUTHOR]

The platelet-derived growth factor (PDGF) pathway is important in angiogenesis, which can accelerate the formation of vessels in tumor tissues and promote the progression of malignant tumors. To clarify the role of PDGF in the occurrence of renal cell carcinoma and targeted drug resistance, we explored the pathway in kidney renal clear cell carcinoma (KIRC) through bioinformatics analysis with the aim of supporting comprehensive and individualized therapy. First, we found 40 genes related to the PDGF pathway through gene set enrichment analysis and then obtained their expressions and clinical data in 32 different cancers from The Cancer Genome Atlas (TCGA). Mutations in these genes (including copy number and single-nucleotide variation) and mRNA expression were also detected. Next, we conducted a hazard ratio analysis to determine whether the PDGF pathway genes were risk or protective factors in tumors. Although PDGF-related genes acted as traditional oncogenes and were closely related to tumor angiogenesis in many cancers, our results indicated that most genes had a protective role in KIRC. We further analyzed the methylation modification of PDGF pathway genes and found that they were prevalent in 32 different cancers. Furthermore, 539 KIRC samples obtained from TCGA were divided into three clusters based on the mRNA expression of PDGF genes, including normal, inactive, and active PDGF gene expressions. The results from survival curve analysis indicated that the active PDGF cluster of patients had the best survival rate. Using the three clusters, we studied the correlation between the PDGF pathway and 12 common targeted drugs, as well as classical oncogenes and infiltrating immune cells. A prognostic risk model was constructed based on the PDGF score using LASSO-Cox regression analysis to analyze the value of the model in predicting the prognosis of patients with KIRC. Finally, 11 genes were selected for LASSO regression analysis, and the results demonstrated the high predictive value of this risk model and its close relationship with the pathological characteristics of KIRC (metastasis, size, grade, stage, etc.). In addition, we found that the risk score was an independent risk factor correlated with overall survival through univariate and multivariate analyses and a nomogram was built to assess patient prognosis. In conclusion, the occurrence and development of KIRC may be associated with an abnormally activated PDGF pathway, which may be a potential drug target in the treatment of KIRC. [ABSTRACT FROM AUTHOR]