A Newly Defined Pyroptosis-Related Gene Signature for the Prognosis of Bladder Cancer

IRF1 governs the expression of SMARCC1 via the GCN5-SETD2 axis and actively engages in the advancement of osteoarthritis

Background

Osteoarthritis (OA) is a degenerative joint disease characterized by the breakdown of joint cartilage and underlying bone. Macrophages are a type of white blood cell that plays a critical role in the immune system and can be found in various tissues, including joints. Research on the relationship between OA and macrophages is essential to understand the mechanisms underlying the development and progression of OA.

Objective

This study was performed to analyze the functions of the IRF1-GCN5-SETD2-SMARCC1 axis in osteoarthritis (OA) development.

Methods

A single-cell RNA sequencing (scRNA-seq) dataset, was subjected to a comprehensive analysis aiming to identify potential regulators implicated in the progression of osteoarthritis (OA). In order to investigate the role of IRF1 and SMARCC1, knockdown experiments were conducted in both OA-induced rats and interleukin (IL)-1β-stimulated chondrocytes, followed by the assessment of OA-like symptoms, secretion of inflammatory cytokines, and polarization of macrophages. Furthermore, the study delved into the identification of aberrant epigenetic modifications and functional enzymes responsible for the regulation of SMARCC1 by IRF1. To evaluate the clinical significance of the factors under scrutiny, a cohort comprising 13 patients diagnosed with OA and 7 fracture patients without OA was included in the analysis.

Results

IRF1 was found to exert regulatory control over the expression of SMARCC1, thus playing a significant role in the development of osteoarthritis (OA). The knockdown of either IRF1 or SMARCC1 disrupted the pro-inflammatory effects induced by IL-1β in chondrocytes, leading to a mitigation of OA-like symptoms, including inflammatory infiltration, cartilage degradation, and tissue injury, in rat models. Additionally, this intervention resulted in a reduction in the predominance of M1 macrophages both in vitro and in vivo. Significant epigenetic modifications, such as abundant H3K27ac and H3K4me3 marks, were observed near the SMARCC1 promoter and 10 kb upstream region. These modifications were attributed to the recruitment of GCN5 and SETD2, which are functional enzymes responsible for these modifications. Remarkably, the overexpression of either GCN5 or SETD2 restored SMARCC1 expression in rat cartilages or chondrocytes, consequently exacerbating the OA-like symptoms.

Conclusion

This research postulates that the transcriptional activity of SMARCC1 can be influenced by IRF1 through the recruitment of GCN5 and SETD2, consequently regulating the H3K27ac and H3K4me3 modifications in close proximity to the SMARCC1 promoter and 10 kb upstream region. These modifications, in turn, facilitate the M1 skewing of macrophages and contribute to the progression of osteoarthritis (OA).

The Translational Potential of this Article

The study demonstrated that the regulation of SMARCC1 by IRF1 plays a crucial role in the development of OA. Knocking down either IRF1 or SMARCC1 disrupted the pro-inflammatory effects induced by IL-1β in chondrocytes, leading to a mitigation of OA-like symptoms in rat models. These symptoms included inflammatory infiltration, cartilage degradation, and tissue injury. These findings suggest that targeting the IRF1-SMARCC1 regulatory axis, as well as the associated epigenetic modifications, could potentially be a novel approach in the development of OA therapies, offering new opportunities for disease management and improved patient outcomes.

Construction of prognostic risk model of bladder cancer based on cuproptosis-related long non-coding RNAs

OBJECTIVES

To construct a prognosis risk model based on long noncoding RNAs (lncRNAs) related to cuproptosis and to evaluate its application in assessing prognosis risk of bladder cancer patients.

METHODS

RNA sequence data and clinical data of bladder cancer patients were downloaded from the Cancer Genome Atlas database. The correlation between lncRNAs related to cuproptosis and bladder cancer prognosis was analyzed with Pearson correlation analysis, univariate Cox regression, Lasso regression, and multivariate Cox regression. Then a cuproptosis-related lncRNA prognostic risk scoring equation was constructed. Patients were divided into high-risk and low-risk groups based on the median risk score, and the immune cell abundance between the two groups were compared. The accuracy of the risk scoring equation was evaluated using Kaplan-Meier survival curves, and the application of the risk scoring equation in predicting 1, 3 and 5-year survival rates was evaluated using receiver operating characteristic (ROC) curves. Univariate and multivariate Cox regression were used to screen for prognostic factors related to bladder cancer patients, and a prognostic risk assessment nomogram was constructed, the accuracy of which was evaluated with calibration curves.

RESULTS

A prognostic risk scoring equation for bladder cancer patients was constructed based on nine cuproptosis-related lncRNAs. Immune infiltration analysis showed that the abundances of M0 macrophages, M1 macrophages, M2 macrophages, resting mast cells and neutrophils in the high-risk group were significantly higher than those in the low-risk group, while the abundances of CD8+ T cells, helper T cells, regulatory T cells and plasma cells in the low-risk group were significantly higher than those in the high-risk group (all P<0.05). Kaplan-Meier survival curve analysis showed that the total survival and progression-free survival of the low-risk group were longer than those of the high-risk group (both P<0.01). Univariate and multivariate Cox analysis showed that the risk score, age and tumor stage were independent factors for patient prognosis. The ROC curve analysis showed that the area under the curve (AUC) of the risk score in predicting 1, 3 and 5-year survival was 0.716, 0.697 and 0.717, respectively. When combined with age and tumor stage, the AUC for predicting 1-year prognosis increased to 0.725. The prognostic risk assessment nomogram for bladder cancer patients constructed based on patient age, tumor stage, and risk score had a prediction value that was consistent with the actual value.

CONCLUSIONS

A bladder cancer patient prognosis risk assessment model based on cuproptosis-related lncRNA has been successfully constructed in this study. The model can predict the prognosis of bladder cancer patients and their immune infiltration status, which may also provide a reference for tumor immunotherapy.

Identification and validation of the pyroptosis-related long noncoding rna signature to predict the prognosis of patients with bladder cancer

Bladder cancer ranked the second most frequent tumor among urological malignancies. This work investigated bladder cancer prognosis, including the relevance of pyroptosis-related long noncoding RNA (lncRNA) in it and its potential roles. The Cancer Genome Atlas database offered statistics on lncRNAs and clinical data from 411 bladder cancer patients. Pearson correlation analysis was used to evaluate pyroptosis-related lncRNAs. To explore prognosis-associated lncRNAs, we performed univariate Cox regression, least absolute shrinkage and selection operator regression analyses, as well as the Kaplan-Meier method. Multivariate Cox analysis was leveraged to establish the risk score model. Afterward, a nomogram was constructed according to the risk score and clinical variables. Finally, to investigate the potential functions of pyroptosis-related lncRNAs, gene set enrichment analysis was employed. Eleven pyroptosis-related lncRNAs were screened to be closely associated with patients prognosis. On this foundation, a risk score model was created to classify patients into high and low risk groups. The signature was shown to be an independent prognostic factor (P < .001) with an area under the curve of 0.730. Then a nomogram was established including risk scores and clinical characteristics. The nomogram prediction effect is excellent, with a concordance index of 0.86. The 11-lncRNAs signature was associated with the supervision of oxidative stress, epithelial-mesenchymal transition, cell adhesion, TGF-β, and Wingless and INT-1 signaling pathway, according to the gene set enrichment analysis. Our findings indicate that pyroptosis-related lncRNAs, which may affect tumor pathogenesis in many ways, might be exploited to assess the prognosis of bladder cancer patients.

Manf Enhances the Pyroptosis Inhibition of Bone Marrow-derived Mesenchymal Stem Cells to Relieve Cerebral Infarction Injury

Cerebral infarction is a common disease characterized by high mortality, a narrow therapeutic window, and limited therapeutic options. Recently, cell therapy based on gene modification has brought a glimmer of hope to the treatment of cerebral infarction although the explicit underlying mechanism is beyond being well dissected. In the present study, we constructed an animal model of middle cerebral artery occlusion (MCAO), compared differentially expressed genes (DEGs) between the sham and MCAO groups by single-cell RNA sequencing (scRNA-seq) to explore the potential cell death-related pathways involved in cerebral infarction, and transfected Manf into BMSCs by lentivirus. Subsequently, we injected BMSCs (bone marrow-derived mesenchymal stem cells), Manf-modified BMSCs, or lentivirus encoding Manf into the brain. Their effects on MANF content, apoptosis, pyroptosis, infarct volume in the brain, and neurological function were evaluated after MCAO. We found that the DEGs upregulated in four major cell clusters after MCAO and were enriched with not only apoptosis, ferroptosis, and necroptosis but also with pyroptosis-related pathways. In addition, transfection of Manf into BMSCs significantly increased the expression and secretion of MANF in BMSCs; BMSCs, Manf-modified BMSCs, and Manf treatment all resulted in an increase in Manf content in the brain, a decrease in the expression of apoptosis- and pyroptosis-related molecules, a reduction in infarct volume, and an improvement in neurological function after MCAO. Moreover, Manf-modified BMSCs have the strongest therapeutic effect. Collectively, Manf-modified BMSCs ameliorate ischemic injury after cerebral infarction by repressing apoptosis- and pyroptosis-related molecules, which represents a new cell therapy strategy for cerebral infarction.

A Novel Defined Pyroptosis-Related Gene Signature for Predicting the Prognosis of Endometrial Cancer

Endometrial carcinoma (EC) is the second major female genital malignancy. Genetic signatures may be an improved choice to predict the prognosis of EC patients. The relationship between pyroptosis and tumours has attracted much attention in recent years. Here, we constructed a new pyroptosis-related gene (PRG) signature for predicting the prognosis of EC. In this study, gene data and clinical information of EC patients were obtained from The Cancer Genome Atlas (TCGA). Following the identification of PRGs correlated with EC prognosis, we further investigate the bioinformatics functions of these PRGs by univariate Cox regression analysis and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Then, we used the least absolute contraction and selection operator (LASSO) regression and multiple Cox regression analysis to construct a new PRG signature that contains seven PRGs (NFKB1, EEF2K, CTSV, MDM2, GZMB, PANX1, and PTEN) and performed the Kaplan-Meier (K-M) analysis, receiver operating characteristic curve (ROC) analysis, and principal component analysis (PCA) to evaluate the prognostic value of our novel PRG signature. Finally, we assessed the correlations between pyroptosis and immune cells/checkpoints through the CIBERSORT tool and single-sample gene set enrichment analysis (ssGSEA). The result suggested that our signature was powerful in predicting EC prognosis and may play a part in assessing response to immunotherapy in EC patients. In conclusion, our study established a novel PRG signature for EC, which can be used as an effective prognostic marker in clinical practice in the future.

A risk model based on pyroptosis subtypes predicts tumor immune microenvironment and guides chemotherapy and immunotherapy in bladder cancer

Although immunotherapy has revolutionized bladder cancer (BLCA) therapy, only few patients demonstrate durable clinical benefits due to the heterogeneity. Emerging evidence has linked pyroptosis to shaping tumor microenvironment (TME) and predicting therapy response. However, the relationship between pyroptosis and immunotherapy response in BLCA remains elusive. In this study, we performed a comprehensive bioinformatic analysis to dissect the role of pyroptosis in BLCA. Differentially expressed pyroptosis-related genes (DEPRGs) between tumor and normal tissues were identified using publicly available datasets. Kaplan-Meier analysis was performed to screen for DEPRGs associated with survival. Consensus clustering was used for BLCA subtyping. TME characteristics were evaluated by CIBERSORT, ESTIMATE and immune checkpoint genes (ICGs). Following univariate COX regression and LASSO analyses with pyroptosis-related DEGs, the risk model and nomogram were constructed with TCGA dataset and validated in the GEO dataset. Furthermore, therapeutic responses in high- and low-risk groups were compared using TIDE and GDSC databases. Two pyroptosis-related subtypes (Cluster 1 and 2) were identified based on expression patterns of GSDMA and CHMP4C. Bioinformatic analyses showed that cluster 1 had poor survival, more M0/M1/M2 macrophages, higher immune/stromal/ESTIMATE scores, and higher expression levels of ICGs. A 15-gene signature for predicting prognosis could classify patients into high- and low-risk groups. Furthermore, the correlation of risk scores with TIDE score and IC₅₀ showed that patients in low-risk group were more sensitive to immunotherapy, whereas patients in high-risk group could better benefit from chemotherapy. Our study identified two novel pyroptosis-related subtypes and constructed a risk model, which can predict the prognosis, improve our understanding the role of PRGs in BLCA, and guide chemotherapy and immunotherapy.

Immune landscape and risk prediction based on pyroptosis-related molecular subtypes in triple-negative breast cancer

The survival outcome of triple-negative breast cancer (TNBC) remains poor, with difficulties still existing in prognosis assessment and patient stratification. Pyroptosis, a newly discovered form of programmed cell death, is involved in cancer pathogenesis and progression. The role of pyroptosis in the tumor microenvironment (TME) of TNBC has not been fully elucidated. In this study, we disclosed global alterations in 58 pyroptosis-related genes at somatic mutation and transcriptional levels in TNBC samples collected from The Cancer Genome Atlas and Gene Expression Omnibus databases. Based on the expression patterns of genes related to pyroptosis, we identified two molecular subtypes that harbored different TME characteristics and survival outcomes. Then, based on differentially expressed genes between two subtypes, we established a 12-gene score with robust efficacy in predicting short- and long-term overall survival of TNBC. Patients at low risk exhibited a significantly better prognosis, more antitumor immune cell infiltration, and higher expression of immune checkpoints including PD-1, PD-L1, CTLA-4, and LAG3. The comprehensive analysis of the immune landscape in TNBC indicated that alterations in pyroptosis-related genes were closely related to the formation of the immune microenvironment and the intensity of the anticancer response. The 12-gene score provided new information on the risk stratification and immunotherapy strategy for highly heterogeneous patients with TNBC.

The Relationship of Pyroptosis-Related Genes, Patient Outcomes, and Tumor-Infiltrating Cells in Bladder Urothelial Carcinoma (BLCA)

Introduction: The role of pyroptosis and its effects on tumor-infiltrating cells (TICs) in the pathogenesis and treatment outcomes of patients with bladder urothelial carcinoma (BLCA) remains unclear.

Methods: We conducted a bioinformatics analysis on the pyroptosis-related genes (PRGs) and TICs using data from public domains, and evaluated their impact on the pathogenesis and clinical outcomes of BLCA patients. A risk score based on PRGs and a prognostic risk model that incorporated patient demographics, tumor characteristics, and differentially expressed genes (DEGs) were developed.

Results: Twenty-three DEGs of 52 PRGs were identified in BLCA and normal samples from the TCGA database. Missense mutations and single nucleotide polymorphisms in PRGs are the most common genetic abnormalities. Patients with high PRG risk scores showed an inferior survival compared to those with low risk scores. The prognostic risk model based on patient demographics, tumor characteristics, and DEGs showed good predictive values for patient survival at 1, 3, and 5 years in BLCA patients. Caspase-8 (CASP8) was the only intersection gene of the prognostic genes, DEGs, and different genes expressed in tissue. Patients with a high CASP8 expression had improved survival, and an increased CASP8 expression level was observed in activated CD4 memory T cells, follicular T helper cells, resting NK cells, M0 macrophages, and activated dendritic cells. CASP8 expression also showed a positive correlation with the IL7R expression—a key cell marker of CD4 memory T cells. CASP8 expression also showed correlations with immune checkpoints (PDCD1, CD274, and CTLA4) and response to immune checkpoint inhibitors.

Conclusion: Our data suggest that PRGs, especially CASP8, showed strong associations with patient outcomes and TICs in BLCA. If validated, these results could potentially aid in the prognostication and guide treatment in BLCA patients.

Novel Pyroptosis-Related Gene Signatures Identified as the Prognostic Biomarkers for Bladder Carcinoma

Background

Bladder carcinoma (BLCA) is a common malignant tumor with high morbidity and mortality in the urinary system. Pyroptosis is a pattern of programmed cell death that is closely associated with progression of tumors. Therefore, it is significant to probe the expression of pyroptosis-related genes (PRGs) in BLCA.

Methods

The differentially expressed genes in normal and BLCA tissues were first obtained from the Cancer Genome Atlas (TCGA) database analysis, as well as PRGs from the National Center for Biotechnology Information (NCBI) database, intersecting to obtain differentially expressed pyroptosis-related genes (DEPRGs) in BLCA. With the construction of a prognostic model of pyroptosis by regression analysis, we derived and validated key genes, which were ascertained as a separate prognostic marker by individual prognostic and clinical relevance analysis. In addition, we gained six immune cells from the Tumor Immune Evaluation Resource (TIMER) website and analyzed the relationship between pyroptosis prognostic genes and immune infiltration.

Result

Our results revealed that 31 DEPRGs were available by comparing normal and BLCA tissues with |log2 (fold change, FC)| &gt; 0.5 and FDR &lt;0.05. Four key genes (CRTAC1, GSDMB, AIM2, and FOXO3) derived from the pyroptosis prognostic model were experimentally validated for consistent expression in BLCA patients. Following risk scoring, the low-risk group of BLCA patients had noticeably higher overall survival (OS) than the high-risk group (p &lt; 0.001). Risk score was still an independent prognostic factor (HR = 1.728, 95% CI =1.289–2.315, p &lt; 0.001). In addition, we found remarkable correlations among the expression of pyroptosis-related prognostic genes and the immune infiltration of CD4+ T cells, CD8+ T cells, B cells, dendritic cells, macrophages, and neutrophils.

Conclusion

Genes (CRTAC1, GSDMB, AIM2, and FOXO3) associated with pyroptosis are potential BLCA prognostic biomarkers that act as an essential part in the predictive prognosis of survival and immunotherapy of BLCA.

Identification of Pyroptosis-Related Gene Signatures and Construction of the Risk Model to Predict BCR in Prostate Cancer

Prostate cancer is one of the most common malignant tumors in men. Pyroptosis is related to tumor immune infiltration and tumor microenvironment (TME) and has been confirmed to be related to the progression of a variety of tumors. However, the relationship between prostate cancer and pyroptosis, as well as TME and tumor immune infiltration, has not been discussed yet. We obtained and combined the RNA-seq data of prostate cancer from TCGA and GEO databases, analyzed the differential expression of pyroptosis-related genes (PRGs), and divided them into two groups according to the PRG expression level. The relationship between pyroptosis subtypes and the TME of prostate cancer was further verified, and the differential expression genes (DEGs) in the two subtypes were identified. The relationship between the DEGs and clinicopathology was explored and KEGG and GO enrichment analysis was conducted; it was found that most DEGs were enriched in immune-related pathways. Then, we randomly divided datasets into training and testing sets, performed the LASSO and multicox progression analysis, selected eight genes as prognostic signatures and used the eight genes, calculated the risk score, and then separated the entire cohort into high- and low-risk groups. The prognosis between two groups and the 1-, 3-, and 5-year ROC curves of biochemical relapse (BCR) were verified in training, testing, and the entire cohort, respectively. The TME, CSC index, mutation, and drug susceptibility were also discussed.

Genome-wide Exploration of a Pyroptosis-Related Long Non-Coding RNA Signature Associated With the Prognosis and Immune Response in Patients With Bladder Cancer

Background: Bladder cancer (BLCA) is a malignant tumor with a complex molecular mechanism and high recurrence rate in the urinary system. Studies have shown that pyroptosis regulates tumor cell proliferation and metastasis and affects the prognosis of cancer patients. However, the role of pyroptosis-related (PR) genes or long non-coding RNAs (lncRNAs) in BLCA development is not fully understood.

Methods: We comprehensively analyzed the molecular biological characteristics of PR genes in BLCA, including copy number variation, mutations, expression and prognostic value based on TCGA database. We then identified PR lncRNAs with prognostic value based on the expression of PR genes and performed a consistent clustering analysis of 407 BLCA patients according to the expression of prognosis-related PR lncRNAs and identified two clusters. The least absolute shrinkage and selection operator (LASSO) regression was used to establish a PR lncRNA signature and calculate the risk score associated with the prognosis of patients with BLCA. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) were used to evaluate the possible functions of PR lncRNA signature. We also evaluated the relationship between the risk score and tumor immune microenvironment (TIME).

Results: A total of 33 PR genes were obtained in our study and 194 prognosis-related PR lncRNAs were identified. We also constructed a signature consisting of eight-PR-lncRNAs and divided patients into high- and low-risk groups. The overall survival rate of patients with a high risk was significantly lower than patients with a low risk. The risk score was significantly correlated with the degree of infiltration of multiple immune cell subtypes and positively correlated with multiple immune checkpoint genes expression in BLCA. Enrichment analyses showed that these lncRNAs are involved in human immune regulatory functions and immune-related pathways.

Conclusion: Our study comprehensively studied the molecular biological characteristics of PR genes BLCA, and the eight-PR-lncRNA signature we identified might play a crucial role in tumor immunity and may be able to predict the prognosis of BLCA patients, providing a theoretical basis for an in-depth study of the relationship between the prognosis and TIME.