A novel pyroptosis-related prognostic lncRNAs signature, tumor immune microenvironment and the associated regulation axes in bladder cancer

Disulfidptosis related immune genes drive prognostic model development and tumor microenvironment characterization in bladder urothelial carcinoma

The intricate nature and varied forms of bladder urothelial carcinoma (BLCA) highlight the need for new indicators to define tumor prognosis. Disulfidptosis, a novel form of cell death, is closely linked to BLCA progression, prognosis, and treatment outcomes. Our current goal is to develop a novel disulfidptosis-related immune prognostic model to enhance BLCA treatment strategies. Utilizing RNA-seq data from The Cancer Genome Atlas (TCGA) , which included 419 patients (19 normal, 400 tumor), we performed weighted gene co-expression network analysis (WGCNA) to identify disulfidptosis-associated immune genes. Through multivariate Cox regression, and the least absolute shrinkage and selection operator (LASSO) regularization, we established a disulfidptosis-related immune risk scoring system. A nomogram combining risk score and clinical features predicted prognosis. Model performance was validated through survival curve analysis and independent validation cohort. Immune checkpoints, cell infiltration, and tumor mutation load were assessed. Differential gene enrichment analysis was conducted. Prognostic genes were validated via in vitro experiments. Eight immune genes related to disulfidptosis were identified and verified in BLCA prognosis. A prognostic model outperformed previous ones in predicting overall survival (OS) for high- and low-risk groups. Patients with low-risk scores had higher OS rates and tumor mutation burden (TMB) compared to high-risk score patients. CD4 memory T cells, CD8 T cells, M1 macrophages, and resting NK cells were found to be higher in the low-risk group. Immune checkpoint inhibitor (ICI) treatment may be more effective for the low-risk score group. High-risk score group exhibited stronger correlation with cancer malignant pathways. Knocking out tumor necrosis factor receptor superfamily member 12 A (TNFRSF12A) inhibits BLCA cell proliferation and invasion while overexpressing it has the opposite effect. We constructed a novel risk score model that combines disulfidptosis and immune genes, demonstrating good prognostic prediction performance. We discovered and verified that the TNFRSF12A gene is an oncogene in BLCA, which may help provide personalized guidance for individualized treatment and immunotherapy selection for BLCA patients to a certain extent.

A pyroptosis-related lncRNA risk model for the prediction of prognosis and immunotherapy response in head and neck squamous cell carcinoma

Background

Recent research has highlighted pyroptosis as a key factor in cancer progression. This study aims to explore the association between pyroptosis-related signatures and overall survival (OS) in head and neck squamous cell carcinoma (HNSC) and develop a pyroptosis-related long non-coding RNA (lncRNA) risk model to predict prognosis and response to immunotherapy in HNSC.

Methods

We extracted expression data for 18 pyroptosis-related genes and identified lncRNA probes specific to HNSC by using datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Consensus clustering was performed to categorize HNSC patients into distinct subtypes. A six-lncRNA risk score model was constructed through univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses. We evaluated the predictive ability of the lncRNA model for patients' survival and immunotherapy response. Gene expression was evaluated using immunohistochemistry (IHC) and Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR).

Results

Our analysis revealed two distinct pyroptosis-related subtypes in HNSC patients, Cluster A and Cluster B. Notably, patients in Cluster B exhibited significantly poorer overall survival compared to those in Cluster A. Through differential expression analysis, we identified six lncRNAs (AC002331.1, CTA-384D8.35, RP11-291B21.2, AC006262.5, RP1-27K12.2, and RP11-54H7.4) that were differentially expressed between these clusters. A 6-lncRNA risk score model was developed, which successfully stratified patients into high- and low-risk groups with distinct overall survival outcomes. Validation using RT-qPCR confirmed the differential expression of these six lncRNAs in HNSC tumor tissues compared to adjacent normal tissues, we found that the expression of CTA-384D8.35 was significantly increased in the tumor group (t=-6.203, P<0.001). Furthermore, the 6-lncRNA risk score model demonstrated a significant association with patient response to immunotherapy, with the low-risk group exhibiting a higher objective response rate to immune checkpoint blockade (ICB) therapy and longer survival compared to the high-risk group.

Conclusion

Our study underscores the role of pyroptosis signatures in HNSC prognosis and identifies two distinct pyroptosis subtypes with differing survival outcomes. The six-lncRNA risk score model offers a valuable tool for predicting patient prognosis and potential benefits from ICB therapy. These findings highlight the importance of pyroptosis and associated lncRNAs in the tumor microenvironment, paving the way for novel targeted therapies in HNSC.

From diagnosis to therapy: The critical role of lncRNAs in hepatoblastoma

According to findings, long non-coding RNAs (lncRNAs) serves an integral part in growth and development of a variety of human malignancies, including Hepatoblastoma (HB). HB is a rare kind of carcinoma of the liver that mostly affects kids and babies under the age of three. Its manifestations include digestive swelling, abdominal discomfort, and losing weight. This thorough investigation digs into the many roles that lncRNAs serve in HB, giving views into their varied activities as well as possible therapeutic consequences. The function of lncRNAs in HB cell proliferation, apoptosis, migratory and penetrating capacities, epithelial-mesenchymal transition, and therapy tolerance is discussed. Various lncRNA regulatory roles are investigated in depth, yielding information on their effect on essential cell processes such as angiogenesis, apoptosis, immunity, and growth. Circulating lncRNAs are currently acknowledged as potential indications for the initial stages of identification of cancer, with the ability to diagnose as well as forecast. In addition to their diagnostic utility, lncRNAs provide curative opportunities as locations and actors, contributing to the expanding landscape of cancer research. Several HB-linked lncRNAs have been demonstrated to exhibit abnormal expression and are involved in tumor-like characteristics via DNA, RNA, or protein binding or encoding short peptides. As a result, a better knowledge of lncRNA instability might bring fresh perspectives into HB etiology as well as innovative strategies for HB early diagnosis and therapy. We describe the abnormalities of lncRNA expression in HB and their tumor-suppressive or carcinogenic activities during HB carcinogenesis in this study. Furthermore, we explore lncRNAs' diagnostic and therapeutic possibilities in HB.

Whole transcriptome sequencing identifies a competitive endogenous RNA network that regulates the immunity of bladder cancer

Several types of non-coding RNAs such as circRNAs, lncRNAs, and miRNAs have been identified to regulate mRNAs through the mechanism known as the competitive endogenous RNA (ceRNA) network. To explore the role of the ceRNA regulatory network in the immune microenvironment of bladder cancer, whole-transcriptome sequencing of bladder tumor and its peritumoral tissues from 38 bladder cancer patients, with a total of 63 samples, was performed to screen differentially expressed circ-, lnc-, mi-, and mRNAs to construct a circ/lnc-mi-mRNA regulatory network with pruning algorithms. We excavated a key immune-related gene BDNF to build the final ceRNA network as hsa-miR-107 sponged by hsa-circ-000211, AC108488.1, and LINC00163. Finally, a meta-analysis of 7 public datasets demonstrated that low expression of BDNF and high expression of hsa-miR-107 were associated with longer survival. Our study identified a ceRNA regulatory network as a potentially new prognostic marker and molecular therapeutic target of bladder cancer.

Carcinogenic roles of MAFG-AS1 in human cancers

The MAF bZIP transcription factor G-antisense RNA 1 (MAFG-AS1) is located on chromosome 17. MAFG-AS1 was upregulated in 15 human cancers. MAFG-AS1 not only suppresses 16 miRNAs but also directly impacts 22 protein-coding genes' expression. Notably, abnormal MAFG-AS1 expression is connected to clinicopathological characteristics and a worse prognosis in a variety of cancers. Moreover, MAFG-AS1 takes its part in the tumorigenesis and progression of various human malignancies by suppressing apoptosis and promoting proliferation, migration, invasion, aerobic glycolysis, ferroptosis, angiogenesis, EMT, and metastasis. Besides, it can predict treatment effectiveness in ER + breast cancer, urothelial bladder carcinoma, and liver cancer by functioning as a trigger of resistance to tamoxifen, sorafenib, and cisplatin. This study systematically presents the functions of MAFG-AS1 in various cancers, as well as the findings of bioinformatics analyses of the MAFG-AS1, which should give clear advice for future research.

A risk model based on lncRNA-miRNA-mRNA gene signature for predicting prognosis of patients with bladder cancer

OBJECTIVES

We aimed to analyze lncRNAs, miRNAs, and mRNA expression profiles of bladder cancer (BC) patients, thereby establishing a gene signature-based risk model for predicting prognosis of patients with BC.

METHODS

We downloaded the expression data of lncRNAs, miRNAs and mRNA from The Cancer Genome Atlas (TCGA) as training cohort including 19 healthy control samples and 401 BC samples. The differentially expressed RNAs (DERs) were screened using limma package, and the competing endogenous RNAs (ceRNA) regulatory network was constructed and visualized by the cytoscape. Candidate DERs were screened to construct the risk score model and nomogram for predicting the overall survival (OS) time and prognosis of BC patients. The prognostic value was verified using a validation cohort in GSE13507.

RESULTS

Based on 13 selected. lncRNAs, miRNAs and mRNA screened using L1-penalized algorithm, BC patients were classified into two groups: high-risk group (including 201 patients ) and low risk group (including 200 patients). The high-risk group's OS time ( hazard ratio [HR], 2.160; 95% CI, 1.586 to 2.942; P= 5.678e-07) was poorer than that of low-risk groups' (HR, 1.675; 95% CI, 1.037 to 2.713; P= 3.393 e-02) in the training cohort. The area under curve (AUC) for training and validation datasets were 0.852. Younger patients (age ⩽ 60 years) had an improved OS than the patients with advanced age (age > 60 years) (HR 1.033, 95% CI 1.017 to 1.049; p= 2.544E-05). We built a predictive model based on the TCGA cohort by using nomograms, including clinicopathological factors such as age, recurrence rate, and prognostic score.

CONCLUSIONS

The risk model based on 13 DERs patterns could well predict the prognosis for patients with BC.

Identification of necroptosis-related long non-coding RNAs prognostic signature and the crucial lncRNA in bladder cancer

BACKGROUND

Research on the relationships between long non-coding RNAs (lncRNAs) and cancer is attractive and has progressed very rapidly. Necroptosis-related biomarkers can potentially be used for predicting the prognosis of cancer patients. This study aimed to establish a necroptosis-related lncRNA (NPlncRNA) signature to predict the prognosis of patients with bladder cancer (BCa).

METHODS

First, NPlncRNAs were identified using Pearson correlation analysis and machine learning algorithms, including SVM-RFE, least absolute shrinkage and selection operator (LASSO) regression, and random forest. The prognostic NPlncRNA signature was constructed using univariate and multivariate Cox regression analyses and the diagnostic efficacy and clinically predictive efficiency were evaluated and validated. The biological functions of the signature were analysed using gene set enrichment analysis (GSEA) and functional enrichment analysis. We further integrated the RNA-seq dataset (GSE133624) with our outcomes to reveal the crucial NPlncRNA that was functionally verified by assessing cell viability, proliferation, and apoptosis in BCa cells.

RESULTS

The prognostic NPlncRNAs signature was composed of PTOV1-AS2, AC083862.2, MAFG-DT, AC074117.1, AL049840.3, and AC078778.1, and a risk score based on this signature was proven to be an independent prognostic factor for the BCa patients, indicated by poor overall survival (OS) of patients in the high-risk group. Additionally, the NPlncRNAs signature had a higher diagnostic validity than that of other clinicopathological variables, with a greater area under the receptor operating characteristic and concordance index curves. A nomogram established by integrating clinical variables and risk score confirmed that the signature can accurately predict the OS of patients and has high clinical practicability. Functional enrichment analysis and GSEA revealed that some cancer-related and necroptosis-related pathways were enriched in high-risk groups. The crucial NPlncRNA MAFG-DT was associated with poor prognosis and was highly expressed in BCa cells. MAFG-DT silencing notably inhibited proliferation and enhanced apoptosis of BCa cells.

CONCLUSIONS

A novel prognostic NPlncRNAs signature was identified in BCa in this study, which provides potential therapeutic targets among which MAFG-DT plays critical roles in the tumorigenesis of BCa.

Sequence Variants in PSMB8/PSMB9 Immunoproteasome Genes and Risk of Urothelial Bladder Carcinoma

BACKGROUND

The PSMB8 and PSMB9 immunoproteasome genes are essential in cell processes, such as decisions on cell survival or death, the cell cycle, and cellular differentiation. Because recent evidence has demonstrated an immunological role for proteasomes in various malignancies, including urothelial bladder carcinoma (UBC), we evaluated single nucleotide polymorphisms (SNPs) in PSMB9 and PSMB8. We determined any associations between these SNPs and susceptibility to UBC in the Saudi community.

METHODS

Samples of genomic DNA were taken from buccal cells of 111 patients with UBC and 78 healthy controls. TaqMan Real-Time PCR was used to determine genotype distributions and allele frequencies for the PSMB9 rs17587 G>A and PSMB8 rs2071543 G>T SNPs. We used SNPStats (https://www.snpstats.net) to choose each SNP's best interactive inheritance model.

RESULTS

The PSMB9 rs17587 SNP was associated with the risk of UBC (odds ratio [OR] = 5.21, P < 0.0001). In contrast, the PSMB8 rs2071543 SNP showed no association with UBC risk (OR = 1.13, P = 0.7871). In terms of genotypic distribution, the rs17587 G>A SNP was more frequent in UBC cases than controls in both the dominant (OR = 7.5; 95% confidence interval, 3.7-15.1; P = 0.0051) and recessive (OR = 17.11, 95% confidence interval 5.1-57.4; P = 0.0026) models. Genotypic distribution of the PSMB8 rs2071543 G>T SNP was not significantly different between cases and controls in any interactive inheritance models (P > 0.05).

CONCLUSION

These results suggest a potential role for PSMB9 as a biomarker for increased UBC risk. Discovering more genetic variants within immunoproteasome genes related to antigen presentation could help further our understanding of this risk.

A review on the roles and molecular mechanisms of MAFG-AS1 in oncogenesis

Long non-coding RNAs (lncRNAs) have more than 200 nucleotides and do not encode proteins. At the same time, they can regulate various biological functions and therefore play an essential role as oncogenes or tumor suppressors in human cancers. MAFG-AS1 is an antisense RNA of MAF BZIP Transcription Factor G (MAFG) located at chromosome 17q25.3 head-to-head with the MAFG encoding gene containing a transcript size of 1895 bp. Accumulating evidence shows that MAFG-AS1 is overexpressed in many cancers, functions as an oncogene, and is significantly associated with poor clinical characteristics and prognosis. In this review, we first discuss the recent literature regarding the role of MAFG-AS1 in different cancers as well as its diagnostic and prognostic values. Then we will provide insights into its biological functions, such as its role in cancer progression, competing endogenous RNA (ceRNA) activity, regulation of EMT, glycolysis, energy metabolism, transcription factors, proteasomal degradation, and signaling pathways.

Identification of platinum resistance-related gene signature for prognosis and immune analysis in bladder cancer

Purpose: Currently, there is limited knowledge about platinum resistance-related long non-coding RNAs (lncRNAs) in bladder cancer. We aim to identify platinum resistance-related lncRNAs and construct a risk model for accurate prognostic prediction of bladder cancer. Methods: Transcriptomic and clinical data were extracted from The Cancer Genome Atlas (TCGA) database, and platinum resistance-related genes were obtained from HGSOC-Platinum. The platinum resistance-related lncRNAs were obtained by the Spearman correlation analysis. Then, we constructed a risk score model through Cox regression analysis and the LASSO algorithm. The model was verified by analyzing the median risk score, Kaplan-Meier curve, receiver operating characteristic (ROC) curve, and heatmap. We also developed a nomogram and examined the relationship between the risk score model, immune landscape, and drug sensitivity. Lastly, we assessed the differential expression of PRR-lncRNAs in the cisplatin-resistant bladder cancer cell line and the normal bladder cancer cell line using qRT-PCR. Results: We developed and validated an eight-platinum resistance-related lncRNA risk model for bladder cancer. The risk model showed independent prognostic significance in univariate and multivariate Cox analyses. Based on multivariate analysis, we developed a nomogram. The modified model is both good predictive and clinically relevant after evaluation. Furthermore, immune-related and drug-sensitivity analyses also showed significant differential expression between high and low-risk groups. The qRT-PCR demonstrated that most of the lncRNAs were upregulated in cisplatin-resistance cancerous tissues than in control tissues. Conclusion: We have developed a predictive model based on eight platinum resistance-related lncRNAs, which could add meaningful information to clinical decision-making.

Analysis of Long Noncoding RNAs-Related Regulatory Mechanisms in Duchenne Muscular Dystrophy Using a Disease-Related lncRNA-mRNA Pathway Network

Objective

This study aimed to investigate the molecular regulatory mechanisms underpinning Duchenne muscular dystrophy (DMD).

Methods

Using microarray data, differentially expressed long noncoding RNAs (DELs) and DMD-related differentially expressed mRNAs (DEMs) were screened based on the comparative toxicogenomics database, using a cutoff of |log₂ fold change| > 1 and false discovery rate (FDR) < 0.05. Then, protein-protein interaction (PPI), coexpression network of lncRNA-mRNA, and DMD-related lncRNA-mRNA pathway networks were constructed, and functional analyses of the genes in the network were performed. Finally, the proportions of immune cells infiltrating the muscle tissues in DMD were analyzed, and the correlation between the immune cells and expression of the DELs/DEMs was studied.

Results

A total of 46 DELs and 313 DMD-related DEMs were identified. The PPI network revealed STAT1, VEGFA, and CCL2 to be the top three hub genes. The DMD-related lncRNA-mRNA pathway network comprising two pathways, nine DELs, and nine DMD-related DEMs showed that PYCARD, RIPK2, and CASP1 were significantly enriched in the NOD-like receptor signaling pathway, whereas MAP2K2, LUM, RPS6, PDCD4, TWIST1, and HIF1A were significantly enriched with proteoglycans in cancers. The nine DELs in this network were DBET, MBNL1-AS1, MIR29B2CHG, CCDC18-AS1, FAM111A-DT, GAS5, LINC01290, ATP2B1-AS1, and PSMB8-AS1.

Conclusion

The nine DMD-related DEMs and DELs identified in this study may play important roles in the occurrence and progression of DMD through the two pathways of the NOD-like receptor signaling pathway and proteoglycans in cancers.