An 18-gene signature based on glucose metabolism and DNA methylation improves prognostic prediction for urinary bladder cancer

Exploring prognostic DNA methylation genes in bladder cancer: a comprehensive analysis

The current study aimed to investigate the status of genes with prognostic DNA methylation sites in bladder cancer (BLCA). We obtained bulk transcriptome sequencing data, methylation data, and single-cell sequencing data of BLCA from public databases. Initially, Cox survival analysis was conducted for each methylation site, and genes with more than 10 methylation sites demonstrating prognostic significance were identified to form the BLCA prognostic methylation gene set. Subsequently, the intersection of marker genes associated with epithelial cells in single-cell sequencing analysis was obtained to acquire epithelial cell prognostic methylation genes. Utilizing ten machine learning algorithms for multiple combinations, we selected key genes (METRNL, SYT8, COL18A1, TAP1, MEST, AHNAK, RPP21, AKAP13, RNH1) based on the C-index from multiple validation sets. Single-factor and multi-factor Cox analyses were conducted incorporating clinical characteristics and model genes to identify independent prognostic factors (AHNAK, RNH1, TAP1, Age, and Stage) for constructing a Nomogram model, which was validated for its good diagnostic efficacy, prognostic prediction ability, and clinical decision-making benefits. Expression patterns of model genes varied among different clinical features. Seven immune cell infiltration prediction algorithms were used to assess the correlation between immune cell scores and Nomogram scores. Finally, drug sensitivity analysis of Nomogram model genes was conducted based on the CMap database, followed by molecular docking experiments. Our research offers a reference and theoretical basis for prognostic evaluation, drug selection, and understanding the impact of DNA methylation changes on the prognosis of BLCA.

Screening a knowledge-based library of low molecular weight compounds against the proline biosynthetic enzyme 1-pyrroline-5-carboxylate 1 (PYCR1)

Δ1-pyrroline-5-carboxylate reductase isoform 1 (PYCR1) is the last enzyme of proline biosynthesis and catalyzes the NAD(P)H-dependent reduction of Δ1-pyrroline-5-carboxylate to L-proline. High PYCR1 gene expression is observed in many cancers and linked to poor patient outcomes and tumor aggressiveness. The knockdown of the PYCR1 gene or the inhibition of PYCR1 enzyme has been shown to inhibit tumorigenesis in cancer cells and animal models of cancer, motivating inhibitor discovery. We screened a library of 71 low molecular weight compounds (average MW of 131 Da) against PYCR1 using an enzyme activity assay. Hit compounds were validated with X-ray crystallography and kinetic assays to determine affinity parameters. The library was counter-screened against human Δ1-pyrroline-5-carboxylate reductase isoform 3 and proline dehydrogenase (PRODH) to assess specificity/promiscuity. Twelve PYCR1 and one PRODH inhibitor crystal structures were determined. Three compounds inhibit PYCR1 with competitive inhibition parameter of 100 μM or lower. Among these, (S)-tetrahydro-2H-pyran-2-carboxylic acid (70 μM) has higher affinity than the current best tool compound N-formyl-l-proline, is 30 times more specific for PYCR1 over human Δ1-pyrroline-5-carboxylate reductase isoform 3, and negligibly inhibits PRODH. Structure-affinity relationships suggest that hydrogen bonding of the heteroatom of this compound is important for binding to PYCR1. The structures of PYCR1 and PRODH complexed with 1-hydroxyethane-1-sulfonate demonstrate that the sulfonate group is a suitable replacement for the carboxylate anchor. This result suggests that the exploration of carboxylic acid isosteres may be a promising strategy for discovering new classes of PYCR1 and PRODH inhibitors. The structure of PYCR1 complexed with l-pipecolate and NADH supports the hypothesis that PYCR1 has an alternative function in lysine metabolism.

Novel Fragment Inhibitors of PYCR1 from Docking-Guided X-ray Crystallography

The proline biosynthetic enzyme Δ1-pyrroline-5-carboxylate (P5C) reductase 1 (PYCR1) is one of the most consistently upregulated enzymes across multiple cancer types and central to the metabolic rewiring of cancer cells. Herein, we describe a fragment-based, structure-first approach to the discovery of PYCR1 inhibitors. Thirty-seven fragment-like carboxylic acids in the molecular weight range of 143-289 Da were selected from docking and then screened using X-ray crystallography as the primary assay. Strong electron density was observed for eight compounds, corresponding to a crystallographic hit rate of 22%. The fragments are novel compared to existing proline analog inhibitors in that they block both the P5C substrate pocket and the NAD(P)H binding site. Four hits showed inhibition of PYCR1 in kinetic assays, and one has lower apparent IC50 than the current best proline analog inhibitor. These results show proof-of-concept for our inhibitor discovery approach and provide a basis for fragment-to-lead optimization.

LncRNA LINC00592 mediates the promoter methylation of WIF1 to promote the development of bladder cancer

Epigenetic alteration is a key feature that contributes to the progression of bladder cancer (BC) and long non-coding RNAs serve crucial role in the epigenetic modulation. This study was designed to explore the epigenetic regulation of LINC00592 in BC. LINC00592 expression in BC was examined. Then, LINC00592 was silenced in BC cell followed by cell behavior analyses using CCK-8, transwell, western blot, or flow cytometry. Potential downstream target of LINC00592 was explored using RNA pull-down assay and methylation of WIF1 was determined using methylated-specific PCR. In addition, WIF1 or/and LINC00592 were silenced in BC cells followed by cell behavior analyses to explore the regulation between them. Upregulation of LINC00592 was significantly detected in BC tissues and cells. In BC cells silencing LINC00592 suppressed the proliferation, migration, and epithelial-mesenchymal transitions (EMT), but enhanced apoptosis. Moreover, LINC00592 recruited DNMT1, DNMT3A, and DNMT3B to enhance WIF1 promoter methylation. In addition, WIF1 overexpression suppressed the proliferation, migration, as well as EMT, but enhanced apoptosis. Silencing WIF1 significantly attenuated the role of silencing LINC00592 in suppressing the proliferative, migratory, and EMT ability of BC cells, and increasing the apoptosis. LINC00592 promoted the growth and metastasis of BC via enhancing the promoter methylation of WIF1 and decreasing WIF1 transcription.

Identification of novel lactate metabolism-related lncRNAs with prognostic value for bladder cancer

Background: Bladder cancer (BCA) has high recurrence and metastasis rates, and current treatment options show limited efficacy and significant adverse effects. It is crucial to find diagnostic markers and therapeutic targets with clinical value. This study aimed to identify lactate metabolism-related lncRNAs (LM_lncRNAs) to establish a model for evaluating bladder cancer prognosis. Method: A risk model consisting of lactate metabolism-related lncRNAs was developed to forecast bladder cancer patient prognosis using The Cancer Genome Atlas (TCGA) database. Kaplan‒Meier survival analysis, receiver operating characteristic curve (ROC) analysis and decision curve analysis (DCA) were used to evaluate the reliability of risk grouping for predictive analysis of bladder cancer patients. The results were also validated in the validation set. Chemotherapeutic agents sensitive to lactate metabolism were assessed using the Genomics of Drug Sensitivity in Cancer (GDSC) database. Results: As an independent prognostic factor for patients, lactate metabolism-related lncRNAs can be used as a nomogram chart that predicts overall survival time (OS). There were significant differences in survival rates between the high-risk and low-risk groups based on the Kaplan‒Meier survival curve. decision curve analysis and receiver operating characteristic curve analysis confirmed its good predictive capacity. As a result, 22 chemotherapeutic agents were predicted to positively affect the high-risk group. Conclusion: An lactate metabolism-related lncRNA prediction model was proposed to predict the prognosis for patients with bladder cancer and chemotherapeutic drug sensitivity in high-risk groups, which provided a new idea for the prognostic evaluation of the clinical treatment of bladder cancer.

Exosomes from PYCR1 knockdown bone marrow mesenchymal stem inhibits aerobic glycolysis and the growth of bladder cancer cells via regulation of the EGFR/PI3K/AKT pathway

Bladder cancer (BC) is a heterogeneous disease, and pyrroline‑5‑carboxylate reductase 1 (PYCR1) can promote the proliferation and invasion of BC cells and accelerate BC progression. In the present study, si‑PYCR1 was loaded into bone marrow mesenchymal stem cell (BMSC)‑derived exosomes (Exos) in BC. First, PYCR1 levels in BC tissues/cells were assessed, and cell proliferation, invasion, and migration were evaluated. Aerobic glycolysis levels (glucose uptake, lactate production, ATP production, and the expression of relevant enzymes) and the EGFR/PI3K/AKT pathway phosphorylation levels were determined. PYCR1‑EGFR interactions were examined by co‑immunoprecipitation experiments. RT4 cells transfected with oe‑PYCR1 were treated with EGFR inhibitor CL‑387785. Exos were loaded with si‑PYCR1 and identified, followed by an assessment of their effects on aerobic glycolysis and malignant cell behaviors. Nude mouse models of xenograft tumors were established by injecting mice with Exo‑si‑PYCR1 and Exo‑si‑PYCR1. PYCR1 was upregulated in BC cells, with the highest expression observed in T24 cells and the lowest expression in RT4 cells. Following PYCR1 knockdown, the malignant behaviors of T24 cells and aerobic glycolysis were decreased, while PYCR1 overexpression in RT4 cells averted these trends. PYCR1 interacted with EGFR, and CL‑387785 inhibited the EGFR/PI3K/AKT pathway and attenuated the effects of PYCR1 overexpression on RT4 cells but had no effect on PYCR1 expression. Exo‑si‑PYCR1 showed stronger inhibitory effects on aerobic glycolysis and on the malignant behaviors of T24 cells than si‑PYCR1. Exo‑si‑PYCR1 blocked xenograft tumor growth and had good biocompatibility. Briefly, PYCR1 knocking loaded by BMSC‑derived Exos suppressed aerobic glycolysis and BC growth via the PI3K/AKT pathway by binding to EGFR.

A novel signature of aging-related genes associated with lymphatic metastasis for survival prediction in patients with bladder cancer

Background

The predominant and most prevalent form of metastatic bladder cancer (BCa) is lymphatic metastasis, which is associated with a highly dismal prognosis for patients. Aging-related genes (ARGs) are believed to contribute significantly to tumor development. However, the effect of ARGs on lymphatic metastasis of BCa is unclear. This research sought to establish a prognosis model based on ARGs associated with lymphatic metastasis in BCa.

Methods

We downloaded BCa data from the TCGA and GEO databases and ARGs from the Aging Atlas database. The least absolute shrinkage and selection operator (LASSO) approach was applied to obtain the characteristic ARGs of risk signature in the TCGA cohort. Verification was done using the GSE13507 dataset. The R package 'ConsensusClusterPlus' was employed to identify the molecular subtypes based on the characteristic ARGs. Protein-Protein interaction network, MCODE analysis, enrichment analysis (KEGG, GO, GSEA), and immune infiltration analysis were performed to investigate underlying mechanisms. EdU, migration and invasion assays, wound healing assays, immunofluorescence staining, and quantitative polymerase chain reaction were conducted to evaluate the impact of ELN on the proliferative, migratory, and invasive capacities of BCa cells.

Results

We identified 20 differently expressed ARGs. A four ARGs risk signature (EFEMP1, UCHL1, TP63, ELN) was constructed in the TCGA cohort. The high-risk group (category) recorded a reduced overall survival (OS) rate relative to the low-risk category (hazard ratio, 2.15; P <0.001). The risk score could predict lymphatic metastasis in TCGA cohort (AUC=0.67). The GSE13507 dataset was employed to verify the validity of this risk score. Based on the four ARGs, two distinct aging profiles (Cluster 1 and Cluster 2) were discovered utilizing the ConsensusClusterPlus, and Cluster 2 possessed a favorable OS in contrast with Cluster 1 (hazard ratio, 0.69; P =0.02). Classical tumor signaling pathways, ECM-associated signaling pathways, and immune-related signaling pathways participate in BCa progression. ELN recombinant protein affected the expression of collagen and increased migration and invasiveness in BCa cells.

Conclusion

We constructed a four-ARG risk signature and identified two aging molecular subtypes. This signature could serve as an effective survival predictor for patients with BCa.

Screening ANLN and ASPM as bladder urothelial carcinoma-related biomarkers based on weighted gene co-expression network analysis

Introduction: Bladder cancer (BLCA) is one of the most common malignancies in the urinary system with a poor prognosis and high treatment costs. Identifying potential prognostic biomarkers is significant for exploring new therapeutic and predictive targets of BLCA.

Methods: In this study, we screened differentially expressed genes using the GSE37815 dataset. We then performed a weighted gene co‐expression network analysis (WGCNA) to identify the genes correlated with the histologic grade and T stage of BLCA using the GSE32548 dataset. Subsequently, Kaplan Meier survival analysis and Cox regression were used to further identify prognosis‐related hub genes using the datasets GSE13507 and TCGA‐BLCA. Moreover, we detected the expression of the hub genes in 35 paired samples, including BLCA and paracancerous tissue, from the Shantou Central Hospital by qRT‐polymerase chain reaction.

Results: This study showed that Anillin (ANLN) and Abnormal spindle-like microcephaly-associated gene (ASPM) were prognostic biomarkers for BLCA. High expression of ANLN and ASPM was associated with poor overall survival.The qRT‐PCR results revealed that ANLN and ASPM genes were upregulated in BLCA, and there was a correlation between the expression of ANLN and ASPM in cancer tissues and paracancerous tissue. Additionally, the increasing multiples in the ANLN gene was obvious in high-grade BLCA.

Discussion: In summary, this preliminary exploration indicated a correlation between ANLN and ASPM expression. These two genes, serving as the risk factors for BLCA progression, might be promising targets to improve the occurrence and progression of BLCA.

scBPGRN: Integrating single-cell multi-omics data to construct gene regulatory networks based on BP neural network

The deterioration and metastasis of cancer involve various aspects of genomic changes, including genomic DNA changes, epigenetic modifications, gene expression, and other complex interactions. Therefore, integrating single-cell multi-omics data to construct gene regulatory networks containing more omics information is of great significance for understanding the pathogenesis of cancer. In this article, an algorithm integrating single-cell RNA sequencing data and DNA methylation data to construct a gene regulatory network based on the back-propagation (BP) neural network (scBPGRN) is proposed. This algorithm uses biweight extreme correlation coefficients to measure the correlation between factors and uses neural networks to calculate generalized weights to construct gene regulation networks. Finally, the node strength is calculated to identify the genes associated with cancer. We apply the scBPGRN algorithm to hepatocellular carcinoma (HCC) data. We construct a regulatory network and identify top-ranked genes, such as MYCBP, KLHL35, PRKCZ, and SERPINA6, as the key HCC-related genes. We analyze the top 100 genes, and the HCC-related genes are concentrated in the top 20. In addition, the single cell data is found to consist of two subpopulations. We also apply scBPGRN to two subpopulations. We analyze the top 50 genes in them, and the HCC-related genes are concentrated in the top 20. The consequences of functional enrichment analysis indicate that the gene regulatory network we have constructed is valid. Our results have been verified in several pieces of literature. This study provides a reference for the integration of single-cell multi-omics data to construct gene regulatory networks.

Mining of immunological and prognostic-related biomarker for cervical cancer based on immune cell signatures

Background

Immunotherapy has changed the therapeutic landscape of cervical cancer (CC), but has durable anti-tumor activity only in a subset of patients. This study aims to comprehensively analyze the tumor immune microenvironment (TIME) of CC and to mine biomarkers related to immunotherapy and prognosis.

Methods

The Cancer Genome Atlas (TCGA) data was utilized to identify heterogeneous immune subtypes based on survival-related immune cell signatures (ICSs). ICSs prognostic model was constructed by Cox regression analyses, and immunohistochemistry was conducted to verify the gene with the largest weight coefficient in the model. Meanwhile, the tumor immune infiltration landscape was comprehensively characterized by ESTIMATE, CIBERSORT and MCPcounter algorithms. In addition, we also analyzed the differences in immunotherapy-related biomarkers between high and low-risk groups. IMvigor210 and two gynecologic tumor cohorts were used to validate the reliability and scalability of the Risk score.

Results

A total of 291 TCGA-CC samples were divided into two ICSs clusters with significant differences in immune infiltration landscape and prognosis. ICSs prognostic model was constructed based on eight immune-related genes (IRGs), which showed higher overall survival (OS) rate in the low-risk group (P< 0.001). In the total population, time-dependent receiver operating characteristic (ROC) curves displayed area under the curve (AUC) of 0.870, 0.785 and 0.774 at 1-, 3- and 5-years. Immunohistochemical results showed that the expression of the oncogene (FKBP10) was negatively correlated with the degree of differentiation and positively correlated with tumor stage, while the expression of tumor suppressor genes (S1PR4) was the opposite. In addition, the low-risk group had more favorable immune activation phenotype and higher enrichment of immunotherapy-related biomarkers. The Imvigor210 and two gynecologic tumor cohorts validated a better survival advantage and immune efficacy in the low-risk group.

Conclusion

This study comprehensively assessed the TIME of CC and constructed an ICSs prognostic model, which provides an effective tool for predicting patient’s prognosis and accurate immunotherapy.

Analysis of prognostic oncogene filaggrin (FLG) wild-type subtype and its implications for immune checkpoint blockade therapy in bladder urothelial carcinoma

BACKGROUND

Bladder urothelial carcinoma (BLCA) is one of the most common urinary tract malignant tumors. Immune checkpoint blockade (ICB) therapy has significantly progressed the treatment of BLCA. This study aimed to investigate the role of specific genetic mutations that may serve as immune biomarkers for ICB therapy in BLCA.

METHODS

Mutation information and expression profiles were acquired from The Cancer Genome Atlas (TCGA) database. Integrated bioinformatics analysis was carried out to explore the subtypes with poor prognosis of BLCA. Functional enrichment analysis was also conducted. The infiltrating immune cells and the prediction of ICB response between different subtypes were explored using the immuCellAI algorithm. Cell Counting Kit-8 (CCK-8) and flow cytometry assays were conducted to explore the effect of filaggrin (FLG) knockdown in BLCA 5637 and T24 cell lines.

RESULTS

An overview of mutation information in BLCA patients was shown. FLG was identified to be strongly associated with the prognosis of BLCA patients and FLG wild-type was associated with poorer outcome. Prognostic FLG wild-type was divided into 2 subtypes (Sub1 and Sub2). Following an investigation of the subtypes, Sub2 of FLG wild-type was found to be associated with poorer outcome in BLCA. The differentially expressed genes (DEGs) between Sub1 and Sub2 were screened out and the DEGs were enriched in malignant tumor proliferation, DNA damage repair, and immune-related pathways. Furthermore, Sub2 of FLG wild-type was associated with infiltrated immune cells, and responded worse to ICB. Sub2 of FLG wild-type may be used as a biomarker to predict the prognosis of BLCA patients receiving ICB. The cellular experiments revealed that knockdown of FLG could suppress BLCA cell proliferation and promote apoptosis.

CONCLUSIONS

FLG is an oncogene that may affect the prognosis of BLCA patients through mutation. Sub2 of FLG wild-type is associated with poor prognosis and can be used to predict ICB response for BLCA treatment. This research provides a new basis and ideas for guiding the clinical application of BLCA immunotherapy.

Survival and clinicopathological significance of PYCR1 expression in cancer: A meta-analysis

Background

Proline metabolism is closely related to the occurrence and development of cancer. Δ1-Pyrroline-5-carboxylate reductase (PYCR) is the last enzyme in proline biosynthesis. As one of the enzyme types, PYCR1 takes part in the whole process of the growth, invasion, and drug resistance of cancer cells. This study investigated PYCR1 expressions in cancers together with their relationship to clinical prognosis.

Methods

A thorough database search was performed in PubMed, EMBASE, and Cochrane Library. RevMan5.3 software was used for the statistical analysis.

Results

Eight articles were selected, and 728 cancer patients were enrolled. The cancer types include lung, stomach, pancreatic ductal adenocarcinoma, hepatocellular carcinoma, and renal cell carcinoma. The meta-analysis results showed that the expression of PYCR1 was higher in the clinical stage III–IV group than that in the clinical stage I–II group (OR = 1.67, 95%CI: 1.03–2.71), higher in the lymph node metastasis group than in the non-lymph node metastasis group (OR = 1.57, 95%CI: 1.06–2.33), and higher in the distant metastasis group than in the non-distant metastasis group (OR = 3.46, 95%CI: 1.64–7.29). However, there was no statistical difference in PYCR1 expression between different tumor sizes (OR = 1.50, 95%CI: 0.89–2.53) and degrees of differentiation (OR = 0.82, 95%CI: 0.54–1.24).

Conclusion

PYCR1 had a high expression in various cancers and was associated with cancer volume and metastasis. The higher the PYCR1 expression was, the poorer the cancer prognosis was. The molecular events and biological processes mediated by PYCR1 might be the underlying mechanisms of metastasis.

Identification and verification of the pyroptosis-related prognostic signature and its associated regulatory axis in bladder cancer

Background: Pyroptosis is an inflammatory form of cell death triggered by certain inflammasomes. Accumulating studies have shown the involvement of pyroptosis in the proliferation, invasion, and metastasis and prognosis of cancer. The prognostic value of pyroptosis-related genes (PRGs) and their association with immune infiltration in bladder cancer have not yet been elucidated.

Methods: We performed a comprehensive analysis of the prognostic value and immune infiltrates of PRGs in bladder cancer using the TCGA dataset. qRT-PCR was also performed to verify our result.

Results: Among 33 PRGs, 14 PRGs were upregulated or downregulated in bladder cancer tissue versus normal tissue. We also summarized copy number variations and somatic mutations of PRGs in bladder cancer. By using consensus clustering analysis of PRGs with prognostic significance, we divided the bladder cancer cohort into two subtypes significantly by different prognosis and immune infiltration. Using the LASSO Cox regression analysis, a prognostic signature including six PRGs was constructed for bladder cancer and the patients could be classified into a low- or high-risk group. Interestingly, this prognostic signature had a favorable performance for predicting the prognosis of bladder cancer patients. Moreover, further analysis demonstrated a significant difference in gender, tumor grade, clinical stage, TNM stage, immunoScore, and immune cell infiltration between the high- and low-risk groups in bladder cancer. We also identified an lncRNA SNHG14/miR-20a-5p/CASP8 regulatory axis in bladder cancer by constructing a ceRNA network.

Conclusion: We identified a PRG-associated prognostic signature associated with the prognosis and immune infiltrates for bladder cancer and targeting pyroptosis may be an alternative approach for therapy. Further vivo and vitro experiments are necessary to verify these results.

Identification and validation of an immune signature associated with EMT and metabolic reprogramming for predicting prognosis and drug response in bladder cancer

Background

Epithelial-mesenchymal transition (EMT), one leading reason of the dismal prognosis of bladder cancer (BLCA), is closely associated with tumor invasion and metastasis. We aimed to develop a novel immune−related gene signature based on different EMT and metabolic status to predict the prognosis of BLCA.

Methods

Gene expression and clinical data were obtained from TCGA and GEO databases. Patients were clustered based on EMT and metabolism scores calculated by ssGSEA. The immune-related differentially expressed genes (DEGs) between the two clusters with the most obvious differences were used to construct the signature by LASSO and Cox analysis. Time-dependent receiver operating characteristic (ROC) curves and Kaplan–Meier curves were utilized to evaluate the gene signature in training and validation cohorts. Finally, the function of the signature genes AHNAK and NFATC1 in BLCA cell lines were explored by cytological experiments.

Results

Based on the results of ssGSEA, TCGA patients were divided into three clusters, among which cluster 1 and cluster 3 had completely opposite EMT and metabolic status. Patients in cluster 3 had a significantly worse clinical prognosis than cluster 1. Immune-related DEGs were selected between the two clusters to construct the predictive signature based on 14 genes. High-risk patients had poorer prognosis, lower proportions of CD8⁺ T cells, higher EMT and carbohydrate metabolism, and less sensitivity to chemotherapy and immunotherapy. Overexpression of AHNAK or NFATC1 promoted the proliferation, migration and invasion of T24 and UMUC3 cells. Silencing ANHAK or NFATC1 could effectively inhibit EMT and metabolism in T24 and UMUC3 cells.

Conclusion

The established immune signature may act as a promising model for generating accurate prognosis for patients and predicting their EMT and metabolic status, thus guiding the treatment of BLCA patients.

The comprehensive and systematic identification of BLCA-specific SF-regulated, survival-related AS events

Bladder urothelial carcinoma (BLCA) is a complex disease with high morbidity and mortality. Changes in alternative splicing (AS) and splicing factor (SF) can affect gene expression, thus playing an essential role in tumorigenesis. This study downloaded 412 patients' clinical information and 433 samples of transcriptome profiling data from TCGA. And we collected 48 AS signatures from SpliceSeq. LASSO and Cox analyses were used for identifying survival-related AS events in BLCA. Finally, 1,645 OS-related AS events in 1,129 genes were validated by Kaplan-Meier (KM) survival analysis, ROC analysis, risk curve analysis, and independent prognostic analysis. Finally, our survey provides an AS-SF regulation network consisting of five SFs and 46 AS events. In the end, we profiled genes that AS occurred in pan-cancer and five SFs' expression in tumor and normal samples in BLCA. We selected CLIP-seq data for validation the interaction regulated by RBP. Our study paves the way for potential therapeutic targets of BLCA.

Heterogeneity Analysis of Bladder Cancer Based on DNA Methylation Molecular Profiling

Bladder cancer is a highly complex and heterogeneous malignancy. Tumor heterogeneity is a barrier to effective diagnosis and treatment of bladder cancer. Human carcinogenesis is closely related to abnormal gene expression, and DNA methylation is an important regulatory factor of gene expression. Therefore, it is of great significance for bladder cancer research to characterize tumor heterogeneity by integrating genetic and epigenetic characteristics. This study explored specific molecular subtypes based on DNA methylation status and identified subtype-specific characteristics using patient samples from the TCGA database with DNA methylation and gene expression were measured simultaneously. The results were validated using an independent cohort from GEO database. Four DNA methylation molecular subtypes of bladder cancer were obtained with different prognostic states. In addition, subtype-specific DNA methylation markers were identified using an information entropy-based algorithm to represent the unique molecular characteristics of the subtype and verified in the test set. The results of this study can provide an important reference for clinicians to make treatment decisions.

Upregulated of ANXA3, SORL1, and Neutrophils May Be Key Factors in the Progressionof Ankylosing Spondylitis

Introduction

The specific pathogenesis of ankylosing spondylitis (AS) remains unclear, and our study aimed to investigate the possible pathogenesis of AS.

Materials and Methods

Two datasets were downloaded from the GEO database to perform differentially expressed gene analysis, GO enrichment analysis, KEGG pathway analysis, DO enrichment analysis, GSEA analysis of differentially expressed genes, and construction of diagnostic genes using SVM and WGCNA along with Hypoxia-related genes. Also, drug sensitivity analysis was performed on diagnostic genes. To identify the differentially expressed immune genes in the AS and control groups, we analyzed the composition of immune cells between them. Then, we examined differentially expressed genes in three AS interspinous ligament specimens and three Degenerative lumbar spine specimens using high-throughput sequencing while the immune cells were examined using the neutrophil count data from routine blood tests of 1770 HLA-B27-positive samples and 7939 HLA-B27-negative samples. To assess the relationship between ANXA3 and SORL1 and disease activity, we took the neutrophil counts of the first 50 patients with above-average BASDAI scores and the last 50 patients with below-average BASDAI scores for statistical analysis. We used immunohistochemistry to verify the expression of ANXA3 and SORL1 in AS and in controls.

Results

ANXA3 and SORL1 were identified as new diagnostic genes for AS. These two genes showed a significant differential expression between AS and controls, along with showing a significant positive correlation with the neutrophil count. The results of high-throughput sequencing verified that these two gene deletions were indeed differentially expressed in AS versus controls. Data from a total of 9707 routine blood tests showed that the neutrophil count was significantly higher in AS patients than in controls (p < 0.001). Patients with AS with a high BASDAI score had a much higher neutrophil count than those with a low score, and the difference was statistically significant (p < 0.001). The results of immunohistochemistry showed that the expression of ANXA3 and SORL1 in AS was significantly higher than that in the control group.

Conclusion

Upregulated of ANXA3, SORL1, and neutrophils may be a key factor in the progression of Ankylosing spondylitis.

Identification of Prognostic Biomarkers for Bladder Cancer Based on DNA Methylation Profile

Background: DNA methylation is an important epigenetic modification, which plays an important role in regulating gene expression at the transcriptional level. In tumor research, it has been found that the change of DNA methylation leads to the abnormality of gene structure and function, which can provide early warning for tumorigenesis. Our study aims to explore the relationship between the occurrence and development of tumor and the level of DNA methylation. Moreover, this study will provide a set of prognostic biomarkers, which can more accurately predict the survival and health of patients after treatment.

Methods: Datasets of bladder cancer patients and control samples were collected from TCGA database, differential analysis was employed to obtain genes with differential DNA methylation levels between tumor samples and normal samples. Then the protein-protein interaction network was constructed, and the potential tumor markers were further obtained by extracting Hub genes from subnet. Cox proportional hazard regression model and survival analysis were used to construct the prognostic model and screen out the prognostic markers of bladder cancer, so as to provide reference for tumor prognosis monitoring and improvement of treatment plan.

Results: In this study, we found that DNA methylation was indeed related with the occurrence of bladder cancer. Genes with differential DNA methylation could serve as potential biomarkers for bladder cancer. Through univariate and multivariate Cox proportional hazard regression analysis, we concluded that FASLG and PRKCZ can be used as prognostic biomarkers for bladder cancer. Patients can be classified into high or low risk group by using this two-gene prognostic model. By detecting the methylation status of these genes, we can evaluate the survival of patients.

Conclusion: The analysis in our study indicates that the methylation status of tumor-related genes can be used as prognostic biomarkers of bladder cancer.

High Expression of BCL11A Predicts Poor Prognosis for Childhood MLL-r ALL

Background

Despite much improvement in the treatment for acute lymphoblastic leukemia (ALL), childhood ALLs with MLL-rearrangement (MLL-r) still have inferior dismal prognosis. Thus, defining mechanisms underlying MLL-r ALL maintenance is critical for developing effective therapy.

Methods

GSE13159 and GSE28497 were selected via the Oncomine website. Differentially expressed genes (DEGs) between MLL-r ALLs and normal samples were identified by R software. Next, functional enrichment analysis of these DEGs were carried out by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). Then, the key hub genes and modules were identified by Weighted Gene Co-expression Network Analysis (WGCNA). Therapeutically Applicable Research to Generate Effective Treatments (TARGET) ALL (Phase I) of UCSC Xena analysis, qPCR, and Kaplan-Meier analysis were conducted for validating the expression of key hub genes from bone marrow cells of childhood ALL patients or ALL cell lines.

Results

A total of 1,045 DEGs were identified from GSE13159 and GSE28497. Through GO, KEGG, GSEA, and STRING analysis, we demonstrated that MLL-r ALLs were upregulating “nucleosome assembly” and “B cell receptor signal pathway” genes or proteins. WGCNA analysis found 18 gene modules using hierarchical clustering between MLL-r ALLs and normal. The Venn diagram was used to filter the 98 hub genes found in the key module with the 1,045 DEGs. We identified 18 hub genes from this process, 9 of which were found to be correlated with MLL-r status, using the UCSC Xena analysis. By using qPCR, we validated these 9 hub key genes to be upregulated in the MLL-r ALLs (RS4;11 and SEM) compared to the non-MLL-r ALL (RCH-ACV) cell lines. Three of these genes, BCL11A, GLT8D1 and NCBP2, were shown to be increased in MLL-r ALL patient bone marrows compared to the non-MLL-r ALL patient. Finally, Kaplan–Meier analysis indicated that childhood ALL patients with high BCL11A expression had significantly poor overall survival.

Conclusion

These findings suggest that upregulated BCL11A gene expression in childhood ALLs may lead to MLL-r ALL development and BCL11A represents a new potential therapeutic target for childhood MLL-r ALL.

DNA Methylation Modification Map to Predict Tumor Molecular Subtypes and Efficacy of Immunotherapy in Bladder Cancer

Background: Considering the heterogeneity and complexity of epigenetic regulation in bladder cancer, the underlying mechanisms of global DNA methylation modification in the immune microenvironment must be investigated to predict the prognosis outcomes and clinical response to immunotherapy. Methods: We systematically assessed the DNA methylation modes of 985 integrated bladder cancer samples with the unsupervised clustering algorithm. Subsequently, these DNA methylation modes were analyzed for their correlations with features of the immune microenvironment. The principal analysis algorithm was performed to calculate the DMRscores of each samples for qualification analysis. Findings: Three DNA methylation modes were revealed among 985 bladder cancer samples, and these modes are related to diverse clinical outcomes and several immune microenvironment phenotypes, e.g., immune-desert, immune-inflamed, and immune-excluded ones. Then patients were classified into high- and low-DMRscore subgroups according to the DMRscore, which was calculated based on the expression of DNA methylation related genes (DMRGs). Patients with the low-DMRscore subgroup presented a prominent survival advantage that was significantly correlated to the immune-inflamed phenotype. Further analysis revealed that patients with low DMRscores exhibited less TP53 wild mutation, lower cancer stage and molecular subtypes were mainly papillary subtypes. In addition, an independent immunotherapy cohort confirmed that DMRscore could serve as a signature to predict prognosis outcomes and immune responses. Conclusion: Global DNA methylation modes can be used to predict the immunophenotypes, aggressiveness, and immune responses of bladder cancer. DNA methylation status assessments will strengthen our insights into the features of the immune microenvironment and promote the development of more effective treatment strategies.

Structure, biochemistry, and gene expression patterns of the proline biosynthetic enzyme pyrroline-5-carboxylate reductase (PYCR), an emerging cancer therapy target

Proline metabolism features prominently in the unique metabolism of cancer cells. Proline biosynthetic genes are consistently upregulated in multiple cancers, while the proline catabolic enzyme proline dehydrogenase has dual, context-dependent pro-cancer and pro-apoptotic functions. Furthermore, the cycling of proline and Δ1-pyrroline-5-carboxylate through the proline cycle impacts cellular growth and death pathways by maintaining redox homeostasis between the cytosol and mitochondria. Here we focus on the last enzyme of proline biosynthesis, Δ1-pyrroline-5-carboxylate reductase, known as PYCR in humans. PYCR catalyzes the NAD(P)H-dependent reduction of Δ1-pyrroline-5-carboxylate to proline and forms the reductive half of the proline metabolic cycle. We review the research on the three-dimensional structure, biochemistry, inhibition, and cancer biology of PYCR. To provide a global view of PYCR gene upregulation in cancer, we mined RNA transcript databases to analyze differential gene expression in 28 cancer types. This analysis revealed strong, widespread upregulation of PYCR genes, especially PYCR1. Altogether, the research over the past 20 years makes a compelling case for PYCR as a cancer therapy target. We conclude with a discussion of some of the major challenges for the field, including developing isoform-specific inhibitors, elucidating the function of the long C-terminus of PYCR1/2, and characterizing the interactome of PYCR.

Development and validation of an intra-tumor heterogeneity-related signature to predict prognosis of bladder cancer: a study based on single-cell RNA-seq

Intra-tumor heterogeneity (ITH) was a potential mechanism of progression and drug resistance in bladder cancer (BCa). However, the understanding of ITH in BCa remains insufficient. Single-cell RNA sequencing (scRNA-seq) profiles of 2075 cells were analyzed, and 2940 cell markers were screened. The ITH of 396 cases was evaluated, and 96 ITH-related genes were identified. Based on the gene-pair strategy, 96 genes were cyclically paired, and an 8-gene-pair model was successfully established to evaluate the overall survival of BCa through Lasso and multivariate Cox regressions. The risk model showed high predictive value in the training dataset (n = 396, p = 0) and external validation datasets (n = 165, p = 2.497e-02; n = 224, p = 3.423e-02). The model was also valuable for the prediction of clinical treatment outcomes. Totally, a prognostic model based on scRNA-seq and ITH was successfully constructed and validated in large cohorts, providing novel clues for ITH study of BCa.

Identification of a competing endogenous RNA axis "SVIL-AS1/miR-103a/ICE1" associated with chemoresistance in lung adenocarcinoma by comprehensive bioinformatics analysis

Background

Chemotherapy is an important treatment for lung cancer. The molecular mechanism of lung adenocarcinoma (LUAD) chemoresistance is not completely understood.

Methods

Weighted gene co‐expression network analysis (WGCNA) was applied to screen the modules related to chemosensitivity using the data of LUAD patients receiving chemotherapy in The Cancer Genome Atlas database. GDCRNATools package was used to establish competing endogenous RNA (ceRNA) network based on the key chemotherapy‐related module. Kaplan–Meier and risk models were used to analyze the influence of genes in the ceRNA network on the prognosis of LUAD patients receiving chemotherapy. Cell counting kit‐8, reverse transcription‐quantitative PCR, and dual‐luciferase reporter assay were used to detect the effects of abnormal expression of genes in the ceRNA network on the proliferation and IC50 of cisplatin (DDP)‐resistant LUAD cells, and the targeting relationship of genes in the ceRNA network. The signaling pathways and functions of ICE1 in LUAD were analyzed by LinkOmics and CancerSEA databases, and validated by Western blot.

Results

Midnightblue module was the only WGCNA module positively correlated with chemosensitivity, in which the function of genes was related to cancer progression. SVIL‐AS1/miR‐103a/ICE1 was constructed based on midnightblue module. High expression of SVIl‐AS1 and ICE1 corresponded to a favorable prognosis. High expression of miR‐103a corresponded to a dismal prognosis. SVIl‐AS1 was downregulated in DDP‐resistant LUAD cells. SVIL‐AS1 overexpression retarded the proliferation and DDP resistance of DDP‐resistant LUAD cell. miR‐103a was sponged by SVIL‐AS1 and directly targeted ICE1. miR‐103a overexpression and ICE1 knockdown overturned the suppressive effect of SVIL‐AS1 overexpression on cell proliferation and DDP resistance. Further bioinformatics analysis and experimental verification showed that SVIL‐AS1/miR‐103a‐3p/ICE1 axis can enhance DNA damage caused by chemotherapeutic agents.

Conclusions

SVIL‐AS1 inhibited chemoresistance by acting as a sponge for miR‐103a and upregulating ICE1 expression, which may be a potential therapeutic target for chemotherapy in LUAD.

The role of IGF2BP2, an m6A reader gene, in human metabolic diseases and cancers

The human insulin-like growth factor 2 (IGF2) mRNA binding proteins 2 (IGF2BP2/IMP2) is an RNA-binding protein that regulates multiple biological processes. Previously, IGF2BP2 was thought to be a type 2 diabetes (T2D)-associated gene. Indeed IGF2BP2 modulates cellular metabolism in human metabolic diseases such as diabetes, obesity and fatty liver through post-transcriptional regulation of numerous genes in multiple cell types. Emerging evidence shows that IGF2BP2 is an N6-methyladenosine (m6A) reader that participates in the development and progression of cancers by communicating with different RNAs such as microRNAs (miRNAs), messenger RNAs (mRNAs) and long non-coding RNAs (lncRNAs). Additionally, IGF2BP2 is an independent prognostic factor for multiple cancer types. In this review, we summarize the current knowledge on IGF2BP2 with regard to diverse human metabolic diseases and its potential for cancer prognosis.