N6-Methyladenosine enhances the translation of ENO1 to promote the progression of bladder cancer by inhibiting PCNA ubiquitination.

The mechanism underlying N6-methyladenosine (m6A) modification in bladder cancer (BC) remains elusive. We identified that the RBM15/METTL3 complex enhances m6A modification and promotes the ENO1 protein translation efficiency through its 359A site by depending on YTHDF1 in BC cells. In the tumor microenvironment, TGF-ß effectively stimulates RBM15/METTL3 expression to improve ENO1 mRNA m6A modification through the Smad2/3 pathway. Reduced ENO1 m6A levels hamper tumor proliferation both in vitro and in vivo. Mechanistically, ENO1 augments PCNA protein stability by reducing its K48-linked ubiquitination and thus prevents protein degradation through the endoplasmic reticulum-associated degradation pathway. According to the subsequent experiments, the ENO1 inhibitor significantly reduced tumor proliferation both in vitro and in vivo. Our study highlights the significance of RBM15/METTL3 complex-mediated ENO1 mRNA m6A modification in ENO1 expression. It also reveals a novel mechanism by which ENO1 promotes BC progression, thereby suggesting that ENO1 can be a therapeutic target for BC.

Identification and validation of a signature based on myofibroblastic cancer-associated fibroblast marker genes for predicting prognosis, immune infiltration, and therapeutic response in bladder cancer.

PURPOSE: Myofibroblastic cancer-associated fibroblasts (myCAFs) are important components of the tumor microenvironment closely associated with tumor stromal remodeling and immunosuppression. This study aimed to explore myCAFs marker gene biomarkers for clinical diagnosis and therapy for patients with bladder cancer (BC). MATERIALS AND METHODS: BC single-cell RNA sequencing (scRNA-seq) data were obtained from the National Center for Biotechnology Information Sequence Read Archive. Transcriptome and clinical data were downloaded from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Subsequently, univariate Cox and LASSO (Least Absolute Shrinkage and Selection Operator regression) regression analyses were performed to construct a prognostic signature. Immune cell activity was estimated using single-sample gene set enrichment analysis whilst the TIDE (tumor immune dysfunction and exclusion) method was employed to assess patient response to immunotherapy. The chemotherapy response of patients with BC was evaluated using genomics of drug sensitivity in cancer. Furthermore, Immunohistochemistry was used to verify the correlation between MAP1B expression and immunotherapy efficacy. The scRNA-seq data were analyzed to identify myCAFs marker genes. RESULTS: Combined with bulk RNA-sequencing data, we constructed a two-gene (COL6A1 and MAP1B) risk signature. In patients with BC, the signature demonstrated outstanding prognostic value, immune infiltration, and immunotherapy response. This signature served as a crucial guide for the selection of anti-tumor chemotherapy medications. Additionally, immunohistochemistry confirmed that MAP1B expression was significantly correlated with immunotherapy efficacy. CONCLUSIONS: Our findings revealed a typical prognostic signature based on myCAF marker genes, which offers patients with BC a novel treatment target alongside theoretical justification.

A feed-forward loop based on aerobic glycolysis and TGF-ß between tumor-associated macrophages and bladder cancer cells promoted malignant progression and immune escape.

PURPOSE: Immunotherapy with programmed cell death 1/ligand 1 (PD-1/PD-L1) checkpoint inhibitors has revolutionized the systemic treatment of solid tumors, including bladder cancer. Previous studies have shown that enhanced glycolysis, tumor-associated macrophage (TAM) infiltration, and TGF-ß secretion in the tumor microenvironment (TME) are closely related to PD-1/PD-L1 inhibitor immunotherapy resistance. However, the potential mechanism of their interaction in bladder cancer has not been fully uncovered. METHODS: By coculturing bladder cancer cells and TAMs, we studied the relationship and interaction mechanism between tumor cell glycolysis, TAM functional remodeling, TGF-ß positive feedback secretion, and PD-L1 mRNA m6A methylation in the bladder cancer microenvironment. RESULTS: Bioinformatics analysis and IHC staining found a close correlation between tumor glycolysis, M2 TAM infiltration, and the prognosis of bladder cancer patients. In Vitro experiments demonstrated that bladder cancer cells could re-educate M2 TAMs through lactate and promote TGF-ß secretion via the HIF-1α signaling pathway. Reciprocally, in vitro, and in vivo experiments validated that M2 TAMs could promote glycolysis in bladder cancer cells by TGF-ß via the Smad2/3 signaling pathways. Furthermore, M2 TAMs could also promote CSCs and EMT of bladder cancer cells. More importantly, we found M2 TAMs enhance PD-L1 mRNA m6A methylation by promoting METLL3 expression in bladder cancer via the TGF-ß/Smad2/3 pathway in the TME. CONCLUSIONS: Our study highlights a feed-forward loop based on aerobic glycolysis and TGF-ß between M2 TAMs and bladder cancer cells, which may be a potential mechanism of malignant progression and immunotherapy resistance in bladder cancer.

Ferroptosis Biomarkers for Predicting Prognosis and Immunotherapy Efficacy in Adrenocortical Carcinoma.

BACKGROUND: Numerous studies have suggested that ferroptosis plays an important regulatory role in cancer cell death. Nonetheless, the potential effects of ferroptosis regulators on the prognosis, the expression of immunomodulatory factors in the tumor microenvironment and on the efficacy of immunotherapy in adrenocortical carcinoma (ACC) remain largely unknown. METHODS: Public ACC datasets were used to investigate the relationship between ferroptosis regulators and prognosis and clinical features. A ferroptosis scoring system was established for individual cases of ACC using principal component analysis algorithms. Hub ferroptosis-related genes involved in immunoregulation and immunotherapy efficacy in ACC were further identified. RESULTS: Twenty ferroptosis regulators were differentially expressed in ACC and 17 ferroptosis regulators were closely related to prognosis in ACC. A ferroptosis scoring system was developed based on ACSL4, FANCD2, and SLC7A1 expression, and the ferroptosis regulators could serve as an independent prognostic factor for ACC. Further analyses indicated that the ferroptosis score integrated with the tumor mutation burden (TMB), and immune-checkpoint gene expression could predict prognosis in ACC. RNA isolation and reverse transcription­quantitative polymerase chain reaction (RT-qPCR) demonstrated significant differences in the expression levels of ACSL4, FANCD2, and SLC7A1 between ACC and normal tissues. Furthermore, FANCD2 was significantly related to immunotherapy efficacy and prognosis in ACC. CONCLUSION: Our study demonstrated that ferroptosis was significantly associated with prognosis, clinical characteristics, immune-checkpoint gene expression, and tumor microenvironment immune cell infiltration in ACC. The current study provides comprehensive evidence for further research on ferroptosis regulators in ACC and provides new insight into the epigenetic regulation of the antitumor immune response.

High expression of COL6A1 predicts poor prognosis and response to immunotherapy in bladder cancer.

Extracellular matrix (ECM), as an important framework for tumor microenvironment, plays important roles in many critical processes, including tumor growth, invasion, immune suppression, and drug resistance. However, few biomarkers of ECM-related genes (ERGs) have been developed for prognosis prediction and clinical treatment of bladder cancer (BC) patients. Bioinformatics analysis and LC-MS/MS analysis were used to screen differentially expressed ERGs in BC. Multivariate Cox regression analysis and Lasso regression analysis were used to construct and validate an ERGs-based prognostic prediction model for BC. Immunohistochemistry was used to detect the protein expression of hub gene-COL6A1 in BC patients. Using bioinformatics analysis from The Cancer Genome Atlas (TCGA) database and proteomic analysis from our BC cohort, we constructed and validated an effective prognostic prediction model for BC patients based on four differentially expressed ERGs (MAP1B, FBN1, COL6A1, and MFAP5). Moreover, we identified human collagen VI-COL6A1 was a hub gene in this prognostic prediction model and found that COL6A1 was closely related to malignancy progression, prognosis, and response to PD-1 inhibitor immunotherapy in BC. Our findings highlight the satisfactory predictive value of ECM-related prognostic models in BC and suggested that COL6A1 may be a potential biomarker in predicting malignant progression, prognosis, and efficacy of immunotherapy in BC.

High expression of GMNN predicts malignant progression and poor prognosis in ACC.

BACKGROUND: Adrenocortical carcinoma (ACC) is a rare endocrine neoplasm, which is characterized by poor prognosis and high recurrence rate. Novel and reliable prognostic and metastatic biomarkers are lacking for ACC patients. This study aims at screening potential prognostic biomarkers and therapeutic targets of ACC through bioinformatic methods and immunohistochemical (IHC) analysis. METHODS: In the present study, by using the Gene Expression Omnibus (GEO) database we identified differentially expressed genes (DEGs) in ACC and validated these DEGs in The Cancer Genome Atlas (TCGA) ACC cohort. A DEGs-based signature was additionally constructed and we assessed its prognosis and prescient worth for ACC by survival analysis and nomogram. Immunohistochemistry (IHC) was used to verify the relationship between hub gene-GMNN expressions and clinicopathologic outcomes in ACC patients. RESULTS: A total of 24 DEGs correlated with the prognosis of ACC were screened from the TCGA and GEO databases. Five DEGs were subsequently selected in a signature which was closely related to the survival rates of ACC patients and GMNN was identified as the core gene in this signature. Univariate and multivariate Cox regression showed that the GMNN was an independent prognostic factor for ACC patients (P < 0.05). Meanwhile, GMNN was closely related to the OS and PFI of ACC patients treated with mitotane (P < 0.001). IHC confirmed that GMNN protein was overexpressed in ACC tissues compared with normal adrenal tissues and significantly correlated with stage (P = 0.011), metastasis (P = 0.028) and Ki-67 index (P = 0.014). CONCLUSIONS: GMNN is a novel tumor marker for predicting the malignant progression, metastasis and prognosis of ACC, and may be a potential therapeutic target for ACC.

TEAD4 is an Immune Regulating-Related Prognostic Biomarker for Bladder Cancer and Possesses Generalization Value in Pan-Cancer.

Recent studies have revealed the significant role of TEA domain family member 4 (TEAD4) in the development and progression of cancer. However, the potential role of TEAD4 in the progression of bladder cancer (BC) remains to be explored. The aim of this study was to determine whether TEAD4 could serve as a pan-cancer predictor of the prognosis for BC. Based on data mined from public databases, expression levels and clinical value of TEAD4 were identified in BC and human pan-cancers. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis was performed to detect the TEAD4 expression levels in BC cell lines. Gene Set Enrichment Analysis (GSEA) was carried out for functional analysis in BC, and the relationship between infiltrating immune cells and TEAD4 expression was evaluated by the CIBERSORT algorithm in BC and pan-cancer data. TEAD4 was overexpressed and associated with poor prognosis in BC and several types of cancers. GSEA and CIBERSORT algorithm suggested that various pathways including immune-related pathways were enriched in TEAD4 high expression group and several immunocytes infiltrated were correlated with the expression of TEAD4. This study revealed TEAD4 is an immune regulating-related predictor of prognosis for BC and has generalization value in pan-cancer.

Development and Validation of an m6A RNA Methylation Regulators-Based Signature for Predicting the Prognosis of Adrenocortical Carcinoma.

Background: Adrenocortical carcinoma (ACC) is an aggressive and rare neoplasm that originates from the cortex of the adrenal gland. N6-methyladenosine (m6A) RNA methylation, the most common form of mRNA modification, has been reported to be correlated with the occurrence and development of the malignant tumor. This study aims to identify the significance of m6A RNA methylation regulators in ACC and construct a m6A based signature to predict the prognosis of ACC patients. Materials and methods: RNA-seq data from The Cancer Genome Atlas (TCGA) database was used to identify the expression level of m6A RNA methylation regulators in ACC. An m6A based signature was further constructed and its prognostic and predictive values were assessed by survival analysis and nomogram. Results: 11 m6A RNA regulators were differentially expressed in ACC and three m6A RNA regulators were finally selected in a signature to predict the prognosis of ACC patients. Survival analysis indicated that high risk scores were closely related to poor survival outcomes in ACC patients. Univariate and multivariate Cox regression analyses demonstrated that the m6A based signature was an independent prognostic factor for ACC patients. A nomogram with clinical factors and the m6A based signature was also constructed to superiorly predict the prognosis of ACC patients. The expression levels of m6A RNA methylation regulators, which were contained in the signature, were also verified in human ACC tissues and normal tissues by using vitro experiments. Conclusion: We identified and validated an m6A based signature, which can be used as an independent prognostic factor in evaluating the prognosis of ACC patients. Further clinical trials and experimental explorations are needed to confirm our observations and mechanisms underlying prognostic values of these m6A RNA methylation regulators in ACC.

Construction of a immune-associated genes based prognostic signature in bladder cancer.

Current studies indicated that immune-associated genes (IAGs) have important roles in the occurrence and development of bladder cancer (BC). The current work aims to identify the prognostic values of IAGs in BC and establish a prognostic signature based on IAGs. RNA sequencing data and protein expression data were used to identify differentially expressed IAGs in BC. An IAGs based signature was further constructed and the prognostic and predictive values of the signature were evaluated by survival analysis and nomogram. RNA isolation and reverse transcription-quantitative PCR (RT-qPCR) were further performed to investigate the expression levels of IAGs in BC cells and were used to explore the relationship between IAGs and M2 tumour-associated macrophages (TAMs) secreted transforming growth factor-ß1 (TGF-ß1) in BC cells. We selected five IAGs to develop an IAGs signature model, which were significantly related to survival outcomes of BC patients. RT-qPCR showed that five IAGs were significantly differentially expressed and three IAGs were positively correlated with M2 TAMs secreted TGF-ß1 in T24 cells. We identified and validated an IAGs based signature to predict the prognosis of BC patients. Furthermore, M2 TAMs may promote the expression of IAGs in BC via the TGF-ß1 signalling pathway.

Identification and verification of an immune-related lncRNA signature for predicting the prognosis of patients with bladder cancer.

BACKGROUND: Recent studies have revealed the significant roles of immune-related long noncoding RNAs (lncRNAs) in cancer development and progression. The identification of biomarkers that contribute to early detection and risk stratification provides significant benefits for bladder cancer (BC) patients. The current study aimed to determine an immune-related lncRNA signature for predicting the prognosis of BC patients. METHODS: Based on The Cancer Genome Atlas (TCGA) database, we identified seven immune-related lncRNAs with prognostic value. The predictive value of the prognostic signature developed from immune-related lncRNAs was assessed by survival and nomogram analyses. Principal component analysis (PCA) was performed to visualize gene expression patterns in the groups defined by the risk score, and the immune composition and purity of the tumor were evaluated by the ESTIMATE algorithm. RESULTS: Based on the Pearson correlation analysis results, 765 immune-related lncRNAs were filtered (|R| > 0.4, P < 0.001), and seven immune-related lncRNAs (Z84484.1, AC009120.2, AL450384.2, AC024060.1, TNFRSF14-AS1, AL354919.2, OCIAD1-AS1) with prognostic value were finally identified. Patients in the low-risk group had a better prognosis than those in the high-risk group. Multivariate Cox regression analysis showed that the signature was an independent prognostic factor. A prognostic nomogram with clinical features and the signature of seven immune-related lncRNAs was also constructed. According to the PCA and ESTIMATE algorithm results, we found different immune statuses in the low-and high-risk groups. CONCLUSIONS: Our study shows that the signature of seven immune-related lncRNAs can be used as a prognostic marker for BC.

Identification of metabolism-associated genes and construction of a prognostic signature in bladder cancer.

BACKGROUND: Bladder cancer (BC) is a commonly diagnosed malignant tumor in the urinary system, with a high morbidity and a high recurrence rate. Current studies indicated that metabolism-associated genes (MAGs) having critical roles in the etiology of BC. The present study aims to identify differentially expressed MAGs and construct a MAGs based prognostic risk signature for BC by using The Cancer Genome Atlas (TCGA) database and proteomics data. METHODS: RNA-sequence data from the TCGA database and proteomics data from our BC samples were used to identify differentially expressed MAGs and construct a MAGs based prognostic signature in BC. Subsequently, survival analysis and nomogram were used to evaluate the prognostic and predictive value of the MAGs based signature in BC. RNA isolation and reverse transcription­quantitative PCR (RT-qPCR) were further performed to investigate the expression levels of MAGs in BC cells and explore the relationship between MAGs and M2 tumor associated macrophages (TAMs) secreted transforming growth factor-ß1 (TGF-ß1) in BC cells. RESULTS: A total of 23 differentially expressed MAGs were identified and five MAGs were finally used to construct a MAGs based signature. Survival analysis revealed that the MAGs based signature was closely correlated with the survival outcomes of patients with BC. A nomogram with the MAGs based signature risk score and clinical features was also constructed to facilitate the individualized prediction of BC patients. RT-qPCR showed that five MAGs were significantly differentially expressed and the expression levels of three MAGs were positively correlated with M2 TAMs secreted TGF-ß1 in T24 cells. CONCLUSIONS: Our study identified novel prognostic MAGs and constructed a MAGs based signature, which can be used as an independent factor in evaluating the prognosis of patients with BC. Furthermore, M2 TAMs may promote the expression of MAGs via the TGF-ß1 signaling pathway in the microenvironment of BC. Further clinical trials and experimental explorations are needed to validate our observations in BC.

The Analysis of PTPN6 for Bladder Cancer: An Exploratory Study Based on TCGA.

PTPN6 (protein tyrosine phosphatase nonreceptor type 6), a tyrosine phosphatase, is known to be signaling molecules that regulate a variety of cellular processes including cell growth, differentiation, mitotic cycle, and oncogenic transformation. Previous studies have demonstrated that PTPN6 expression is relatively elevated in several malignancies. However, the role of PTPN6 in bladder cancer (BC) remains unclear. The purpose of this study was to explore the prognostic value of PTPN6 in BC. RNA-seq data from The Cancer Genome Atlas (TCGA) was used to identify the expression level of PTPN6 in BC. The relationship between clinical pathologic features and PTPN6 were analyzed with the Wilcoxon signed-rank test. The prognostic and predictive value of PTPN6 was evaluated by survival analysis and nomogram. Gene Set Enrichment Analysis (GSEA) was conducted to explore the potential molecular mechanisms of PTPN6 in BC. Finally, Tumor Immune Estimation Resource (TIMER) was applied to investigate the relationship between PTPN6 and immune cell infiltration in the tumor microenvironment. Results indicated that PTPN6 was overexpressed in BC tissues compared with normal bladder tissues and was significantly correlated with grade, stage, T, and N. Survival analysis showed that low expression of PTPN6 was significantly related to the poor overall survival (OS) in BC patients. Coexpression analysis showed that PTPN6 and TNFRSF14 (Tumor necrosis factor receptor superfamily member 14) have a close correlation in BC. GSEA showed that multiple cancer-associated signaling pathways are differentially enriched in the PTPN6 high expression phenotype. Moreover, the expression level of PTPN6 was positively associated with the infiltration of B cells, CD4+T cells, dendritic cells, and neutrophils and negatively associated with CD8+ T cells and macrophages in BC. In conclusion, we identified that PTPN6 may be a novel prognostic biomarker in BC based on the TCGA database. Further clinical trials are needed to confirm our observations and mechanisms underlying the prognostic value of PTPN6 in BC also deserve further experimental exploration.

Development and validation of a prognostic immune-associated gene signature in clear cell renal cell carcinoma.

BACKGROUND: Recent studies have demonstrated that immune-associated genes (IAGs) play an important role in the occurrence and progression of clear renal clear cell carcinoma (ccRCC). Novel biomarkers and a reliable prognostic prediction model for ccRCC patients are still limited. The objective of this study was to develop a IAGs signature and validate its prognostic value in ccRCC using bioinformatic methods and publicly database. METHODS: In the present study, we identified differentially expressed IAGs in ccRCC based on The Cancer Genome Atlas (TCGA) database. A prognostic IAGs risk model was further developed and its prognostic and predictive value was evaluated by survival analysis and nomogram. RESULTS: A total of 681 differentially expressed IAGs were identified and seven IAGs (IFI30, WNT5A, IRF9, AGER, PLAUR, TEK, BID) were finally selected in a IAGs signature. Survival analysis revealed that high IAGs risk scores were significantly related to poor survival outcomes. The IAGs signature was demonstrated as an independent prognostic factor and closely related to the metastasis status of ccRCC. A nomogram with clinicopathologic characteristics and IAGs signature was also constructed to superiorly predict prognosis of ccRCC patients. CONCLUSIONS: We identified seven IAGs as a potential signature for reflecting the prognosis of ccRCC based on TCGA database. Further clinical trials are needed to validate our observations and the mechanisms underlying the prognostic value of IAGs signature in ccRCC also deserve further experimental exploration.

Construction of an Immune-Associated Gene-Based Signature in Muscle-Invasive Bladder Cancer.

BACKGROUND: In recent years, immune-associated genes (IAGs) have been documented as having critical roles in the occurrence and progression of muscle-invasive bladder cancer (MIBC). Novel immune-related biomarkers and a robust prognostic signature for MIBC patients are still limited. The study is aimed at developing an IAG-based signature to predict the prognosis of MIBC patients. METHODS: In the present study, we identified differentially expressed IAGs in MIBC by using transcriptomics data from The Cancer Genome Atlas (TCGA) database and proteomics data from our samples. We further constructed an IAG-based signature and evaluated its prognostic and predictive value by survival analysis and nomogram. Tumor Immune Estimation Resource (TIMER) was applied to explore the correlation between the IAG-based signature and immune cell infiltration in the microenvironment of MIBC. RESULTS: A total of 22 differentially expressed IAGs were identified, and 2 IAGs (NR2F6 and AHNAK) were used to establish a prognostic signature. Subsequently, survival analysis showed that high-risk scores were significantly correlated with poor overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS) of MIBC patients. A prognostic nomogram was constructed by integrating clinical factors with the IAG-based signature risk score. In addition, the IAG-based signature risk score was positively associated with the infiltration of macrophages and dendritic cells in MIBC. CONCLUSIONS: We constructed and verified a novel IAG-based signature, which could predict the prognosis of MIBC and might reflect the status of the immune microenvironment of MIBC. Further studies in more independent clinical cohorts and further experimental exploration of the prognostic IAG-based signature are still needed.