METTL3-mediated m6A modification of circGLIS3 promotes prostate cancer progression and represents a potential target for ARSI therapy.

BACKGROUND: Circular RNAs (circRNAs) have been shown to be involved in tumorigenesis and progression. However, the role of circGLIS3 (hsa_circ_0002874) in prostate cancer (PCa) has yet not been reported. METHODS: Candidate circRNA were determined through comprehensive analysis of public datasets, PCa cell lines, and tissues data. A series of cellular functional assays, including CCK-8, colony formation, wound healing, and transwell assays were performed. Subsequently, RNA sequencing, RNA immunoprecipitation, methylated RNA immunoprecipitation, microRNA pulldown, luciferase reporter assay, and western blot were used to explore the underlying molecular mechanisms. Moreover, the xenograft tumor mouse model was established to elucidate the function of circGLIS3. RESULTS: CircGLIS3, derived from exon 2 of the parental GLIS3 gene, was identified as a novel oncogenic circRNA in PCa that was closely associated with the biochemical recurrence. Its expression levels were upregulated in PCa tissues and cell lines as well as enzalutamide high-resistant cells. The cellular functional assays revealed that circGLIS3 promoted PCa cell proliferation, migration, and invasion. METTL3-mediated N6-methyladenosine (m6A) modification maintained its upregulation by enhancing its stability. Mechanically, CircGLIS3 sponged miR-661 to upregulate MDM2, thus regulating the p53 signaling pathway to promote cell proliferation, migration, and invasion. Furthermore, in vitro and in vivo experiments, the knockdown of circGLIS3 improved the response of PCa cells to ARSI therapies such as enzalutamide. CONCLUSIONS: METTL3-mediated m6A modification of circGLIS3 regulates the p53 signaling pathway via the miR-661/MDM2 axis, thereby facilitating PCa progression. Meanwhile, this study unveils a promising potential target for ARSI therapy for PCa.

Downregulation of RAB17 have a poor prognosis in kidney renal clear cell carcinoma and its expression correlates with DNA methylation and immune infiltration.

BACKGROUND: RAB17 is one of the RAB family members. It has been reported to be closely associated with a variety of tumors and has different roles in various tumors. However, the effect of RAB17 in KIRC remains unclear. MATERIALS AND METHODS: We analyzed the differential expression of RAB17 in kidney renal clear cell carcinoma (KIRC) tissues and normal tissues using the public databases. The prognostic role of RAB17 in KIRC was analyzed using the Cox regression methods, and a prognostic model was constructed based on the results of the Cox analysis. In addition, further analysis of RAB17 in KIRC was performed in relation to genetic alterations, DNA methylation m6A methylation and immune infiltration. Finally, RAB17 mRNA and protein expression levels were analyzed in tissue samples (KIRC tissues and normal tissues) and cell lines (normal renal tubular cell and KIRC cells), and in vitro functional assays were performed. RESULTS: RAB17 was low-expressed in KIRC. Downregulation of RAB17 expression is correlated with unfavorable clinicopathological characteristics and a worse prognosis in KIRC. The RAB17 gene alteration in KIRC was primarily characterized by copy number alteration. Six CpG sites of RAB17 DNA methylation levels are higher in KIRC tissues than in normal tissues, and are correlated with RAB17 mRNA expression levels, showing a significant negative correlation. cg01157280 site DNA methylation levels are associated with pathological stage and overall survival, and it may be the only CpG site with independent prognostic significance. Functional mechanism analysis revealed that RAB17 is closely associated with immune infiltration. RAB17 expression was found to be negatively correlated with most immune cell infiltration according to two different methods. Furthermore, most immunomodulators were significantly negatively correlated with RAB17 expression, and significantly positively correlated with RAB17 DNA methylation levels. RAB17 was significantly low expression in KIRC cells and KIRC tissues. In vitro, silencing of RAB17 promoted KIRC cell migration. CONCLUSION: RAB17 can be used as a potential prognostic biomarker for patients with KIRC and for assessing immunotherapy response.

Novel cuproptosis-related long non-coding RNA signature to predict prognosis in prostate carcinoma.

BACKGROUND: Cuproptosis, an emerging form of programmed cell death, has recently been identified. However, the association between cuproptosis-related long non-coding RNA (lncRNA) signature and the prognosis in prostate carcinoma remains elusive. This study aims to develop the novel cuproptosis-related lncRNA signature in prostate cancer and explore its latent molecular function. METHODS: RNA-seq data and clinical information were downloaded from the TCGA datasets. Then, cuproptosis-related gene was identified from the previous literature and further applied to screen the cuproptosis-related differentially expressed lncRNAs. Patients were randomly assigned to the training cohort or the validation cohort with a 1:1 ratio. Subsequently, the machine learning algorithms (Lasso and stepwise Cox (direction = both)) were used to construct a novel prognostic signature in the training cohorts, which was validated by the validation and the entire TCGA cohorts. The nomogram base on the lncRNA signature and several clinicopathological traits were constructed to predict the prognosis. Functional enrichment and immune analysis were performed to evaluate its potential mechanism. Furthermore, differences in the landscape of gene mutation, tumour mutational burden (TMB), microsatellite instability (MSI), drug sensitivity between both risk groups were also assessed to explicit their relationships. RESULTS: The cuproptosis-related lncRNA signature was constructed based on the differentially expressed cuproptosis-related lncRNAs, including AC005790.1, AC011472.4, AC099791.2, AC144450.1, LIPE-AS1, and STPG3-AS1. Kaplan-Meier survival and ROC curves demonstrate that the prognosis signature as an independent risk indicator had excellent potential to predict the prognosis in prostate cancer. The signature was closely associated with age, T stage, N stage, and the Gleason score. Immune analysis shows that the high-risk group was in an immunosuppressive microenvironment. Additionally, the significant difference in landscape of gene mutation, tumour mutational burden, microsatellite instability, and drug sensitivity between both risk groups was observed. CONCLUSIONS: A novel cuproptosis-related lncRNA signature was constructed using machine learning algorithms to predict the prognosis of prostate cancer. It was closely with associated with several common clinical traits, immune cell infiltration, immune-related functions, immune checkpoints, gene mutation, TMB, MSI, and the drug sensitivity, which may be useful to improve the clinical outcome.

MAPK8IP2 is a potential prognostic biomarker and promote tumor progression in prostate cancer.

BACKGROUND: MAPK8IP2 is one of the JNK-interacting proteins (JIPs) family members, and is involved in the regulation of the JNK and P38 MAPK signaling pathways. MAPK8IP2 has been reported to be closely associated with several cancers. However, the biological function of MAPK8IP2 in prostate cancer (PCa) remains unclear. METHODS: MAPK8IP2 expression in PCa and subgroups of PCa was analyzed by public databases. The prognostic role of MAPK8IP2 in prostate cancer was analyzed using the Cox regression method. The potential mechanism by which MAPK8IP2 affects PCa progression was investigated by utilizing public data, including genetic alteration, DNA methylation, m6A methylation, and immune infiltration data. We further performed in vitro assays to validate the effect of MAPK8IP2 on PCa cell proliferation, migration and invasion. RESULTS: MAPK8IP2 is highly expressed in PCa tissues. Overexpression of MAPK8IP2 is associated with adverse clinicopathological factors and a poor prognosis in PCa. Receiver operating curve analysis showed that MAPK8IP2 can distinguish PCa tissues from non-PCa tissues with a certain accuracy (AUC = 0.814). The MAPK8IP2 genetic alteration rate was 2.6% and MAPK8IP2 alterations correlated with a poor prognosis. We also found that CDK12 and TP53 mutations were associated with MAPK8IP2 expression. The DNA methylation level of MAPK8IP2 was higher in primary tumors than in normal tissues, and the high MAPK8IP2 DNA methylation group of PCa patients had poor survival. Enrichment analysis indicated that MAPK8IP2 was involved in the MAPK signaling pathway. In vitro, knockdown of MAPK8IP2 inhibited PCa cell proliferation, migration and invasion. CONCLUSION: MAPK8IP2 is a potential target for PCa treatment and can serve as a novel biomarker for PCa diagnosis and prognosis evaluation.

Novel amino acid metabolism-related gene signature to predict prognosis in clear cell renal cell carcinoma.

Background: Amino acid metabolism (AAM) deregulation, an emerging metabolic hallmark of malignancy, plays an essential role in tumour proliferation, invasion, and metastasis. However, the expression of AAM-related genes and their correlation with prognosis in clear cell renal cell carcinoma (ccRCC) remain elusive. This study aims to develop a novel consensus signature based on the AAM-related genes. Methods: The RNA-seq expression data and clinical information for ccRCC were downloaded from the TCGA (KIRC as training dataset) and ArrayExpress (E-MTAB-1980 as validation dataset) databases. The AAM-related differentially expressed genes were screened via the "limma" package in TCGA cohorts for further analysis. The machine learning algorithms (Lasso and stepwise Cox (direction = both)) were then utilised to establish a novel consensus signature in TCGA cohorts, which was validated by the E-MTAB-1980 cohorts. The optimal cutoff value determined by the "survminer" package was used to categorise patients into two risk categories. The Kaplan-Meier curve, the receiver operating characteristic (ROC) curve, and multivariate Cox regression were utilised to evaluate the prognostic value. The nomogram based on the gene signature was constructed, and its performance was analysed using ROC and calibration curves. Gene Set Enrichment Analysis (GSEA) and immune cell infiltration analysis were conducted on its potential mechanisms. The relationship between the gene signature and key immune checkpoint, N6-methyladenosine (m6A)-related genes, and sensitivity to chemotherapy was assessed. Results: A novel consensus AMM-related gene signature consisting of IYD, NNMT, ACADSB, GLDC, and PSAT1 is developed to predict prognosis in TCGA cohorts. Kaplan-Meier survival shows that overall survival in the high-risk group was more dismal than in the low-risk group in the TCGA cohort, validated by the E-MTAB-1980 cohort. Multivariate regression analysis also demonstrates that the gene signature is an independent predictor of ccRCC. Immune infiltration analysis highlighted that the high-risk group indicates an immunosuppressive microenvironment. It is also closely related to the level of key immune checkpoints, m6A modification, and sensitivity to chemotherapy drugs. Conclusion: In this study, a novel consensus AAM-related gene signature is developed and validated as an independent predictor to robustly predict the overall survival from ccRCC, which would further improve the clinical outcomes.

Prognostic values of distal ureter involvement and survival outcomes in bladder cancer at T1 and T2 stages: a propensity score matching study.

PURPOSE: To study prognostic values of distal ureter involvement (DUI) and survival outcomes in bladder cancer at T1 and T2 stages. METHODS: The national Surveillance, Epidemiology, and End Results database (2004-2015) was applied to obtain bladder cancer patients. We used the Kaplan-Meier method with the log-rank test, subgroup analyses, the multivariable Cox proportional hazard model and propensity score matching (PSM). RESULTS: A total of 490 patients with DUI and 28,498 patients with non-DUI (non-involvement) were enrolled in our study. After 1:1 PSM, 490 matched pairs were picked out. The multivariable Cox regression before and after PSM revealed that the DUI group had a high risk of overall mortality (HR = 1.374, P < 0.001 before PSM; HR = 1.513, P < 0.001 after PSM) and cancer-specific mortality (HR = 1.632, P < 0.001 before PSM; HR = 1.699, P < 0.001 after PSM). The results of survival analyses showed that patients in the DUI group had lower survival probability in OS (P = 0.0011) and CSS (P < 0.0001) analyses. Nevertheless, in the subgroup analysis, significant differences were only observed in the T1 stage in terms of CSS and T2a stage in terms of OS and CSS (all P < 0.05). CONCLUSION: The prognosis of DUI was poorer than that of non-DUI. DUI was an independent risk factor for OM and CSM in bladder cancer at T1 and T2 stages especially for those at T1 and T2a stages.

New Prognostic Gene Signature and Immune Escape Mechanisms of Bladder Cancer.

Background: The immune microenvironment profoundly affects tumor prognosis and therapy. The present study aimed to reveal potential immune escape mechanisms and construct a novel prognostic signature via systematic bioinformatic analysis of the bladder cancer (BLCA) immune microenvironment. Patients and Methods: The transcriptomic data and clinicopathological information for patients with BLCA were obtained from The Cancer Genome Atlas (TCGA). Consensus clustering analysis based on the CIBERSORT and ESTIMATE algorithms was performed with patients with BLCA, which divided them into two clusters. Subsequently, the differentially expressed genes (DEGs) in the two were subjected to univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses to identify prognostic genes, which were used to construct a prognostic model. The predictive performance of the model was verified by receiver operating characteristic (ROC) and Kaplan-Meier (K-M) analyses. In addition, we analyzed the differentially altered immune cells, mutation burden, neoantigen load, and subclonal genome fraction between the two clusters to reveal the immune escape mechanism. Results: Based on the ESTIMATE and clustering analyses, patients with BLCA were classified into two heterogeneous clusters: ImmuneScoreH and ImmuneScoreL. Univariate Cox and LASSO regression analyses identified CD96 (HR = 0.83) and IBSP (HR = 1.09), which were used to construct a prognostic gene signature with significant predictive accuracy. Regarding potential immune escape mechanisms, ImmuneScoreH and ImmuneScoreL were characterized by inactivation of innate immune cell chemotaxis. In ImmuneScoreL, a low tumor antigen load might contribute to immune escape. ImmuneScoreH featured high expression of immune checkpoint molecules. Conclusion: CD96 and IBSP were considered prognostic factors for BLCA. Innate immune inactivation and a low tumor antigen load may be associated with immune escape mechanisms in both clusters. Our research complements the exploration of the immune microenvironment in BLCA.

Integrated Analysis of Microarray Studies to Identify Novel Diagnostic Markers in Bladder Pain Syndrome/Interstitial Cystitis with Hunner Lesion.

Background: The aim of this study was to identify novel genetic features of Hunner's lesion interstitial cystitis (HIC) via comprehensive analysis of the Gene Expression Omnibus (GEO) database. Methods: The GSE11783 and GSE28242 datasets were downloaded from GEO for further analysis. Differentially expressed genes (DEGs) were identified and analyzed for functional annotation. The diagnostic markers for HIC were screened and validated using the least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine recursive feature elimination (SVM-RFE) algorithms. Finally, the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm was adopted to investigate the correlation between immune cell infiltration and diagnostic markers in HIC. Results: A total of 7837 DEGs were identified in GSE11783 and 1583 DEGs in GSE28242. Venn diagrams were used to obtain 16 overlapping upregulated and 67 overlapping downregulated DEGs separately. The LASSO logistic model and SVM-RFE algorithm were used to identify 6 genes including KRT20, SLFN11, CD86, ITGA4, PLAC8, and BTN3A3 from DEGs as diagnostic markers for HIC. Their diagnostic potential in HIC and bladder pain syndrome/interstitial cystitis (BPS/IC) were acceptable. PLAC8 exhibited the best diagnostic performance in BPS/IC with an area under the curve of 0.916. The results of immune infiltration involving GSE11783 revealed that the plasma cell ratio (p = 0.017), activated memory CD4+ T cells (p = 0.009), activated dendritic cells (p = 0.01), eosinophils (p = 0.004), and neutrophils (p = 0.03) were significantly higher in HIC than in normal samples, in contrast to resting mast cells (p = 0.022). A positive correlation existed between diagnostic markers and infiltrating immune cells. Conclusion: KRT20, SLFN11, CD86, ITGA4, PLAC8, and BTN3A3 represent novel and potent diagnostic markers for HIC. They also exhibit certain diagnostic potential in BPS/IC. Immune cell infiltration might play a key role in the pathogenesis and progression of BPS/IC.

Novel circular RNA circ_0086722 drives tumor progression by regulating the miR-339-5p/STAT5A axis in prostate cancer.

Recent studies validate that circular RNAs have played critical regulatory functions in cancer biology. However, their contribution to prostate cancer (PCa) remained largely unclear. Our study aimed to explore the regulatory function and underlying mechanisms of circ_0086722 in PCa. The circ_0086722 levels in PCa tissues and cell lines were detected through qRT-PCR. In vivo and in vitro experiments were performed to evaluate the functions of circ_0086722 in PCa. Subsequently, the underlying mechanisms of circ_0086722 were explored with qRT-PCR, RNA immunoprecipitation, miRNA pull-down, and luciferase reporter assay experiments. Results revealed that circ_0086722 was highly expressed in PCa tissues and cell lines. Furthermore, high levels of circ_0086722 were positively correlated with pT3 stage, higher specimen Gleason score (>7), and worse biochemical recurrence-free survivals of PCa patients. Then, functional experiments revealed that circ_0086722 accelerated PCa proliferation and progression. Moreover, we demonstrated that circ_0086722 could mechanistically relieve the repressive effects of miR-339-5p on its target STAT5A, which facilitates PCa development. In conclusion, our findings revealed that circ_0086722 drives PCa development via the miR-339-5p/STAT5A axis, and it may function as a potential prognostic biomarker or therapeutic target for PCa treatment. Further studies with large sample sizes and sufficiently long follow-up periods are necessary to confirm the predictive role of circ_0086722 for the prognosis of PCa patients.

LINC00467 Promotes Prostate Cancer Progression via M2 Macrophage Polarization and the miR-494-3p/STAT3 Axis.

BACKGROUND: The long non-coding RNA LINC00467 plays a vital role in many malignancies. Nevertheless, the role of LINC00467 in prostate carcinoma (PC) is unknown. Herein, we aimed to explore the mechanism by which LINC00467 regulates PC progression. METHODS: We used bioinformatics analyses and RT-qPCR to investigate the expression of LINC00467 in PC tissues and cells. The function of LINC00467 in the progression of PC was confirmed by loss-of-function experiments. PC cell proliferation was assessed by CCK-8 and EdU assays. The cell cycle progression of PC cells was examined by flow cytometry. Moreover, Transwell assays were used to investigate the migration and invasion of PC cells. Western blot assays were used to detect the expression of factors associated with epithelial-mesenchymal transition. The interactions of LINC00467 with prostate cancer progression and M2 macrophage polarization were confirmed by RT-qPCR. The subcellular localization of LINC00467 was investigated via the fractionation of nuclear and cytoplasmic RNA. Bioinformatics data analysis was used to predict the correlation of LINC00467 expression with miR-494-3p expression. LINC00467/miR-494-3p/STAT3 interactions were identified by using a dual-luciferase reporter system. Finally, the influence of LINC00467 expression on PC progression was investigated with an in vivo nude mouse model of tumorigenesis. RESULTS: We established that LINC00467 expression was upregulated in PC tissues and cells. Downregulated LINC00467 expression inhibited PC cell growth, cell cycle progression, migration, and invasion. Downregulated LINC00467 expression similarly inhibited PC cell migration via M2 macrophage polarization. Western blot analysis showed that LINC00467 could regulate the STAT3 pathway. We established that LINC00467 is mainly localized to the cytoplasm. Bioinformatics analysis and rescue experiments indicated that LINC00467 promotes PC progression via the miR-494-3p/STAT3 axis. Downregulated LINC00467 expression was also able to suppress PC tumor growth in vivo. CONCLUSIONS: Our study reveals that LINC00467 promotes prostate cancer progression via M2 macrophage polarization and the miR-494-3p/STAT3 axis.