Aberrant Super-Enhancer Landscape in Enzalutamide-Resistant Prostate Cancer Cells.

Background: Castration-resistant prostate cancer (CRPC), which has developed resistance to next-generation antiandrogens, such as enzalutamide (Enz), is a lethal disease. Furthermore, transcriptional regulation by super enhancers (SEs) is crucial for the growth and spread of prostate cancer, as well as drug resistance. The functions of SEs, a significant class of noncoding DNA cis-regulatory elements, have been the subject of numerous recent studies in the field of cancer research. Materials and Methods: The goal of this research was to identify SEs associated with Enz resistance in C4-2B cells using chromatin immunoprecipitation sequencing and cleavage under targets and tagmentation (CUT&Tag). Using HOMER analysis to predict protein/gene-binding motifs, we identified master transcription factors (TFs) that may bind to SE sites. Using small interfering RNA, WST-1 assays, and qRT-PCR, we then confirmed the associations between TFs of SEs and Enz resistance. Results: A total of 999 SEs were screened from C4-2B EnzR cells in total. Incorporating analysis with RNA-seq data revealed 41 SEs to be strongly associated with the promotion of Enz resistance. In addition, we finally predicted that master TFs bind to SE-binding regions. Subsequently, we selected zinc finger protein 467 (ZFP467) and SMAD family member 3 to confirm the functional connections of master TFs with Enz resistance through SEs (ZNF467). Conclusions: In this study, SMAD3 and ZNF467 were found to be closely related to Enz-resistant CRPC. Our research uncovered a sizable group of SEs linked to Enz resistance in prostate cancer, dissected the mechanisms underlying SE Enz resistance, and shed light on potential clinical uses for SEs.

Identification of a 9-gene signature to enhance biochemical recurrence prediction in primary prostate cancer: A benchmarking study using ten machine learning methods and twelve patient cohorts.

Prostate cancer (PCa) is a prevalent malignancy among men worldwide, and biochemical recurrence (BCR) after radical prostatectomy (RP) is a critical turning point commonly used to guide the development of treatment strategies for primary PCa. However, the clinical parameters currently in use are inadequate for precise risk stratification and informing treatment choice. To address this issue, we conducted a study that collected transcriptomic data and clinical information from 1662 primary PCa patients across 12 multicenter cohorts globally. We leveraged 101 algorithm combinations that consisted of 10 machine learning methods to develop and validate a 9-gene signature, named BCR SCR, for predicting the risk of BCR after RP. Our results demonstrated that BCR SCR generally outperformed 102 published prognostic signatures. We further established the clinical significance of these nine genes in PCa progression at the protein level through immunohistochemistry on Tissue Microarray (TMA). Moreover, our data showed that patients with higher BCR SCR tended to have higher rates of BCR and distant metastasis after radical radiotherapy. Through drug target prediction analysis, we identified nine potential therapeutic agents for patients with high BCR SCR. In conclusion, the newly developed BCR SCR has significant translational potential in accurately stratifying the risk of patients who undergo RP, monitoring treatment courses, and developing new therapies for the disease.

N6-methyladenosine modified lncRNAs signature for stratification of biochemical recurrence in prostate cancer.

Nonmutational epigenetic reprogramming is a crucial mechanism contributing to the pronounced heterogeneity of prostate cancer (PCa). Among these mechanisms, N6-methyladenosine (m6A)-modified long non-coding RNAs (lncRNAs) have emerged as key players. However, the precise roles of m6A-modified lncRNAs in PCa remain to be elucidated. In this study, methylated RNA immunoprecipitation sequencing (MeRIP-seq) was conducted on primary and metastatic PCa samples, leading to the identification of 21 lncRNAs exhibiting differential methylation and expression patterns. We further established a PCa prognostic signature, named m6A-modified lncRNA score (mLs), based on 9 differential methylated lncRNAs in 4 multicenter cohorts. The high mLs score cohort exhibited a tendency for earlier biochemical recurrence (BCR) compared to the low mLs score cohort. Remarkably, the predictive performance of the mLs score surpassed that of five previously reported lncRNA-based signatures. Functional enrichment analysis underscored a negative correlation between the mLs score and lipid metabolism. Additionally, through MeRIP-qPCR, we pinpointed a hub gene, MIR210HG, which was validated through in vitro and in vivo experiments. These findings collectively illuminate the landscape of m6A-methylated lncRNAs in PCa tissue via MeRIP-seq and harness this information to prognosticate PCa outcomes using the mLs score. Furthermore, our study validates, both experimentally and mechanistically, the facilitative role of MIR210HG in driving PCa progression.

Identification and verification of an ALYREF-involved 5-methylcytosine based signature for stratification of prostate cancer patients and prediction of clinical outcome and response to therapies.

OBJECTIVES: Due to the heterogeneity of PCa, the clinical indicators used for PCa can't satisfy risk prognostication and personalized treatment. It is imperative to develop novel biomarkers for prognosis prediction and therapy response in PCa. Accumulating evidence shows that non-mutational epigenetic reprogramming, independent from genomic instability and mutation, serves as a newly added hallmark in cancer progression. METHODS: In this study, we integrated multi-center cohorts (N > 1300) to develop a RNA 5-methylcytosine regulator-based signature, the m5C score. We performed unsupervised clustering and LASSO regression to identify novel m5C-related subtypes and calculate the m5C score. Then we assessed the role of m5C cluster and m5C score in several clinical aspects such as prognosis in various molecular subtypes, responses to chemotherapy, androgen receptor signaling inhibitor (ARSI) therapy and immunotherapy in PCa. Finally, we validated the cancer-promoting performance of ALYREF through clinical data analysis and experiments in vivo and in vitro. RESULTS: The investigation revealed that the m5C score could accurately predict the biochemical recurrence (BCR) in different subtypes (the PAM50 subtypes and immunophenotypes) and the responses to chemotherapy, ARSI therapy, and immunotherapy (PD1/PD-L1). A high m5C score indicated a poor BCR prognosis in every subtype of PCa, unfavorable responses in ARSI therapy and immunotherapy (PD1/PD-L1). Moreover, the m5C reader gene termed ALYREF, yielding the highest weighed coefficient, promoted PCa progression through in silico analysis and experimental validations (in vivo and in vitro). CONCLUSIONS: The m5C signature can function in many aspects of PCa, such as the development and prognosis of the disease, and multiple therapy responses. Further, the m5C reader, ALYREF, was identified as a prognostic biomarker and a potential therapeutic target for PCa. The m5C signature could act as a brand-new tool for predicting the prognosis of patients in different molecular subtypes and patients' therapy responses and promoting customized treatments.

A prognostic signature consisting of N6-methyladenosine modified mRNAs demonstrates clinical potential in prediction of biochemical recurrence and guidance on precision therapy in prostate cancer.

Novel biomarkers are urgently needed to improve the prediction of clinical outcomes and guide personalized treatment for prostate cancer (PCa) patients. However, the role of N6-methyladenosine (m6A) modifications in PCa initiation and progression remains largely elusive. In our study, we collected benign Prostate Hyperplasia (BPH), localized PCa, and metastatic PCa samples from patients and performed methylated RNA immunoprecipitation sequencing (MeRIP-Seq) to map m6A-methylated mRNAs. Furthermore, we developed a prognostic signature based on 239 differentially methylated RNAs and the TCGA-PRAD dataset, which can be used to calculate an m6A-modified mRNA (MMM) score for a PCa patient, validated by independent multi-center cohorts. Our findings revealed that differential m6A modifications were positively correlated with altered expressions of mapped m6A-modified mRNAs. Higher MMM scores were associated with shorter times to biochemical recurrence (BCR) in PCa patients, and the MMM scoring system outperformed three well-established signatures in nine independent validation cohorts, as demonstrated by Kaplan-Meier survival analysis, C-index and ROC. Patients who did not respond to androgen receptor signaling inhibitor (ARSI) therapy and immunotherapy were found to have high MMM scores. Two hub genes, TLE1 and PFKL, were confirmed to have m6A sites through MeRIP-qPCR, and their knockdown promoted PCa cell invasion. Bioinformatics analysis of single-cell databases identified cell types with high transcript abundance levels of these two genes. In summary, our study is the first to perform transcriptome-wide m6A mapping in prostate tissues. The translational potential of a prognostic signature, comprising m6A-methylated mRNAs, in predicting clinical outcomes and therapy responses for PCa patients, is demonstrated.

Integrated analysis reveals prognostic value and progression-related role of AMIGO2 in prostate cancer.

Background: Even though emerging studies supplied evidence that Adhesion Molecule with Ig Like Domain family 2 (AMIGO2) plays a critical role in numerous cancers, comprehensive analysis of the prognostic value and significant role of AMIGO2 in prostate cancer (PCa) have not been described. Methods: Differentially expressed analysis, survival analysis and univariate cox regression analysis were first performed to explore the diagnostic and prognostic role of AMIGO2 in various cancers, especially in PCa. Tissue microarray were used to examined the association between AMGIO2 and clinical features. Multivariate cox regression analysis, concordance index, nomogram construction, the receiver operator characteristic curve and calibration curves were further used to discover the effects of AMIGO2 on recurrence-free survival (RFS) and clinicopathological characteristics, including age, Gleason score (GS) and tumor stage. Genetic and Epigenetic Alterations analysis were further conducted to explore the potential effect of AMIGO2 in PCa and examined by biological function analysis and in vitro experiments. Results: AMIGO2 was associated with poor RFS (P<0.05) and differentially expressed (P<0.05) in multiple cancer type, especially in PCa. Besides, decreasing the expression of AMIGO2 inhibited PCa cell proliferation and colony formation in vitro. In addition, AMIGO2 was a reliable prognostic marker providing additional information (C-index: 0.7) that supplement the currently used prognosis evaluation system, e.g., T stage (C-index: 0.62) and GS (C-index: 0.65). A novel nomogram was established based on AMIGO2, tumor stage and GS with accuracies (areas under curve) of 0.70, 0.78 and 0.82 for predicting 3-, 5- and 7-year RFS, respectively. Bioinformatic analysis and in vitro examination also suggested that AMIGO2 might involve in the progression of PCa tumors inducing epithelial mesenchymal transition (EMT). Conclusions: We identified AMIGO2 as a pan-cancer gene that could not only be a prognostic biomarker in various cancers, especially in PCa, but may functionally promoting PCa progression via EMT and mediating docetaxel resistance, suggesting AMIGO2 as a potential target for future treatment of PCa.

Differential Expression of E2F Transcription Factors and Their Functional and Prognostic Roles in Human Prostate Cancer.

Given the tumor heterogeneity, most of the current prognostic indicators cannot accurately evaluate the prognosis of patients with prostate cancer, and thus, the best opportunity to intervene in the progression of this disease is missed. E2F transcription factors (E2Fs) have been reported to be involved in the growth of various cancers. Accumulating studies indicate that prostate cancer (PCa) carcinogenesis is attributed to aberrant E2F expression or E2F alteration. However, the expression patterns and prognostic value of the eight E2Fs in prostate cancer have yet to be explored. In this study, The Cancer Genome Atlas (TCGA), Kaplan-Meier Plotter, Metascape, the Kyoto Encyclopedia of Genes and Genomes (KEGG), CIBERSORT, and cBioPortal and bioinformatic analysis were used to investigate E2Fs in patients with PCa. Our results showed that the expression of E2F1-3, E2F5, and E2F6 was higher in prostate cancer tissues than in benign tissues. Furthermore, elevated E2F1-3 and E2F5 expression levels were associated with a higher Gleason score (GS), advanced tumor stage, and metastasis. Survival analysis suggested that high transcription levels of E2F1-3, E2F5, E2F6, and E2F8 were associated with a higher risk of biochemical recurrence. In addition, we developed a prognostic model combining E2F1, E2F6, Gleason score, and the clinical stage that may accurately predict a biochemical recurrence-free survival. Functional enrichment analysis revealed that the E2F family members and their neighboring genes were mainly enriched in cell cycle-related pathways. Somatic mutations in different subgroups were also investigated, and immune components were predicted. Further experiments are warranted to clarify the biological associations between Pca-related E2F family genes, which may influence prognosis via the cell cycle pathway.

Tumor Suppressor Role and Clinical Significance of the FEV Gene in Prostate Cancer.

Background: In our previous research, we developed a 32-gene risk index model that may be utilized as a robust prognostic method for predicting prostate cancer (PCa) recurrence after surgery. Among the 32 genes, the Fifth Ewing Variant (FEV) gene was one of the top downregulated genes in relapsed PCa. However, current understanding of the FEV gene and its involvement in PCa is limited. Methods: FEV mRNA expression was analyzed and correlated to clinical outcomes in PCa patients who underwent prostatectomy at the Massachusetts General Hospital. Specimens from tissue microarray (TMA) including 102 prostate cancer patients were analysis for the expression of FEV. Meanwhile, FEV expression profiles were also assessed in PCa cell lines and in BPH-1 prostate epithelial cells using western blotting and quantitative reverse transcription-PCR (qRT-PCR). Furthermore, we transfected LNCaP and PC-3 cells with either an empty vector or full-length FEV gene and performed in vitro cell functional assays. The part FEV plays in tumor xenograft growth was also assessed in vivo. Results: Of the 191 patients included in this study base on the DASL dataset, 77 (40.3%) and 24 (13.6%), respectively, developed prostate-specific antigen (PSA) relapse and metastasis postradical prostatectomy. Significant FEV downregulation was observed in PCa patients showing PSA failure and metastasis. The protein expression of FEV was significantly negatively correlated with the Gleason score and pathological stage in prostate cancer tissues. Similarly, FEV expression significantly decreased in all PCa cell lines relative to BPH-1 (all P < 0.05). Functional assays revealed that FEV expression markedly inhibited PCa cell growth, migration, and invasion, which in turn significantly repressed the growth of tumor xenografts in vivo. Conclusion: The results of this study suggest an association between downregulated FEV expression and PSA relapse in PCa patients. In addition, FEV may act as a tumor suppressor in PCa.

Altered small non-coding RNA expression profiles of extracellular vesicles in the prostatic fluid of patients with chronic pelvic pain syndrome.

Chronic pelvic pain syndrome (CPPS) and chronic prostatitis (CP) is difficult to distinguish from each other, herein termed CP/CPPS. The present study aimed at gaining further insight into the change in extracellular vesicles (EVs) in the prostatic fluid of males with CPPS. From December 2019 to November 2020, after clinical screening, 24 patients with CPPS without obvious urinary symptoms and 13 healthy male participants were included. EVs were isolated from expressed prostatic secretion (EPS) of all subjects. The small non-coding ribonucleic acid (sncRNA) expression of EVs was sequenced, analyzed, and validated by quantitative real-time polymerase chain reaction (qPCR) assays. The results showed that numerous sncRNAs were differentially expressed between the patients and healthy participants. Further qPCR assays validated that several chronic pain-related miRNAs, including miR-204-5p, let-7d-3p, let-7b-3p, let-7c-3p, miR-146a-5p, and miR-320a-5p, were differentially expressed. Series sncRNAs including several chronic pain-related miRNAs were altered in EVs in prostatic fluid of patients with CPPS, which may serve as diagnostic markers for CPPS.

Mannose inhibits the growth of prostate cancer through a mitochondrial mechanism.

The limited treatment options for advanced prostate cancer (PCa) lead to the urgent need to discover new anticancer drugs. Mannose, an isomer of glucose, has been reported to have an anticancer effect on various tumors. However, the anticancer effect of mannose in PCa remains unclear. In this study, we demonstrated that mannose inhibits the proliferation and promotes the apoptosis of PCa cells in vitro, and mannose was observed to have an anticancer effect in mice without harming their health. Accumulation of intracellular mannose simultaneously decreased the mitochondrial membrane potential, increased mitochondrial and cellular reactive oxygen species (ROS) levels, and reduced adenosine triphosphate (ATP) production in PCa cells. Mannose treatment of PCa cells induced changes in mitochondrial morphology, caused dysregulated expression of the fission protein, such as fission, mitochondrial 1 (FIS1), and enhanced the expression of proapoptotic factors, such as BCL2-associated X (Bax) and BCL2-antagonist/killer 1 (Bak). Furthermore, lower expression of mannose phosphate isomerase (MPI), the key enzyme in mannose metabolism, indicated poorer prognosis in PCa patients, and downregulation of MPI expression in PCa cells enhanced the anticancer effect of mannose. This study reveals the anticancer effect of mannose in PCa and its clinical significance in PCa patients.

Integrin-Linked Kinase (ILK) Regulates Urinary Stem Cells Differentiation into Smooth Muscle via NF-κB Signal Pathway.

OBJECTIVES: Urinary stem cells (USCs) have the capacity for unlimited growth and are promising tools for the investigations of cell differentiation and urinary regeneration. However, the limited life span significantly restricts their usefulness. This study is aimed at exploring the effect of integrin-linked kinase (ILK) on the smooth muscle cells (SMCs) differentiation of the dog USCs and investigating its molecular mechanism. METHODS: An immortalized USCs cell line with the molecular markers and biological functions was prepared. After successfully inducing the differentiation of USCs into SMCs, the expression level of the unique key factor and its mechanisms in this process was determined through real-time polymerase chain reaction, Western blot, or Immunofluorescence staining. RESULTS: We found that high cell density promoted USCs differentiation SMCs, and ILK was necessary for USCs differentiation into SMCs. Knocking down ILK decreased the expression of SMCs specific-marker, while using a selective ILK agonist increased the expression of SMCs specific-marker. Furthermore, ILK regulated SMCs differentiation in part through the activation of NF-κB pathway in USCs. A NF-κB activity assay showed overexpression of ILK could significantly upregulate NF-κB p50 expression, and NF-κB p50 acts as downstream signal molecular of ILK. CONCLUSION: High cell density induces the differentiation of USCs into SMCs, and ILK is a key regulator of myogenesis. Furthermore, NF-κB signaling pathway might play a crucial role in this process.

Claspin Overexpression Promotes Tumor Progression and Predicts Poor Clinical Outcome in Prostate Cancer.

Background: Claspin (CLSPN) expression is acknowledged as a poor clinical prognostic factor in various tumors. However, the clinical characteristics and biological functions of CLSPN in prostate cancer (PCa) are still to be clarified. The aim of our study was to evaluate the association of CLSPN expression during PCa progression and its potential role in prognosis. Methods: We analyzed mRNA expression of the CLSPN gene with various clinicopathological features using the Cancer Genome Atlas and GSE21032 dataset. Immunohistochemical assays were used to detect the protein expression levels of CLSPN in human PCa tissue microarrays. Furthermore, we characterized the role of CLSPN in PCa progression through in vitro experiments using a CLSPN knockout. Results: Immunohistochemistry and public datasets revealed that CLSPN expression was increased in PCa with: a high Gleason score; advanced pathological stage; and positive surgical margins. In addition, upregulation of CLSPN was correlated with shorter biochemical recurrence (BCR)-free survival and overall survival. After we knocked-out CLSPN in DU145 and LNCaP cells, the in vitro phenotypic results showed that the ability of the knockouts to proliferate, migrate, and invade was attenuated; but that apoptosis was promoted. Conclusions: Our data support an oncogenic role for CLSPN in PCa progression. Moreover, increased CLSPN expression was identified as an independent factor in predicting bCR-free survival and disease-free survival in PCa patients.

Down-regulation of ACACA suppresses the malignant progression of Prostate Cancer through inhibiting mitochondrial potential.

Background and aim: Silencing the expression of ACACA inhibits cell proliferation and induces apoptosis in prostate cancer LNCaP cells. However, the role of ACACA in other prostate cancer cells is not fully understood. Also, the effect of knocking down ACACA gene on mitochondria remains unclear. This study aimed to discover the specific role of ACACA gene in prostate cancer (PCa) DU145 and PC3 cells as well as its effects on mitochondrial potential. Methods: The expression of ACACA gene was detected in human prostate cancer tissue microarrays and assessed in different clinical stages. Then, prostate cancer cell lines with low expression of ACACA were constructed to evaluate the changes in their cell cycle, proliferation, and metabolites. The effect of ACACA on tumor formation in vivo was analyzed. Also, mito-ATP production, mitochondrial staining, and mtDNA, nicotinamide adenine dinucleotide (NAD+/NADH), and reactive oxygen species (ROS) levels were detected. Results: ACACA was expressed more strongly in prostate cancer tissues. The expression level of ACACA was higher in patients with advanced PCa than in patients with lower grades. The proliferation ability reduced in ACACA-knockdown cells. In in vivo tests, the tumor volume and weight were lower in the experimental group than in the control group. Mito-ATP production decreased significantly after ACACA suppression, mtDNA levels and MitoTracker staining decreased in the experimental group. The ratio of NAD+/NADH and ROS levels were upregulated in the experimental group. Conclusion: Targeting ACACA gene and mitochondria might serve as a novel therapy for prostate cancer treatment.