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.

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.

RNA modification Regulators' Co-Expression Score (RMRCoeS) predicts biochemical recurrence and therapy response in prostate cancer: A multi-omics and experimental validation study.

BACKGROUND: Owing to the heterogeneity of prostate cancer (PCa), the clinical indicators traditionally fall short of meeting the requirements for personalized medicine. The realm of RNA modification has emerged as an increasingly relevant domain, shedding light on its pivotal role in tumor heterogeneity. However, the specific contributions of RNA modification regulators within the context of PCa remain largely unexplored. METHODS: In this study, we undertook a literature review to summarize the common 8 types of RNA modifications (ac4c, AI, APA, m1A, m5c, m6A, m7G, Ψ) encompassing a total of 84 regulators. Moreover, we integrated multi-center cohorts with Ridge regression to develop the Regulators' Co-Expression Score (RMRCoeS). Then we assessed the role of RMRCoeS in several clinical aspects such as biochemical recurrence (BCR), responses to chemotherapy, androgen receptor signaling inhibitor (ARSI) therapy and immunotherapy in PCa. Finally, we validated the cancer-promoting performance of five hub genes through immunohistochemistry and in vitro assays. RESULTS: Within the mutation landscape of RNA modification regulators, we observed a relatively low overall mutation rate. Remarkably, RMRCoeS, comprising 81 RNA modification regulators, exhibited a notable capability for accurately predicting the prognosis and therapeutic responses in PCa patients subjected to BCR, chemotherapy, ARSI therapy, and immunotherapy. A high RMRCoeS was indicative of a poor prognosis and unfavorable therapy responses. Functional enrichment analysis unveiled that RMRCoeS may exert its influence on PCa progression through various metabolic pathways. Furthermore, a higher RMRCoeS showed a positive correlation with elevated CNV mutations. Lastly, we validated the oncogene effects of CPSF4, WBSCR22, RPUSD3, TRMT61A, and NSUN5-five hub regulators-within the context of PCa. CONCLUSION: The function of different RNA modifications is interconnected. Comprising eight distinct RNA modifications' regulators, RMRCoeS exhibits multifaceted roles in various aspects of PCa, including disease progression, prognosis, and responses to multiple therapies. Furthermore, we provide the initial validation of the oncogene effect associated with WBSCR22, RPUSD3, TRMT61A and NSUN5 in PCa. Our findings offer novel insights into the significance of RNA modifications in PCa personalized medicine.

Lamin B1: a novel biomarker in adult and pediatric adrenocortical carcinoma.

Adrenocortical carcinoma (ACC) is a malignancy with a poor prognosis and high mortality rate. A high tumor mutational burden (TMB) has been found to be associated with poor prognosis in ACC. Thus, exploring ACC biomarkers based on TMB holds significant importance for patient risk stratification. In our research, we utilized weighted gene coexpression network analysis and an assay for transposase-accessible chromatin with high-throughput sequencing to identify genes associated with TMB. Through the comprehensive analysis of various public datasets, Lamin B1 (LMNB1) was identified as a biomarker associated with a high TMB and low chromatin accessibility. Immunohistochemical staining demonstrated high expression of LMNB1 in ACC compared to noncancerous tissues. Functional enrichment analyses revealed that the function of LMNB1 is associated with cell proliferation and division. Furthermore, cell assays suggested that LMNB1 promotes tumor proliferation and invasion. In addition, mutation analysis suggested that the high expression of LMNB1 is associated with TP53 mutations. Additionally, LMNB1 was highly expressed in the vast majority of solid tumors across cancers. In our immune analysis, we discovered that the high expression of LMNB1 might suppress the infiltration of CD8+ T cells in the ACC microenvironment. In summary, LMNB1 is a predictive factor for the poor prognosis of adult and pediatric ACC. Its high expression in ACC is positively associated with high TMB and lower chromatin accessibility, and it promotes ACC cell proliferation and invasion. Therefore, LMNB1 holds promise as a novel biomarker and potential therapeutic target for ACC.

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.

M6A-modified circRBM33 promotes prostate cancer progression via PDHA1-mediated mitochondrial respiration regulation and presents a potential target for ARSI therapy.

N6-Methyladenosine (m6A) is the most prevalent RNA modification in various types of RNA, including circular RNAs (circRNAs). Mounting evidence has shown that circRNAs may play critical roles in diverse malignancies. However, the biological relevance of m6A modification of circRNAs in prostate cancer (PCa) remains unclear and needs to be elucidated. Our data showed that circRBM33 was m6A-modified and was more highly expressed in PCa cells than in normal cells/tissues. The in vitro and in vivo experiments showed that downregulation/upregulation of circRBM33 inhibited/promoted tumour growth and invasion, respectively. Decreasing m6A levels rescued the tumour-promoting effect of circRBM33. Additionally, once modified by m6A, circRBM33 interacts with FMR1 by forming a binary complex that sustains the mRNA stability of PDHA1, a downstream target gene. Suppressed/overexpressed circRBM33 lowered/enhanced the ATP production, the acetyl-CoA levels and the NADH/NAD+ ratio. Moreover, depletion of circRBM33 significantly increased the response sensitivity to androgen receptor signalling inhibitor (ARSI) therapy, including enzalutamide and darolutamide, in prostate tumours. Our study suggested that the m6A-mediated circRBM33-FMR1 complex can activate mitochondrial metabolism by stabilizing PDHA1 mRNA, which promotes PCa progression, and can attenuate circRBM33 increased ARSI effectiveness in PCa treatment. This newly discovered circRNA may serve as a potential therapeutic target for PCa.

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 high-throughput analysis identifies super enhancers in metastatic castration-resistant prostate cancer.

Background: Metastatic castration-resistant prostate cancer (mCRPC) is a highly aggressive stage of prostate cancer, and non-mutational epigenetic reprogramming plays a critical role in its progression. Super enhancers (SE), epigenetic elements, are involved in multiple tumor-promoting signaling pathways. However, the SE-mediated mechanism in mCRPC remains unclear. Methods: SE-associated genes and transcription factors were identified from a cell line (C4-2B) of mCRPC by the CUT&Tag assay. Differentially expressed genes (DEGs) between mCRPC and primary prostate cancer (PCa) samples in the GSE35988 dataset were identified. What's more, a recurrence risk prediction model was constructed based on the overlapping genes (termed SE-associated DEGs). To confirm the key SE-associated DEGs, BET inhibitor JQ1 was applied to cells to block SE-mediated transcription. Finally, single-cell analysis was performed to visualize cell subpopulations expressing the key SE-associated DEGs. Results: Nine human TFs, 867 SE-associated genes and 5417 DEGs were identified. 142 overlapping SE-associated DEGs showed excellent performance in recurrence prediction. Time-dependent receiver operating characteristic (ROC) curve analysis showed strong predictive power at 1 year (0.80), 3 years (0.85), and 5 years (0.88). The efficacy of his performance has also been validated in external datasets. In addition, FKBP5 activity was significantly inhibited by JQ1. Conclusion: We present a landscape of SE and their associated genes in mCPRC, and discuss the potential clinical implications of these findings in terms of their translation to the clinic.

A five-pseudouridylation-associated-LncRNA classifier for primary prostate cancer prognosis prediction.

Background: Prostate cancer (PCa) is one of the most common cancers in males around the globe, and about one-third of patients with localized PCa will experience biochemical recurrence (BCR) after radical prostatectomy or radiation therapy. Reportedly, a proportion of patients with BCR had a poor prognosis. Cumulative studies have shown that RNA modifications participate in the cancer-related transcriptome, but the role of pseudouridylation occurring in lncRNAs in PCa remains opaque. Methods: Spearman correlation analysis and univariate Cox regression were utilized to determine pseudouridylation-related lncRNAs with prognostic value in PCa. Prognostic pseudouridylation-related lncRNAs were included in the LASSO (least absolute shrinkage and selection operator) regression algorithm to develop a predictive model. KM (Kaplan-Meier) survival analysis and ROC (receiver operating characteristic) curves were applied to validate the constructed model. A battery of biological cell assays was conducted to confirm the cancer-promoting effects of RP11-468E2.5 in the model. Results: A classifier containing five pseudouridine-related lncRNAs was developed to stratify PCa patients on BCR and named the "ψ-lnc score." KM survival analysis showed patients in the high ψ-lnc score group experienced BCR more than those in the low ψ-lnc score group. ROC curves demonstrated that ψ-lnc score outperformed other clinical indicators in BCR prediction. An external dataset, GSE54460, was utilized to validate the predictive model's efficacy and authenticity. A ceRNA (competitive endogenous RNA) network was constructed to explore the model's potential molecular functions and was annotated through GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analyses. RP11-468E2.5 was picked for further investigation, including pan-cancer analysis and experimental validation. Preliminarily, RP11-468E2.5 was confirmed as a tumor promoter. Conclusion: We provide some evidence that pseudouridylation in lncRNA played a role in the development of PCa and propose a novel prognostic classifier for clinical practice.

Gut dysbiosis promotes prostate cancer progression and docetaxel resistance via activating NF-κB-IL6-STAT3 axis.

BACKGROUND: The gut microbiota is reportedly involved in the progression and chemoresistance of various human malignancies. However, the underlying mechanisms behind how it exerts some effect on prostate cancer, as an extra-intestinal tumor, in a contact-independent way remain elusive and deserve exploration. Antibiotic exposure, one of the various factors affecting the gut microbiota community and capable of causing gut dysbiosis, is associated with multiple disorders. This study aims to preliminarily clarify the link between gut dysbiosis and prostate cancer. RESULTS: First, we discovered that perturbing the gut microbiota by consuming broad-spectrum antibiotics in water promoted the growth of subcutaneous and orthotopic tumors in mice. Fecal microbiota transplantation could transmit the effect of antibiotic exposure on tumor growth. Then, 16S rRNA sequencing for mouse feces indicated that the relative abundance of Proteobacteria was significantly higher after antibiotic exposure. Meanwhile, intratumoral lipopolysaccharide (LPS) profoundly increased under the elevation of gut permeability. Both in vivo and in vitro experiments revealed that the NF-κB-IL6-STAT3 axis activated by intratumoral LPS facilitated prostate cancer proliferation and docetaxel chemoresistance. Finally, 16S rRNA sequencing of patients' fecal samples revealed that Proteobacteria was enriched in patients with metastatic prostate cancer and was positively correlated with plasma IL6 level, regional lymph node metastasis status, and distant metastasis status. The receiver operating characteristic (ROC) curves showed that the relative abundance of Proteobacteria had better performance than the prostate-specific antigen (PSA) level in predicting the probability of distant metastasis in prostate cancer (area under the ROC curve, 0.860; p < 0.001). CONCLUSION: Collectively, this research demonstrated that gut dysbiosis, characterized by the enrichment of Proteobacteria due to antibiotic exposure, resulted in the elevation of gut permeability and intratumoral LPS, promoting the development of prostate cancer via the NF-κB-IL6-STAT3 axis in mice. Considering findings from human patients, Proteobacteria might act as an intestinal biomarker for progressive prostate cancer. Video Abstract.

Autophagy-related circRNA evaluation reveals hsa_circ_0001747 as a potential favorable prognostic factor for biochemical recurrence in patients with prostate cancer.

Prostate cancer (PCa) is a common high-incidence malignancy in men, some of whom develop biochemical recurrence (BCR) in the advanced stage. However, there are currently no accurate prognostic indicators of BCR in PCa. The aim of our study was to identify an autophagy-related circular RNA prognostic factor of BCR for patients with PCa. In this study, immunochemistry revealed that the classic autophagy marker MAP1LC3B was positively correlated with Gleason score. Least absolute shrinkage and selector operator regression were conducted to develop a novel prognostic model with tenfold cross-validation and an L1 penalty. Five autophagy-related circRNA signatures were included in the prognostic model. Patients with PCa were ultimately divided into high- and low-risk groups, based on the median risk score. Patients with PCa, who had a high risk score, were more likely to develop BCR in a shorter period of time. Univariate and multivariate Cox regression analyses demonstrated that the risk score was an independent variable for predicting BCR in PCa. In addition, a prognostic nomogram integrated with the risk score and numerous clinicopathological parameters was developed to accurately predict 3- and 5-year BCR of patients with PCa. Finally, the hsa_circ_0001747 signature was selected for further experimental verification in vitro and in vivo, which showed that downregulated hsa_circ_0001747 might facilitate PCa via augmenting autophagy. Our findings indicate that the autophagy-related circRNA signature hsa_circ_0001747 may serve as a promising indicator for BCR prediction in patients with PCa.

5-Methylcytosine RNA Methyltransferases-Related Long Non-coding RNA to Develop and Validate Biochemical Recurrence Signature in Prostate Cancer.

The effects of 5-methylcytosine in RNA (m5C) in various human cancers have been increasingly studied recently; however, the m5C regulator signature in prostate cancer (PCa) has not been well established yet. In this study, we identified and characterized a series of m5C-related long non-coding RNAs (lncRNAs) in PCa. Univariate Cox regression analysis and least absolute shrinkage and selector operation (LASSO) regression analysis were implemented to construct a m5C-related lncRNA prognostic signature. Consequently, a prognostic m5C-lnc model was established, including 17 lncRNAs: MAFG-AS1, AC012510.1, AC012065.3, AL117332.1, AC132192.2, AP001160.2, AC129510.1, AC084018.2, UBXN10-AS1, AC138956.2, ZNF32-AS2, AC017100.1, AC004943.2, SP2-AS1, Z93930.2, AP001486.2, and LINC01135. The high m5C-lnc score calculated by the model significantly relates to poor biochemical recurrence (BCR)-free survival (p < 0.0001). Receiver operating characteristic (ROC) curves and a decision curve analysis (DCA) further validated the accuracy of the prognostic model. Subsequently, a predictive nomogram combining the prognostic model with clinical features was created, and it exhibited promising predictive efficacy for BCR risk stratification. Next, the competing endogenous RNA (ceRNA) network and lncRNA-protein interaction network were established to explore the potential functions of these 17 lncRNAs mechanically. In addition, functional enrichment analysis revealed that these lncRNAs are involved in many cellular metabolic pathways. Lastly, M AFG-AS1 was selected for experimental validation; it was upregulated in PCa and probably promoted PCa proliferation and invasion in vitro. These results offer some insights into the m5C's effects on PCa and reveal a predictive model with the potential clinical value to improve the prognosis of patients with PCa.

HnRNP-L-regulated circCSPP1/miR-520h/EGR1 axis modulates autophagy and promotes progression in prostate cancer.

The circRNAs, a new subclass of non-coding RNAs that are catalyzed by RNA-binding proteins (RBPs), have been reported to be associated with the progression of multiple types of cancer. We previously discovered that heterogeneous nuclear ribonucleoprotein L (HnRNP-L), a multi-functional RBP, is associated with pro-proliferation and anti-apoptosis activities in prostate tumor cells. In this study, we aim to establish the biological relevance of circCSPP1 (a newly discovered signature circRNA in prostate cancer [PCa]) and HnRNP-L to prostate cancer progression. First, we demonstrated that circCSPP1 expression was higher in prostate cancer tissues than in benign tissues and higher in prostate cancer cells than in benign cells. Then, the in vitro gain- and loss-of-function experiments showed that the circCSPP1 expression in prostate cancer cells was regulated by HnRNP-L, and the increased circCSPP1 significantly induced autophagy, which led to an enhanced potential in proliferation, migration, and invasion of prostate cancer cells. These results were consistent with the in vivo experiment where increased or decreased circCSPP1 was associated with higher or slower growth rate in grafted tumors. Finally, we demonstrated the potential competing endogenous RNA network, involving circCSPP1, miR-520h, and early growth response factor 1 (EGR1), in prostate cancer cells, which may play an important role in prostate cancer progression. Our study indicated that the increase in circCSPP1 in prostate cancer, which may be catalyzed by HnRNP-L, can induce cellular autophagy through the circCSPP1-miR-520h-EGR1 axis, leading to the progression of prostate tumor. This newly discovered circRNA biomarker may be used for clinical prognosis of prostate cancer as well as for development of novel therapy plans.

Phosphoribosyl pyrophosphate synthetases 2 knockdown inhibits prostate cancer progression by suppressing cell cycle and inducing cell apoptosis.

Phosphoribosyl pyrophosphate synthetases 2 (PRPS2) protein function as nucleotide synthesis enzyme that plays vital roles in cancer biology. However, the expression profile and function of PRPS2 in prostate cancer (PCa) remain to be identified. Here we investigated the expression of PRPS2 protein in human PCa and paired normal tissues by immunohistochemistry, meanwhile the regulatory effects on cell proliferation, apoptosis and growth of xenograft tumors in nude mice were evaluated in PCa cells with PRPS2 depletion. Moreover, the signaling pathways were also explored by western blot analysis and quantitative polymerase chain reaction assays. We found that PRPS2 was dramatically upregulated in prostate adenocarcinoma tissues in comparison with normal tissues, and that increased PRPS2 was linked intimately to advanced clinical stage and pT status. Functional experiments showed that knockdown of PRPS2 significantly suppressed cell growth both in vitro and in vivo. In addition, depletion of PRPS2 induced G1 phase cell cycle arrest and elevated cell apoptosis. Silencing of PRPS2 resulted in the decreased expression of Bcl­2 and cyclinD1 and increased levels of Bax, cleavage of caspases­3, caspases­9 and PARP. Furthermore, we also detected PRPS2 expression was significantly induced after DHT treatment, which implied the important role of PRPS2 in oncogenesis of PCa. Taken together, our findings elucidated that PRPS2 may be a potential novel candidate for PCa therapy.

An Eight-CircRNA Assessment Model for Predicting Biochemical Recurrence in Prostate Cancer.

Prostate cancer (PCa) is a high morbidity malignancy in males, and biochemical recurrence (BCR) may appear after the surgery. Our study is designed to build up a risk score model using circular RNA sequencing data for PCa. The dataset is from the GEO database, using a cohort of 144 patients in Canada. We removed the low abundance circRNAs (FPKM < 1) and obtained 546 circRNAs for the next step. BCR-related circRNAs were selected by Logistic regression using the "survival" and "survminer" R package. Least absolute shrinkage and selector operation (LASSO) regression with 10-fold cross-validation and penalty was used to construct a risk score model by "glmnet" R software package. In total, eight circRNAs (including circ_30029, circ_117300, circ_176436, circ_112897, circ_112897, circ_178252, circ_115617, circ_14736, and circ_17720) were involved in our risk score model. Further, we employed differentially expressed mRNAs between high and low risk score groups. The following Gene Ontology (GO) analysis were visualized by Omicshare Online tools. As per the GO analysis results, tumor immune microenvironment related pathways are significantly enriched. "CIBERSORT" and "ESTIMATE" R package were used to detect tumor-infiltrating immune cells and compare the level of microenvironment scores between high and low risk score groups. What's more, we verified two of eight circRNA's (circ_14736 and circ_17720) circular characteristics and tested their biological function with qPCR and CCK8 in vitro. circ_14736 and circ_17720 were detected in exosomes of PCa patients' plasma. This is the first bioinformatics study to establish a prognosis model for prostate cancer using circRNA. These circRNAs were associated with CD8+ T cell activities and may serve as a circRNA-based liquid biopsy panel for disease prognosis.