Prediction of Biochemical Recurrence-Free Survival of Prostate Cancer Patients Leveraging Multiple Gene Expression Profiles in Tumor Microenvironment.
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ABSTRACT:
SUBMITTER: Zhou R
PROVIDER: S-EPMC8495167 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Objective: To identify ferroptosis-related molecular clusters, and to develop and validate a ferroptosis-based molecular signature for predicting biochemical recurrence-free survival (BCRFS) and tumor immune microenvironment of prostate cancer (PCa). Materials and Methods: The clinical data and transcriptome data of PCa were downloaded from TCGA and GEO database. Ferroptosis-related genes (FRGs) were obtained from FerrDb database. We performed consensus clustering analysis to identify ferroptosis-related molecular subtypes for PCa. Univariate and multivariate Cox regression analysis were used to establish a ferroptosis-based signature for predicting BCRFS. Internal verification, external verification and subgroup survival analysis were then successfully performed. Results: There was a total of 40 differentially expressed FRGs in PCa. We then identified three ferroptosis-related molecular clusters of PCa, which have significantly different immune infiltrating cells, tumor immune microenvironment and PD-L1 expression level. More importantly, a novel ferroptosis-based signature for predicting BCRFS of PCa based on four FRGs (including ASNS, GPT2, NFE2L2, RRM2) was developed. Internal and external verifications were then successfully performed. Patients with high-risk score were associated with significant poor BCRFS compared with those with low-risk score in training cohort, testing cohort and validating cohort, respectively. The area under time-dependent Receiver Operating Characteristic (ROC) curve were 0.755, 0.705 and 0.726 in training cohort, testing cohort and validating cohort, respectively, indicating the great performance of this signature. Independent prognostic analysis indicated that this signature was an independent predictor for BCRFS of PCa. Subgroup analysis revealed that this signature was particularly suitable for younger or stage T III-IV or stage N0 or cluster 1-2 PCa patients. Patients with high-risk score have significantly different tumor immune microenvironment in comparison with those with low-risk score. The results of qRT-PCR successfully verified the mRNA expression levels of ASNS, GPT2, RRM2 and NFE2L2 in DU-145 and RWPE-1 cells while the results of IHC staining exactly verified the relative protein expression levels of ASNS, GPT2, RRM2 and NFE2L2 between PCa and BPH tissues. Conclusions: This study successfully identified three ferroptosis-related molecular clusters. Besides, we developed and validated a novel ferroptosis-based molecular signature, which performed well in predicting BCRFS and tumor immune microenvironment of PCa.
| S-EPMC8773967 | biostudies-literature
Project description:BackgroundsFatty acid synthase (FASN) has been regarded as a prognostic marker in prostate cancer (PCa). In this study, we evaluated FASN expression at both mRNA and protein levels and assessed the association between FASN expression and prognosis in male Han Chinese with PCa treated with radical prostatectomy (RP).MethodsExpression profile and prognostic value of FASN were analyzed in tissue microarray (TMA) and data retrieved from databases including TCGA public database, GEO database, and our sequencing data with whole clinicopathological characteristics.ResultsFASN expression was associated with clinical parameters and biochemical recurrence of prostate cancer. The relative expression of FASN mRNA was higher in the tumor tissue in all public databases and our sequencing data (p < 0.001). A similar result was seen in tissue microarray (TMA) (p < 0.001). Analysis of our sequencing data indicated that FASN's relative expression was associated with tumor stage (p = 0.048), and FASN expression was positively associated with the Gleason score (p = 0.004) and seminal vesicle invasion (p = 0.011) in TMA. We found that high FASN expression was an independent predictor of shorter BCR-free survival with univariate and multivariate survival analysis (p < 0.05), rendering FASN an optimal prognostic biomarker in male Han Chinese with prostate cancer.ConclusionsOur study demonstrated that FASN was overexpressed at mRNA and protein levels in PCa. We found that patients with high FASN expression had a shorter BCR-free survival, showing its value as a prognostic biomarker in male Han Chinese with PCa.
| S-EPMC7321525 | biostudies-literature
Project description:BackgroundIdentifying prostate cancer (PCa) patients with a worse prognosis and a higher risk of biochemical recurrence (BCR) is essential to guide treatment choices. Here, we aimed to identify possible imaging biomarker (perfusion/diffusion + radiomic features) profiles extracted from MRIs that were able to discriminate patients according to their risk or the occurrence of BCR 10 years after diagnosis, as well as to evaluate their predictive value with or without clinical data.MethodsPatients with localized PCa receiving neoadjuvant androgen deprivation therapy and radiotherapy were retrospectively evaluated. Imaging features were extracted from MRIs for each prostate region or for the whole gland. Univariate and multivariate analyses were conducted.Results128 patients (mean [range] age, 71 [50-83] years) were included. Prostate region-wise imaging biomarker profiles mainly composed of radiomic features allowed discriminating risk groups and patients experiencing BCR. Heterogeneity-related radiomic features were increased in patients with worse prognosis and with BCR. Overall, imaging biomarkers profiles retained good predictive ability (AUC values superior to 0.725 in most cases), which generally improved when clinical data were included (particularly evident for the prediction of the BCR, with AUC values ranging from 0.841 to 0.877 for combined models and sensitivity values above 0.960) and when models were built per prostate region vs. the whole gland.ConclusionsProstate region-aware imaging profiles enable identification of patients with worse prognosis and with a higher risk of BCR, retaining higher predictive values when combined with clinical variables.
| S-EPMC10453281 | biostudies-literature
Project description:Background: D'Amico high-risk prostate cancer (Pca) patients experience poor and heterogeneous oncological outcomes. This heterogeneity highlights a need to extensively explore factors associated with poor outcomes to guide decision-making. Objective: To assess predictors of biochemical recurrence (BCR)-free survival in high-risk patients following radical prostatectomy (RP), and subsequently establish a model predicting outcomes. Methods: We retrospectively identified D'Amico high-risk non-metastatic Pca patients who underwent RP between 2013 and 2019 in our hospital. We collected data including PSA level, clinical stage, biopsy Gleason score (GS), number of D'Amico high-risk factors (RF), the inflammatory status (Neutrophil-to-lymphocyte ratio [NLR], derived NLR [dNLR], platelet-to-lymphocyte ratio [PLR] and LDH). Kaplan–Meier methods were used to analyze BCR-free survival. Univariate and multivariate analyses were performed using Cox proportional hazards model to evaluate the association between clinicopathological parameters and BCR-free survival. Results: The median follow-up time for the 101 patients' cohort was 26 months (range: 3–81 months). The number of RF (1RF vs. ?2RF), biopsy GS (<8 vs. ?8), clinical stage (?cT2c vs. >cT2c), pathological stage, and the presence of adverse pathological features were significant predictors of BCR (P < 0.05). Other parameters including inflammatory status (dNLR, NLR, PLR, and LDH) were not of predictive value. On multivariable analysis, biopsy GS (<8 vs. ?8; HR 2.439) and clinical stage (?cT2c vs. >cT2c; HR 3.271) were the independent predictors of BCR. Based on these two independent predictors, patients were stratified into three risk subgroups: favorable (0 risk factor; 47% of patients), intermediate (1 risk factor; 42 %), unfavorable (2 risk factors; 11%). The intermediate and unfavorable subgroups have a significantly shorter median BCR-free survival compared to the favorable subgroup (P < 0.001). Conclusion: Several factors are associated with BCR. Clinical stage (?cT2c vs. >cT2c) and biopsy GS (<8 vs. ?8) are the independent predictors of BCR. The stratification of high-risk patients into risk subgroups based on these two predictors shows that the intermediate and unfavorable subgroups have a significantly shorter median BCR-free survival compared to the favorable subgroup. The preoperative stratification model may help urologists and patients during decision-making. In non-metastatic high-risk patients, preoperative inflammatory markers (NLR, dNLR, PLR, and LDH) are not of prognostic value.
| S-EPMC7511762 | biostudies-literature
Project description:BackgroundThis study evaluated the predictive value of gene signatures for biochemical recurrence (BCR) in primary prostate cancer (PCa) patients.MethodsClinical features and gene expression profiles of PCa patients were attained from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets, which were further classified into a training set (n = 419), a validation set (n = 403). The least absolute shrinkage and selection operator Cox (LASSO-Cox) method was used to select discriminative gene signatures in training set for biochemical recurrence-free survival (BCRFS). Selected gene signatures established a risk score system. Univariate and multivariate analyses of prognostic factors about BCRFS were performed using the Cox proportional hazards regression models. A nomogram based on multivariate analysis was plotted to facilitate clinical application. Kyoto Encyclopedia of Gene and Genomes (KEGG) and Gene Ontology (GO) analyses were then executed for differentially expressed genes (DEGs).ResultsNotably, the risk score could significantly identify BCRFS by time-dependent receiver operating characteristic (t-ROC) curves in the training set (3-year area under the curve (AUC) = 0.820, 5-year AUC = 0.809) and the validation set (3-year AUC = 0.723, 5-year AUC = 0.733).ConclusionsClinically, the nomogram model, which incorporates Gleason score and the risk score, could effectively predict BCRFS and potentially be utilized as a useful tool for the screening of BCRFS in PCa.
| S-EPMC8446568 | biostudies-literature
Project description:Prostate cancer (PCa) is one of the most frequently diagnosed cancers in males worldwide. Approximately 25% of all patients experience biochemical recurrence (BCR) after radical prostatectomy (RP) and BCR indicates increased risk for metastasis and castration resistance. PCa patients with highly glycolytic tumors have a worse prognosis. Thus, this study aimed to explore glycolysis-based predictive biomarkers for BCR. Expression data and clinical information of PCa samples were retrieved from three publicly available datasets. One from The Cancer Genome Atlas (TCGA) dataset was used as the training cohort, and two from the Gene Expression Omnibus (GEO) dataset (GSE54460 and GSE70769) were used as validation cohorts. Using the training cohort, univariate Cox regression survival analysis, robust likelihood-based survival model, and stepwise multiply Cox analysis were sequentially applied to explore predictive glycolysis-related candidates. A five-gene risk score was then constructed based on the Cox coefficient as the following: (-0.8367*GYS2) + (0.3448*STMN1) + (0.3595*PPFIA4) + (-0.1940*KDELR3) + (0.4779*ABCB6). Receiver operating characteristic curve (ROC) analysis was used to identify the optimal cut-off point, and patients were divided into low risk and high risk groups. Kaplan-Meier analysis revealed that high risk group had significantly shorter BCR free survival time as compared with that in low risk group in training and validation cohorts. In conclusion, our data support the glycolysis-based five-gene signature as a novel and robust signature for predicting BCR of PCa patients.
| S-EPMC8092437 | biostudies-literature
Project description:Prostate cancer (PCa) is one of the malignant tumors of urinary system with a high morbidity. Enhancer RNA is a subclass of long non-coding RNA transcribed from active enhancer regions, which plays a critical role in gene transcriptional regulation. However, the role of enhancer RNA (eRNA) in PCa remains extremely mysterious. This study is aimed at exploring key prognostic eRNAs in PCa. First, we downloaded gene expression data and clinical data of 33 cancer types from UCSC Xena platform. Second, we selected reported putative eRNA-target pairs and performed the Kaplan-Meier survival and correlation analysis to determine the crucial eRNAs most related to biochemical recurrence (BCR)-free survival. Third, we explored the clinical characteristics with the key eRNA GAS1 adjacent regulatory RNA (GAS1RR) and performed a computational difference algorithm and the Cox regression analysis. Next, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to explore the underlying mechanisms. Finally, we used the pan-cancer data from The Cancer Genome Atlas (TCGA) and performed reverse transcription-quantitative polymerase chain reaction (RT-qPCR) of 18 pairs of specimens to prove the results we acquired. Among all 2695 putative eRNAs, 6 pairs of eRNA-target genes were prominently related to BCR-free survival. Growth arrest-specific protein 1 (GAS1) was a target gene of GAS1RR (r = 0.86, P < 0.001). Patients with low GAS1RR expression were likely to have unfavorable clinical characteristics. The result of computational Cox regression analysis demonstrated that GAS1RR may predict the prognosis of PCa independently. RT-qPCR results illuminated that GAS1RR and GAS1 were both downregulated in PCa tissues, and they show a strong positive correlation. GO and KEGG analyses revealed biological processes that GAS1RR was mainly associated with. Immune infiltration analysis indicated that GAS1RR expression is correlated with the infiltration level of six kinds of immune cells. Our results suggest that GAS1RR may be clinically useful in the prediction of PCa prognosis. Moreover, it may also be a prognostic predictor and theoretic target with great promise in PCa.
| S-EPMC9989148 | biostudies-literature
Project description:NR6A1/CT150, as an orphan receptor, is a novel member of the cancer-testis (CT) antigen family. Here, we investigated the expression and function of NR6A1 and its underlying mechanisms in prostate cancer (PCa) patients who underwent radical prostatectomy. A total of 303 cases of prostate cancer after radical prostatectomy were analysed in a tissue microarray (TMA) for NR6A1 immunohistochemistry-based protein expression. Kaplan-Meier/log-rank analysis and Cox regression analysis were used to investigate the relationship between NR6A1 expression and clinicopathological factors in PCa. NR6A1 mRNA expression was examined by reversing transcriptase-polymerase chain reaction (RT-PCR). Knockdown of NR6A1 by small interfering RNA mediated gene silencing and overexpression of NR6A1 through lentivirus were utilized to investigate its potential role in prostate cancer cells. NR6A1 protein expression was 29.7% (90/303) and mRNA expression was 28.1%(9/32) in PCa patients. NR6A1 expression was significantly associated with Gleason score (GS) (P=0.003) and tumor stage (P=0.042). The patients with positive NR6A1 expression have a shorter biochemical recurrence-free survival. NR6A1 predicted biochemical recurrence in univariate (P=0.0159) and multivariate models (P=0.0317). In addition, gene silencing of NR6A1 resulted in G0/G1 phase cell cycle arrest, and decreased metastatic and invasive potential of prostate cancer cells DU145 and PC3. In contrast, overexpression of NR6A1 reduced G0/G1 phase cell cycle arrest, and promoted metastatic and invasive potential of prostate cancer cells 22RV1. And overexpression of NR6A1 significantly promoted tumor growth in vivo. What's more, down regulation of NR6A1 could reverse epithelial-to-mesenchymal transition (EMT) process in DU145 and PC3 cell lines, and the overexpression could enhance EMT process in 22RV1 cell line. NR6A1 played a prominent role in migration and invasion of PCa cells, and it is indicated that NR6A1 may act as a novel marker for biochemical recurrence after radical prostatectomy.
| S-EPMC5610014 | biostudies-literature
Project description:BackgroundBiochemical recurrence (BCR) after initial treatment, such as radical prostatectomy, is the most frequently adopted prognostic factor for patients who suffer from prostate cancer (PCa). In this study, we aimed to construct a prognostic model consisting of gene expression profiles to predict BCR-free survival.MethodsWe analyzed 70 metabolic pathways in 152 normal prostate samples and 494 PCa samples from the UCSC Xena dataset (training set) via gene set enrichment analysis (GSEA) to select BCR-related genes and constructed a BCR-related gene risk score (RS) model. We tested the power of our model using Kaplan-Meier (K-M) plots and receiver operator characteristic (ROC) curves. We performed univariate and multivariate analyses of RS using other clinicopathological features and established a nomogram model, which has stronger prediction ability. We used GSE70770 and DFKZ 2018 datasets to validate the results. Finally, we performed differential expression and quantitative real-time polymerase chain reaction analyses of the UCSC data for further verification of the findings.ResultsA total of 194 core enriched genes were obtained through GSEA, among which 16 BCR-related genes were selected and a three-gene RS model based on the expression levels of CA14, LRAT, and MGAT5B was constructed. The outcomes of the K-M plots and ROC curves verified the accuracy of the RS model. We identified the Gleason score, pathologic T stage, and RS model as independent predictors through univariate and multivariate Cox analyses and constructed a nomogram model that presented better predictability than the RS model. The outcomes of the validation set were consistent with those of the training set. Finally, the results of differential expression analyses support the effectiveness of our model.ConclusionWe constructed an RS model based on metabolic genes that could predict the prognosis of PCa patients. The model can be easily used in clinical applications and provide important insights into future research on the underlying mechanism of PCa.
| S-EPMC8896158 | biostudies-literature
Project description:BackgroundTo clarify the involvement of HIVEP3 and SOX9 coexpression in prostate cancer (PCa).MethodsA small interfering RNA was used to knockdown SOX9 expression in a PCa cell line and to analyze the effects of SOX9 inhibition on the expression of HIVEP3 in vitro. Then, HIVEP3 and SOX9 expression patterns in the human PCa tissues were detected using quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis and immunohistochemistry.ResultsWe found that the downregulation of SOX9 could inhibit the expression of HIVEP3 in the PCa cells in vitro. In addition, both HIVEP3 and SOX9 messenger RNA expression levels in the PCa tissues were significantly higher than those in the noncancerous prostate tissues (P=0.006 and P<0.001, respectively). Moreover, the immunohistochemical staining scores of HIVEP3 in the PCa tissues with PSA failure were significantly higher than those without (P=0.042); the increased SOX9 protein expression was more frequently found in the PCa tissues with a high Gleason score (P=0.045) and a high clinical stage (P=0.012). The tumors showing the HIVEP3-high/SOX9-high expression more frequently had PSA failure (P=0.024). When the patients with an HIVEP3 overexpression combined with the SOX9 overexpression, this group had a worse biochemical recurrence-free survival (P<0.001). Furthermore, the multivariate analysis showed that the HIVEP3/SOX9 coexpression was an independent predictor of an unfavorable biochemical recurrence-free survival.ConclusionOur data offer the convincing evidence for the first time that a combined analysis of HIVEP3 and SOX9 may help to predict the tumor progression and prognosis of PCa patients. In particular, the overexpression of HIVEP3 in PCa might partly explain the poor prognosis of patients with an upregulation of SOX9.
| S-EPMC3908830 | biostudies-literature