Dataset Information

A Novel Predictor Tool of Biochemical Recurrence after Radical Prostatectomy Based on a Five-MicroRNA Tissue Signature.

ABSTRACT: Within five to ten years after radical prostatectomy (RP), approximately 15-34% of prostate cancer (PCa) patients experience biochemical recurrence (BCR), which is defined as recurrence of serum levels of prostate-specific antigen >0.2 µg/L, indicating probable cancer recurrence. Models using clinicopathological variables for predicting this risk for patients lack accuracy. There is hope that new molecular biomarkers, like microRNAs (miRNAs), could be potential candidates to improve risk prediction. Therefore, we evaluated the BCR prognostic capability of 20 miRNAs, which were selected by a systematic literature review. MiRNA expressions were measured in formalin-fixed, paraffin-embedded (FFPE) tissue RP samples of 206 PCa patients by RT-qPCR. Univariate and multivariate Cox regression analyses were performed, to assess the independent prognostic potential of miRNAs. Internal validation was performed, using bootstrapping and the split-sample method. Five miRNAs (miR-30c-5p/31-5p/141-3p/148a-3p/miR-221-3p) were finally validated as independent prognostic biomarkers. Their prognostic ability and accuracy were evaluated using C-statistics of the obtained prognostic indices in the Cox regression, time-dependent receiver-operating characteristics, and decision curve analyses. Models of miRNAs, combined with relevant clinicopathological factors, were built. The five-miRNA-panel outperformed clinically established BCR scoring systems, while their combination significantly improved predictive power, based on clinicopathological factors alone. We conclude that this miRNA-based-predictor panel will be worth to be including in future studies.

SUBMITTER: Zhao Z

PROVIDER: S-EPMC6826532 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Novel Predictor Tool of Biochemical Recurrence after Radical Prostatectomy Based on a Five-MicroRNA Tissue Signature.

Zhao Zhongwei Z Weickmann Sabine S Jung Monika M Lein Michael M Kilic Ergin E Stephan Carsten C Erbersdobler Andreas A Fendler Annika A Jung Klaus K

Cancers 20191021 10

Within five to ten years after radical prostatectomy (RP), approximately 15-34% of prostate cancer (PCa) patients experience biochemical recurrence (BCR), which is defined as recurrence of serum levels of prostate-specific antigen >0.2 µg/L, indicating probable cancer recurrence. Models using clinicopathological variables for predicting this risk for patients lack accuracy. There is hope that new molecular biomarkers, like microRNAs (miRNAs), could be potential candidates to improve risk predict ...[more]

PMID: 31640261

Similar Datasets

Project description:The objective of this study was to utilize a microarray platform to determine the microRNA (miRNA) expression profile in prostate cancer tissue from patients who underwent radical prostatectomy and were followed for an average of 47 months. The GeneChip® miRNA Array (Affymetrix) contains more than 46,000 probes, and more than 1,100 mature human miRNAs and transcripts. An expression level higher or lower than 1.1 with a p<0.05 were considered to be differentially expressed. When tumors with a GS<7 were compared with those with a GS≥7, five miRNAs were down-regulated and nine were up-regulated. In comparing tumors from patients with PSA <10 ng/mL vs. those with PSA ≥10 ng/mL, 21 miRNAs were down-regulated and 29 were overexpressed. There was decreased expression of 21 miRNAs and increased expression of 22 miRNAs when pT2 and pT3 tumors were compared. The comparison of the expression profiles of men with vs. without recurrent disease (PSA>0.2 ng/mL) revealed that 14 miRNAs were down-regulated and 17 were up-regulated. Considering the three prognostic factors and biochemical recurrence, miR-335 was overexpressed in pT3 tumors in patients with PSA>10 ng/mL, miR-1202 was overexpressed in recurrent tumors in which PSA >10 ng/mL, and miR-885 and miR-1226 were overexpressed in recurrent pT3 tumors. Six miRNAs (miR- 361, 378, 548, 574, 652 and 892) had decreased expression in pT3 tumors in patients with PSA >10 ng/mL. miR-16 was down-regulated in recurrent pT3 tumors. miR-92 and miR-450 exhibited decreased expression in recurrent tumors in patients with PSA > 10 ng/mL. miR-28 was down-regulated in pT3 adenocarcinomas with a GS ≥ 7. The differentially expressed miRNAs in recurrent tumors were validated using qRT-PCR in 74 additional specimens. miR-21 was overexpressed in recurrent tumors, and in the Cox model, expression levels higher than 0.64 were indicative of biochemical recurrence with a risk of 2.4. These results, which were based on clinical specimens from patients treated in a standardized way and followed for an average of 47 months, provide an initial understanding of the role of miRNAs in prostatecancer progression; the foremost representative is miR-21, which has been implicated in the progression of various human cancers.

Project description:The objective of this study was to utilize a microarray platform to determine the microRNA (miRNA) expression profile in prostate cancer tissue from patients who underwent radical prostatectomy and were followed for an average of 47 months. The GeneChipM-BM-. miRNA Array (Affymetrix) contains more than 46,000 probes, and more than 1,100 mature human miRNAs and transcripts. An expression level higher or lower than 1.1 with a p<0.05 were considered to be differentially expressed. When tumors with a GS<7 were compared with those with a GSM-bM-^IM-%7, five miRNAs were down-regulated and nine were up-regulated. In comparing tumors from patients with PSA <10 ng/mL vs. those with PSA M-bM-^IM-%10 ng/mL, 21 miRNAs were down-regulated and 29 were overexpressed. There was decreased expression of 21 miRNAs and increased expression of 22 miRNAs when pT2 and pT3 tumors were compared. The comparison of the expression profiles of men with vs. without recurrent disease (PSA>0.2 ng/mL) revealed that 14 miRNAs were down-regulated and 17 were up-regulated. Considering the three prognostic factors and biochemical recurrence, miR-335 was overexpressed in pT3 tumors in patients with PSA>10 ng/mL, miR-1202 was overexpressed in recurrent tumors in which PSA >10 ng/mL, and miR-885 and miR-1226 were overexpressed in recurrent pT3 tumors. Six miRNAs (miR- 361, 378, 548, 574, 652 and 892) had decreased expression in pT3 tumors in patients with PSA >10 ng/mL. miR-16 was down-regulated in recurrent pT3 tumors. miR-92 and miR-450 exhibited decreased expression in recurrent tumors in patients with PSA > 10 ng/mL. miR-28 was down-regulated in pT3 adenocarcinomas with a GS M-bM-^IM-% 7. The differentially expressed miRNAs in recurrent tumors were validated using qRT-PCR in 74 additional specimens. miR-21 was overexpressed in recurrent tumors, and in the Cox model, expression levels higher than 0.64 were indicative of biochemical recurrence with a risk of 2.4. These results, which were based on clinical specimens from patients treated in a standardized way and followed for an average of 47 months, provide an initial understanding of the role of miRNAs in prostatecancer progression; the foremost representative is miR-21, which has been implicated in the progression of various human cancers. Fifty-three patients underwent a radical prostatectomy performed by the same surgeon (MS) to treat localized PC between August 2000 and June 2002. The mean age was 65 years (SD: 7.5, range: 49 - 77). The mean Gleason score was 7 (SD: 1.1, range: 5 - 10); 15 tumors had a score of 5 or 6, and 38 had a score between 7 and 10. Twenty-four (45.3%) of the patients had pT2 tumors, and 29 (54.7%) had pT3 tumors. The control group consisted of three patients with lower urinary tract symptoms, a mean age of 55.3 years and a diagnosis of benign prostatic hyperplasia (BPH) who consented to open surgery.

Project description:The time and speed of biochemical recurrence (BCR) of prostate cancer (PCa) after radical prostatectomy (RP) is highly variable. Stratification methods based on TNM staging and Gleason score (GS) do not allow the identification of patients at risk of BCR following RP. Therefore, the aim of the present study was to identify molecular signatures that can predict BCR risk effectively and facilitate treatment-related decisions for patients with PCa. RNA sequencing data and corresponding clinical data were downloaded from The Cancer Genome Atlas (TCGA) and Oncomine databases. Bioinformatics analysis was performed to identify differentially expressed genes in patients with GS=6 and GS ?7. Cox regression models were used to determine the PCa signature (PCasig) and a clinical nomogram for the prediction of BCR. The performance of nomograms was assessed using time-dependent receiver operating characteristic curves and the concordance index (C-index). A PCasig comprising 10 genes, including SEMG2, KCNJ16, TFAP2B, SYCE1, KCNU1, AFP, GUCY1B2, GRIA4, NXPH1 and SOX11, was significantly associated with BCR, which was identified in TCGA cohort [hazard ratio (HR), 5.18; 95% CI, 3.241-8.272; C-index, 0.777] and validated in the Oncomine cohort (HR, 2.78; 95% CI, 1.39-5.54; C-index, 0.66). The expression levels of SEMG2, KCNJ16 and TFAP2B were downregulated in patients with GS ?7. The expression levels of SYCE1, KCNU1, AFP, GUCY1B2, GRIA4, NXPH1 and SOX11 were upregulated in patients with GS ?7. The clinical nomogram was constructed based on the GS and pathologic T stage (HR, 4.15; 95% CI, 1.39-5.54; C-index, 0.713). The addition of the PCasig to the clinical nomogram significantly improved prognostic value (HR, 7.25; 95% CI, 4.54-11.56; C-index, 0.782) with an net reclassification improvement of 75.3% (95% CI, 46.8-104.6%). Furthermore, the endogenous expression of each gene in the PCasig was measured in five PCa cell lines and in normal prostate cells, and these genes exhibited different expression levels relative to one another. In conclusion, an PCasig was identified by mining TCGA and successfully validated in an Oncomine cohort. This PCasig was an independent prognostic factor with a greater prognostic value for all patients regardless of GS than traditional clinical variables, which can improve the performance of clinical nomograms in predicting BCR of patients with GS ?7.

Project description:Background: Nowadays, predictions of biochemical recurrence (BCR) in localized prostate cancer (PCa) patients after radical prostatectomy (RP) are mainly based on clinical parameters with a low predictive accuracy. Given the critical role of apoptosis in PCa occurrence and progression, we aimed to establish a novel predictive model based on apoptosis-related gene signature and clinicopathological parameters that can improve risk stratification for BCR and assist in clinical decision-making. Methods: Expression data and corresponding clinical information were obtained from four public cohorts, one from The Cancer Genome Atlas (TCGA) dataset and three from the Gene Expression Omnibus (GEO) dataset. Weighted gene co-expression network analysis (WGCNA) was performed to identify candidate modules closely correlated to BCR, and univariate and multivariate Cox regression analyses were utilized to build the gene signature. Time-dependent receiver operating curve (ROC) and Kaplan-Meier (KM) survival analysis were used to assess the prognostic value. Finally, we analyzed the expression of genes in the signature and validated the results using quantitative real-time PCR (qRT-PCR). Results: The novel gene signature we established exhibited a high prognostic value and was able to act as an independent risk factor for BCR [Training set: P < 0.001, hazard ratio (HR) = 7.826; Validation set I: P = 0.006, HR = 2.655; Validation set II: P = 0.003, HR = 4.175; Validation set III: P < 0.001, HR = 3.008]. Nomogram based on the gene signature and clinical parameters was capable of distinguishing high-risk BCR patients. Additionally, functional enrichment analysis showed several enriched pathways and biological processes, which might help reveal the underlying mechanism. The expression results of qRT-PCR were consistent with TCGA results. Conclusion: The apoptosis-related gene signature could serve as a powerful predictor and risk factor for BCR in localized PCa patients after RP.

Project description:Accurate estimation of recurrence risk is needed for optimal treatment of clinically localized prostate cancer (PCa) patients. We combined classical clinicopathological predictors of biochemical recurrence (BCR) and molecular markers into a new risk score for predicting BCR after radical prostatectomy (RP). A retrospective study which included 122 PCa patients who attended our department between 2000 and 2007 was conducted. Total RNA was isolated from formalin-fixed paraffin embedded PCa tissue. Gene expression patterns were analyzed in 21 selected samples from 7 localized, 6 locally advanced, and 8 metastatic PCa patients using Illumina microarrays. Expression levels of 41 genes were validated by quantitative PCR in an independent retrospective series of 101 patients with ≥ 10 years follow-up who underwent RP for clinically localized PCa. Univariate and multivariate logistic regression analysis were used to identify individual predictors of BCR. A risk score (RS) for predicting BCR including clinicopathological and gene expression data was developed and Kaplan-Meier curves were generated. Interaction networks between the genes of the model were built by GeneMANIA Cytoscape plugin. In a median follow-up of 120 months (range 3-190), 37 patients developed BCR (36.6%). Expression levels of 7,930 transcripts differed between clinically localized and locally advanced-metastatic PCa groups (FDR<0.1). A set of 41 genes were validated by quantitative PCR. Regression analysis showed that expression of ASF1B and MCL1 as well as Gleason score, extracapsular extension, seminal vesicle invasion and positive margins were independent prognostic factors of BCR. A RS generated using these gene expression and clinicopathological variables was able to discriminate between two groups of patients with a significantly different probability of BCR (HR 6.24; CI 3.23-12.4, p<0.01), improving the individual discriminative performance of each of these variables on their own. Direct interactions between the two genes of the model were not found. In conclusion, identification of new gene expression patterns associated with a high probability of BCR in clinically localized PCa patients treated with RP, and their combination with clinicopathological variables in a robust, easy-to-use and reliable classifier may contribute to improve PCa risk stratification and, consequently, to tailor treatment and surveillance strategies in these patients.

Dataset Information

A Novel Predictor Tool of Biochemical Recurrence after Radical Prostatectomy Based on a Five-MicroRNA Tissue Signature.

Publications

A Novel Predictor Tool of Biochemical Recurrence after Radical Prostatectomy Based on a Five-MicroRNA Tissue Signature.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets