ProstaTrend—A Multivariable Prognostic RNA Expression Score for Aggressive Prostate Cancer

Kreuz, Markus; Otto, Dominik J.; Fuessel, Susanne; Blumert, Conny; Bertram, Catharina; Bartsch, Sophie; Loeffler, Dennis; Puppel, Sven-Holger; Rade, Michael; Buschmann, Tilo; Christ, Sabina; Erdmann, Kati; Friedrich, M.; Froehner, Michael; Muders, Michael H.; Schreiber, S; Specht, Michael; Toma, Marieta; Benigni, Fabio; Freschi, Massimo; Gandaglia, Giorgio; Briganti, Alberto; Baretton, Gustavo; Loeffler, Markus; Hackermüller, Jörg; Reiche, Kristin; Wirth, Manfred P.; Horn, Friedemann

doi:10.1016/j.eururo.2020.06.001

Cited by 17 publications

(25 citation statements)

References 24 publications

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“…It could heavily threaten patients' quality of life and even lifespan when it comes to BCR because patients with BCR have higher chances of developing metastatic PCa. Thus, risk stratification of patients via PSA, GS, and pathological stage, etc., becomes significant for prognosis prediction ( Kreuz et al, 2020 ). However, with a deeper understanding of PCa, they gradually fail to provide more precise prediction.…”

Section: Discussionmentioning

confidence: 99%

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

Wang

Zhong

Long

et al. 2021

Front. Mol. Biosci.

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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, MAFG-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.

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Section: Discussionmentioning

confidence: 99%

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

Wang

Zhong

Long

et al. 2021

Front. Mol. Biosci.

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“…Until now, several clinical and laboratory variables have been identified for the classification of PCa, including preoperative prostate-specific antigen (PSA) levels, Gleason score, and tumor stage [ 2 – 4 ]. However, it is well known that these methods are imperfect and limited because some patients within a given risk group have variable long-term outcomes [ 5 ]. Thus, additional biological markers that provide an objective evaluation of tumor biology are urgently needed to improve risk stratification for patients with PCa.…”

Section: Introductionmentioning

confidence: 99%

CircSCAF8 promotes growth and metastasis of prostate cancer through the circSCAF8-miR-140-3p/miR-335-LIF pathway

Wen

Zhang

et al. 2022

Cell Death Dis

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Circular RNAs (circRNAs) have been increasingly linked to cancer progression. However, the detailed biological functions of circRNAs in prostate cancer (PCa) remain unclear. Using high-throughput circRNA sequencing, we previously identified 18 urine extracellular vesicle circRNAs that were increased in patients with PCa compared with those with benign prostatic hyperplasia. Spearman correlation analysis of the expression levels of the 18 circRNAs between the tumor tissue and matched urine extracellular vesicles in 30 PCa patients showed that circSCAF8 had the highest R2 (R2 = 0.635, P < 0.001). The Cox proportional hazards regression model was used to estimate the effect of circSCAF8 on progression-free survival. The in vitro and in vivo functional experiments were implemented to investigate the effects of circSCAF8 on the phenotype of PCa. We found that the knockdown of circSCAF8 in PCa cells suppressed the proliferation, migration, and invasion ability, while overexpression of circSCAF8 had the opposite effects. Similar results were observed in vivo. In a cohort of 85 patients who had undergone radical prostatectomy, circSCAF8 expression in PCa tissues was a powerful predictor of progression-free survival (HR = 2.14, P = 0.022). Mechanistically, circSCAF8 can function by binding to both miR-140-3p and miR-335 to regulate LIF expression and activate the LIF-STAT3 pathway that leads to the growth and metastasis of PCa. Collectively, our findings demonstrate that circSCAF8 contributes to PCa progression through the circSCAF8-miR-140-3p/miR-335-LIF pathway.

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“…Nonetheless, up to 50% patients will experience biochemical recurrence (BCR) after the operation (Freedland et al, 2005;Moris et al, 2020). Research has shown that the prognosis of prostate cancer depends on many factors, such as age, positive margin, pathological stage, Gleason score, PSA, and so on (Kreuz et al, 2020). Due to the heterogeneity of prostate cancer, the existing prognosis judgment system currently fails to meet the needs of every patient.…”

Section: Introductionmentioning

confidence: 99%

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

Wang

Zhong

et al. 2020

Front. Cell Dev. Biol.

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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.

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ProstaTrend—A Multivariable Prognostic RNA Expression Score for Aggressive Prostate Cancer

Cited by 17 publications

References 24 publications

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

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

CircSCAF8 promotes growth and metastasis of prostate cancer through the circSCAF8-miR-140-3p/miR-335-LIF pathway

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

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