Prostate cancer is a major disease impacting men’s health worldwide. Peplau, who is known as “the mother of psychiatric society,” developed an interpersonal relationship theory for nursing. Implementation of this theory in practice has been shown to positively impact patients’ quality of life and reduce adverse symptoms after surgery.

To investigate the effects of a nursing model based on Peplau’s interpersonal relationship theory combined with bladder function training on patients with prostate cancer.

Eighty-nine patients with prostate cancer who underwent transurethral resection of the prostate (TURP) participated in this study. These patients were admitted to The First Affiliated Hospital of Soochow University or Dushu Lake Hospital Affiliated to Soochow University between January 2020 and April 2021. Patients were randomized into either the Peplau nursing group (n = 44) or a routine nursing group (n = 45). The routine nursing group received routine care and bladder function training, while the Peplau care group received care that integrated concepts from the Peplau interpersonal relationship theory as well as bladder function training. The urinary incontinence symptoms of the two groups were recorded, and the respective International Prostate Symptom Scores (IPSS), Functional Assessment of Chronic Illness Therapy- Spiritual Well-Being (FACIT-Sp) scores, and quality of life (QOL) scores for each group were compared before and after three months of nursing intervention.

During the intervention period, the duration of urinary incontinence, frequency, number and amount of urinary incontinence were significantly greater in the routine nursing group compared to the Peplau care group (P < 0.05). The indicators of the routine nursing group were 7.13 ± 2.42 days, 8.23 ± 2.75 times, and 1.24 ± 0.42 L, while those of the Peplau care group were 4.74 ± 1.85 d, 4.21 ± 1.26 times, and 0.56 ± 0.11 L, respectively. After three months of intervention, the mean IPSS score of the routine nursing group was significantly reduced (P < 0.05), while the mean FACIT-Sp and QOL scores were significantly increased (P < 0.05). The mean IPSS score in the Peplau nursing group was significantly lower compared to the routine nursing group, while the FACIT-Sp and QOL scores were higher (P < 0.05).

A nursing model based on Peplau’s interpersonal relationship theory combined with bladder function training can significantly improve prostate function and urinary symptoms, resulting in the restoration of physiological function and improvement in the QOL of patients with prostate cancer following TURP.

• Peplau interpersonal relationship theory
• Bladder function training
• Prostate cancer
• Quality of life
• Nursing

Background: Prostate cancer (PCa) is an epithelial malignant tumor that occurs in the urinary system with high incidence and is the second most common cancer among men in the world. Thus, it is important to screen out potential key biomarkers for the pathogenesis and prognosis of PCa. The present study aimed to identify potential biomarkers to reveal the underlying molecular mechanisms.

Methods: Differentially expressed genes (DEGs) between PCa tissues and matched normal tissues from The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) dataset were screened out by R software. Weighted gene co-expression network analysis was performed primarily to identify statistically significant genes for clinical manifestations. Protein–protein interaction (PPI) network analysis and network screening were performed based on the STRING database in conjunction with Cytoscape software. Hub genes were then screened out by Cytoscape in conjunction with stepwise algorithm and multivariate Cox regression analysis to construct a risk model. Gene expression in different clinical manifestations and survival analysis correlated with the expression of hub genes were performed. Moreover, the protein expression of hub genes was validated by the Human Protein Atlas database.

Results: A total of 1,621 DEGs (870 downregulated genes and 751 upregulated genes) were identified from the TCGA-PRAD dataset. Eight prognostic genes [BUB1, KIF2C, CCNA2, CDC20, CCNB2, PBK, RRM2, and CDC45] and four hub genes (BUB1, KIF2C, CDC20, and PBK) potentially correlated with the pathogenesis of PCa were identified. A prognostic model with good predictive power for survival was constructed and was validated by the dataset in GSE21032. The survival analysis demonstrated that the expression of RRM2 was statistically significant to the prognosis of PCa, indicating that RRM2 may potentially play an important role in the PCa progression.

Conclusion: The present study implied that RRM2 was associated with prognosis and could be used as a potential therapeutic target for PCa clinical treatment.

• FGFR
• biomarker
• prostate cancer
• survival

Background: The tumor microenvironment (TME) and immune checkpoint inhibitors have been shown to promote active immune responses through different mechanisms. We attempted to identify the important prognostic genes and prognostic characteristics related to TME in prostate cancer (PCa).

Methods: The gene transcriptome profiles and clinical information of PCa patients were obtained from The Cancer Genome Atlas (TCGA) database, and the immune and stromal scores were calculated by the ESTIMATE algorithm. We evaluated the prognostic value of the risk score (RS) model based on univariate Cox analysis and least absolute shrinkage and selection operation (LASSO) Cox regression analysis and established a nomogram to predict disease-free survival (DFS) in PCa patients. The GSE70768 dataset was utilized for external validation. Twenty-two subsets of tumor-infiltrating immune cells were analyzed using the CIBERSORT algorithm.

Results: In this study, the patients with higher immune/stromal scores were associated with a worse DFS, higher Gleason score, and higher pathological T stage. Based on the immune and stromal scores, 515 differentially expressed genes (DEGs) were identified. The univariate Cox and LASSO Cox regression models were employed to select 18 DEGs from 515 DEGs and construct an RS model. The DFS of the high-RS group was significantly lower than that of the low-RS group (P<0.001). The AUCs for the 1-year, 3-year and 5-year DFS rates in the RS model were 0.890, 0.877 and 0.841, respectively. A nomogram of DFS was established based on the RS and Gleason score, and the AUCs for the 1-year, 3-year and 5-year DFS rates in the nomogram were 0.907, 0.893, and 0.872, respectively. These results were further validated in the GSE70768 dataset. In addition, the proportion of Tregs was determined to be higher in high-RS patients (P<0.05), and the expression levels of five immune checkpoints (CTLA-4, PD-1, LAG-3, TIM-3 and TIGIT) were observed to be higher in high-RS patients (P<0.05).

Conclusions: Our study established and validated an 18-gene prognostic signature model associated with TME, which might serve as a prognosis stratification tool to predict DFS in PCa patients after radical prostatectomy.

• immune
• microenvironment
• prediction
• prognosis
• prostate cancer
• radical prostatectomy
• stromal

Prostate cancer is a life-threatening and highly heterogeneous malignancy. In the past decade, circulating tumor cells (CTCs) have been suggested to play a critical role in the occurrence and progression of prostate cancer. In particular, as the “seed” of the cancer metastasis cascade, CTCs determine numerous biological behaviors, such as tumor invasion into adjacent tissues and migration to distant organs. Many studies have shown that CTCs are necessary in the processes of tumor progression, including tumorigenesis, invasion, metastasis, and colonization. Furthermore, CTCs express various biomarkers relevant to prostate cancer and thus can be applied clinically in noninvasive tests. Moreover, CTCs can serve as potential prognostic targets in prostate cancer due to their roles in regulating many processes associated with cancer metastasis. In this review, we discuss the isolation and detection of CTCs as predictive markers of prostate cancer, and we discuss their clinical application in the diagnosis and prognosis of prostate cancer and in monitoring the response to treatment and the prediction of metastasis.

• EMT
• IFN-γ
• Prostate cancer
• circRNAs
• miRNAs

• prostate cancer
• prostate health index
• sensitivity
• specificity

• Area Under Curve
• Biomarkers
• Biomarkers, Tumor
• Biopsy
• Humans
• Male
• Prognosis
• Prostate/metabolism
• Prostate/pathology
• Prostatic Neoplasms/diagnosis
• Prostatic Neoplasms/metabolism
• Publication Bias
• ROC Curve
• Reproducibility of Results
• Severity of Illness Index

• 2015JC3026 Hunan Department of Science and Technology Foundation China