Risk factor analysis and nomogram construction in patients with distant metastatic prostate cancer at different PSA levels: a study based on the SEER database.

OBJECTIVE: Prostate cancer (PCa) is the most common malignant tumor in the male genitourinary system. Once PCa has metastasized, it is very difficult to cure. The purpose of this study was to investigate the prognostic risk factor analysis of patients with different prostate-specific antigen (PSA) levels in distant metastatic PCa. At the same time, we construct effective models for predicting the survival rate of prostate cancer patients. PATIENTS AND METHODS: Data on prostate cancer patients with the presence of distant metastases were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. PCa patients with distant metastases were categorized into two groups based on PSA levels, one with PSA <20 ng/mL and the other with PSA ≥20 ng/mL. Univariate and multivariate COX regression analyses were used to identify independent factors affecting the prognosis of the patients. A nomogram was constructed using the independent prognostic factors, and the results were evaluated using calibration curves, timeROC curves, and Kaplan-Meier curves. RESULTS: In the PSA <20 ng/mL group, there were a total of 1,832 patients. COX regression analysis showed that age, marital status, N stage, grade, Gleason score, and medical household income inflation were independent prognostic factors for overall survival (OS) in patients. In addition, we found that age, marital status, N stage, bone metastasis, grade, and Gleason score were independent prognostic factors for cancer-specific survival (CSS) in patients. In the PSA ≥20 ng/mL group, there were a total of 5,314 patients. It was found that age, ethnicity, marital status, bone metastasis, first malignant primary indicator, grade, Gleason score, and medical household income inflation were patients' independent prognostic factors for OS. For CSS, we found that age, ethnicity, marital status, T stage, radiotherapy, bone metastasis, Gleason score, and Median household income inflation were independent prognostic factors. Constructing a nomogram can accurately predict the prognosis of this group of patients. CONCLUSIONS: We found different independent prognostic factors for different PSA levels in patients with distant metastatic PCa. A new nomogram was constructed to predict OS and CSS in patients, which helps in clinical-assisted decision-making.

A comprehensive analysis of essential meiotic endonuclease 1 to prognosis and immune infiltration in kidney renal clear cell carcinoma.

OBJECTIVE: Clear cell renal cell carcinoma (ccRCC) is the most common type of cancer, and its molecular pathogenesis is unclear. In this study, we investigated the prognostic value of essential meiotic endonuclease 1 (EME1) in kidney renal clear cell carcinoma (KIRC). MATERIALS AND METHODS: We downloaded the RNA-Seq expression of 526 KIRC tissues and 72 normal tissues from the TCGA database and the corresponding clinical data. The gene expression profiles associated with four clear cell renal cell carcinomas were downloaded from the GEO database for analysis. The expression of EME1 in clear renal cell carcinoma and its correlation with the clinical baseline data were analyzed. Kaplan-Meier survival curve analysis was performed to assess the relationship between EME1 and patient survival. Enrichment analysis was performed to elucidate the possible functions of EME1. We also analyzed the relationship between the EME1 expression and immune infiltration through TIMER2.0 and TISIDB online databases as well as the relationship between EME1 and common immune checkpoints. RESULTS: EME1 was identified as a risk factor for overall survival in clear cell renal cell carcinoma with a hazard ratio of 3.201 (95% confidence interval: 2.430-4.215; p < 0.001). EME1 was highly expressed in KIRC compared to that in normal tissues (p < 0.001) and in the worse TNM stages and late stages (stage 3/4) (p < 0.001). High EME1 expression was strongly associated with the advanced T stage (p = 0.003), advanced N stage (p = 0.002), and advanced M stage (p = 0.006). Research data on KIRC were simultaneously collected and analyzed from the GEO database, including GSE40435, GSE53000, GSE68417, and GSE53757. EME1 predicted the survival status in KIRC patients (AUC = 0.62). We further established a nomogram including the correlation between the high and low EME1 expression, and EME1 was found to contribute to the prediction of the probability of patient survival with a c-index = 0.796. Kaplan-Meier analysis revealed a lower likelihood of survival with a high EME1 expression (p < 0.001). In addition, further bioinformatics analysis suggested that EME1 may be associated with the extent of immune infiltration in KIRC. CONCLUSIONS: An increased expression of EME1 in KIRC is thus associated with advanced clinicopathological features, possibly acting as a potential biomarker of poor prognosis in KIRC.