Circulating Forms of Urokinase-Type Plasminogen Activator Receptor in Plasma Can Predict Recurrence and Survival in Patients with Urothelial Carcinoma of the Bladder

suPARnostic: an advanced predictive tool for detecting recurrence in renal cell carcinoma

BACKGROUND

Plasma soluble urokinase-type Plasminogen Activator Receptor (suPAR) predicts disease aggressiveness in renal cell carcinoma (ccRCC), but its prognostic accuracy has not been investigated. To investigate the prognostic accuracy of preoperative plasma suPAR in patients who received curative treatment for initially localized ccRCC.

METHODS

We retrospectively analyzed plasma samples stored in the Danish National Biobank between 2010 and 2015 from 235 patients with ccRCC at any stage. Relationships with outcome analyzed using univariate and multiple logistic Cox regression analysis.

RESULTS

There were 235 patients with ccRCC. The median follow-up period was 7.7 years. In univariate analysis suPAR ≥ 6 ng/mL was significantly associated with overall survival (OS) and recurrence-free survival (RFS). Patients with elevated suPAR were more likely to recur, with a Hazard Ratio (HR) of 2.3 for RFS. In multiple logistic regression, suPAR ≥ 6 ng/mL remained a negative predictor of OS and RFS. Limitations include retrospective study design, wide confidence intervals, and tumor subtype heterogeneity bias.

CONCLUSIONS

ccRCC patients with high plasma suPAR concentrations are at an elevated risk of disease recurrence and see lower OS. suPAR is a promising surveillance tool to more precisely follow up with ccRCC patients and detect future recurrences. In this study, we showed that new type of liquid marker in blood plasma, called suPAR, is associated to a higher risk of kidney cancer recurrence when elevated above 6ng/mL. We also showed suPAR to independently be able to predict patients overall and recurrence free survival in patient with any stage of kidney cancer.

Blood-Based Biomarkers as Prognostic Factors of Recurrent Disease after Radical Cystectomy: A Systematic Review and Meta-Analysis

Survival outcomes after radical cystectomy (RC) for bladder cancer (BCa) have not improved in recent decades; nevertheless, RC remains the standard treatment for patients with localized muscle-invasive BCa. Identification of the patients most likely to benefit from RC only versus a combination with systemic therapy versus systemic therapy first/only and bladder-sparing is needed. This systematic review and meta-analysis pools the data from published studies on blood-based biomarkers to help prognosticate disease recurrence after RC. A literature search on PubMed and Scopus was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. Articles published before November 2022 were screened for eligibility. A meta-analysis was performed on studies investigating the association of the neutrophil-to-lymphocyte ratio (NLR), the only biomarker with sufficient data, with recurrence-free survival. The systematic review identified 33 studies, and 7 articles were included in the meta-analysis. Our results demonstrated a statistically significant correlation between elevated NLR and an increased risk of disease recurrence (HR 1.26; 95% CI 1.09, 1.45; p = 0.002) after RC. The systematic review identified various other inflammatory biomarkers, such as interleukin-6 or the albumin-to-globulin ratio, which have been reported to have a prognostic impact on recurrence after RC. Besides that, the nutritional status, factors of angiogenesis and circulating tumor cells, and DNA seem to be promising tools for the prognostication of recurrence after RC. Due to the high heterogeneity between the studies and the different cut-off values of biomarkers, prospective and validation trials with larger sample sizes and standardized cut-off values should be conducted to strengthen the approach in using biomarkers as a tool for risk stratification in clinical decision-making for patients with localized muscle-invasive BCa.

Optimal Systemic Treatment of Advanced Bladder Cancer Calls for a Multidisciplinary Approach

Although the bladder cancer treatment field is expanding with several new treatments introduced in the last decade, many patients with an advanced form of the disease can expect a poor prognosis when diagnosed [...].

Identification of Immune-Related Genes Associated With Bladder Cancer Based on Immunological Characteristics and Their Correlation With the Prognosis

Background:To identify the immune-related genes of bladder cancer (BLCA) based on immunological characteristics and explore their correlation with the prognosis. Methods:We downloaded the gene and clinical data of BLCA from the Cancer Genome Atlas (TCGA) as the training group, and obtained immune-related genes from the Immport database. We downloaded GSE31684 and GSE39281 from the Gene Expression Omnibus (GEO) as the external validation group. R (version 4.0.5) and Perl were used to analyze all data. Result:Univariate Cox regression analysis and Lasso regression analysis revealed that 9 prognosis-related immunity genes (PIMGs) of differentially expressed immune genes (DEIGs) were significantly associated with the survival of BLCA patients (p < 0.01), of which 5 genes, including NPR2, PDGFRA, VIM, RBP1, RBP1 and TNC, increased the risk of the prognosis, while the rest, including CD3D, GNLY, LCK, and ZAP70, decreased the risk of the prognosis. Then, we used these genes to establish a prognostic model. We drew receiver operator characteristic (ROC) curves in the training group, and estimated the area under the curve (AUC) of 1-, 3- and 5-year survival for this model, which were 0.688, 0.719, and 0.706, respectively. The accuracy of the prognostic model was verified by the calibration chart. Combining clinical factors, we established a nomogram. The ROC curve in the external validation group showed that the nomogram had a good predictive ability for the survival rate, with a high accuracy, and the AUC values of 1-, 3-, and 5-year survival were 0.744, 0.770, and 0.782, respectively. The calibration chart indicated that the nomogram performed similarly with the ideal model. Conclusion:We had identified nine genes, including PDGFRA, VIM, RBP1, RBP1, TNC, CD3D, GNLY, LCK, and ZAP70, which played important roles in the occurrence and development of BLCA. The prognostic model based on these genes had good accuracy in predicting the OS of patients and might be promising candidates of therapeutic targets. This study may provide a new insight for the diagnosis, treatment and prognosis of BLCA from the perspective of immunology. However, further experimental studies are necessary to reveal the underlying mechanisms by which these genes mediate the progression of BLCA.