Nephrometric scoring system: Recent advances and outlooks.

A nephrometry scoring system is a key standard to evaluate the feasibility of partial nephrectomy (PN). Whether based on two-dimensional or three-dimensional images, simplicity, effectiveness, and practicality are the keys to the nephrometric scoring system. Since the emergence of RENAL score in 2009, numerous scoring systems based on different anatomical parameters are established to seek accurately and few parameters to assess the risk of PN and complications. This study aimed to achieve a three-game winning streak in PN more easily and efficiently (negative resection margin, maximum preservation of normal nephron function, and avoiding short-term and long-term complications). Using PubMed, we counted 28 kinds of nephrometric scoring systems. We considered only English literatures published and excluded editorials, commentaries, and meeting abstracts. To the best of our knowledge, this is to date and most comprehensive summary as well as an outlook of the nephrometric scoring system.

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.