Staging of Renal Cell Carcinoma: Past, Present, and Future

Construction and validation of a ferroptosis-related long noncoding RNA signature in clear cell renal cell carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is characterized by the accumulation of lipid-reactive oxygen species. Ferroptosis, due to the lipid peroxidation, has been reported to be strongly correlated with tumorigenesis and progression. However, the functions of the ferroptosis process in ccRCC remain unclear.

Methods

After sample cleaning, data integration, and batch effect removal, we used the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases to screen out the expression and prognostic value of ferroptosis-related lncRNAs and then performed the molecular subtyping using the K-means method. Then, the functional pathway enrichment and immune microenvironment infiltration between the different clusters were carried out. The results showed a significant difference in immune cell infiltration between the two clusters and the associated marker responded to individualized differences in treatment. Then, least absolute shrinkage and selection operator (LASSO) Cox regression was used to establish a prognostic signature based on 5 lncRNAs. This signature could accurately predicted patient prognosis and served as an independent clinical risk factor. We then combined significant clinical parameters in multivariate Cox regression and the prognostic signature to construct a clinical predictive nomogram, which provides appropriate guidance for predicting the overall survival of ccRCC patients.

Results

The prognostic differentially expressed ferroptosis-related LncRNAs (DEFRlncRNAs) were found, and 5 lncRNAs were finally used to establish the prognostic signature in the TCGA cohort, with subsequently validation in the internal and external cohorts. Moreover, we conducted the molecular subtyping and divided the patients in the TCGA cohort into two clusters showing differences in Hallmark pathways, immune infiltration, immune target expression, and drug therapies. Differences between clusters contributed to individualizing treatment. Furthermore, a nomogram was established to better predict the clinical outcomes of the ccRCC patients.

Conclusions

Our study conducted molecular subtyping and established a novel predictive signature based on the ferroptosis-related lncRNAs, which contributed to the prognostic prediction and individualizing treatment of ccRCC patients.

Characteristics and Outcome of Children with Renal Cell Carcinoma: A Narrative Review

Pediatric renal cell carcinoma (RCC) is a rare type of kidney cancer, most commonly occurring in teenagers and young adolescents. Few relatively large series of pediatric RCC have been reported. Knowledge of clinical characteristics, outcome and treatment strategies are often based on the more frequently occurring adult types of RCC. However, published pediatric data suggest that clinical, molecular and histological characteristics of pediatric RCC differ from adult RCC. This paper summarizes reported series consisting of ≥10 RCC pediatric patients in order to create an up-to-date overview of the clinical and histopathological characteristics, treatment and outcome of pediatric RCC patients.

Comparison of digital image analysis versus visual assessment to assess survivin expression as an independent predictor of survival for patients with clear cell renal cell carcinoma

We previously used quantitative digital image analysis to report that high immunohistochemical tumor expression levels of survivin independently predict poor outcome among patients with clear cell renal cell carcinoma. However, given the cumbersome and costly nature of digital image analysis, we evaluated simple visual assessment as an alternative to digital image analysis for assessing survivin as a predictor of clear cell renal cell carcinoma patient outcomes. We identified 310 patients treated surgically for unilateral, sporadic, clear cell renal cell carcinoma at our institution between 1990 and 1994. Survivin expression was quantified independently by digital image analysis and visual assessment in paraffin slides using a commercially available antibody. We examined the agreement between the 2 methods using the kappa statistic and then used Cox regression to compare the ability of the 2 methods to predict renal cell carcinoma death. The kappa statistic comparing high survivin expression determined by digital image analysis versus visual assessment was .68, indicating substantial agreement between the 2 methods. Moreover, even after multivariate adjustment, the association of high survivin expression with risk of renal cell carcinoma death was similar for both visual assessment (risk ratio = 2.01; 95% confidence interval, 1.26-3.22) and digital image analysis (risk ratio = 1.75; 95% confidence interval, 1.10-2.80). Finally, among patients with "moderate risk" (Stage, Size, Grade, and Necrosis scores 3-6) and "high risk" (Stage, Size, Grade, and Necrosis scores 7 or greater) clear cell renal cell carcinoma, high survivin expression determined by visual assessment was significantly associated with poorer survival (P = .006 and P = .017, respectively). Herein, we demonstrate substantial agreement between survivin quantification by digital image analysis and visual assessment. We further confirm that high survivin expression assessed by visual assessment remains an independent predictor of aggressive clear cell renal cell carcinoma behavior. Thus, visual assessment represents an economical, widely available, and reliable method to assess survivin as a predictor of clear cell renal cell carcinoma patient outcomes.