Predicting recurrence and survival in patients with non-metastatic renal-cell carcinoma after nephrectomy: a prospective population-based study with multicenter validation

Background: Accurate prognostication of oncological outcomes is crucial for the optimal management of patients with renal cell carcinoma (RCC) after surgery. Previous prediction models were developed mainly based on retrospective data in the Western populations, and their predicting accuracy remains limited in contemporary, prospective validation. We aimed to develop contemporary RCC prognostic models for recurrence and overall survival (OS) using prospective population-based patient cohorts and compare their performance with existing, mostly utilized ones. Methods: In this prospective analysis and external validation study, the development set included 11 128 consecutive patients with non-metastatic RCC treated at a tertiary urology center in China between 2006 and 2022, and the validation set included 853 patients treated at 13 medical centers in the USA between 1996 and 2013. The primary outcome was progression-free survival (PFS), and the secondary outcome was OS. Multivariable Cox regression was used for variable selection and model development. Model performance was assessed by discrimination [Harrell’s C-index and time-dependent areas under the curve (AUC)] and calibration (calibration plots). Models were validated internally by bootstrapping and externally by examining their performance in the validation set. The predictive accuracy of the models was compared with validated models commonly used in clinical trial designs and with recently developed models without extensive validation. Results: Of the 11 128 patients included in the development set, 633 PFS and 588 OS events occurred over a median follow-up of 4.3 years [interquartile range (IQR) 1.7–7.8]. Six common clinicopathologic variables (tumor necrosis, size, grade, thrombus, nodal involvement, and perinephric or renal sinus fat invasion) were included in each model. The models demonstrated similar C-indices in the development set (0.790 [95% CI 0.773–0.806] for PFS and 0.793 [95% CI 0.773–0.811] for OS) and in the external validation set (0.773 [0.731–0.816] and 0.723 [0.731–0.816]). A relatively stable predictive ability of the models was observed in the development set (PFS: time-dependent AUC 0.832 at 1 year to 0.760 at 9 years; OS: 0.828 at 1 year to 0.794 at 9 years). The models were well calibrated and their predictions correlated with the observed outcome at 3, 5, and 7 years in both development and validation sets. In comparison to existing prognostic models, the present models showed superior performance, as indicated by C-indices ranging from 0.722 to 0.755 (all P<0.0001) for PFS and from 0.680 to 0.744 (all P<0.0001) for OS. The predictive accuracy of the current models was robust in patients with clear-cell and non-clear-cell RCC. Conclusions: Based on a prospective population-based patient cohort, the newly developed prognostic models were externally validated and outperformed the currently available models for predicting recurrence and survival in patients with non-metastatic RCC after surgery. The current models have the potential to aid in clinical trial design and facilitate clinical decision-making for both clear-cell and non-clear-cell RCC patients at varying risk of recurrence and survival

A Risk Signature with Autophagy-Related Long Noncoding RNAs for Predicting the Prognosis of Clear Cell Renal Cell Carcinoma: Based on the TCGA Database and Bioinformatics

Background. Disorders of autophagic processes have been reported to affect the survival outcome of clear cell renal cell carcinoma (ccRCC) patients. The purpose of our study was to identify and validate the candidate prognostic long noncoding RNA signature of autophagy. Methods. Transcriptome profiles were obtained from The Cancer Genome Atlas. The autophagy gene list was obtained from the Human Autophagy Database. Based on coexpression analysis, we obtained a list of autophagy-related lncRNAs (ARlncRNAs). GO enrichment analysis and KEGG pathway analysis were conducted to explore the functional annotation of these ARlncRNAs. Univariate and multivariate Cox regression analyses were conducted to elucidate the correlation between overall survival and the expression level of each ARlncRNAs. We then established a prognostic signature that was a linear combination of the regression coefficients from the multivariate Cox regression model (β) multiplied by the expression levels of the respective ARlncRNAs in the training cohort. The predictive performance was tested in the validation cohort. Additionally, the independence of the risk signature was assessed, and the relationship between the risk signature and conventional clinicopathological features was explored. Results. Seven autophagy-related lncRNAs with prognostic value (SNHG3, SNHG17, MELTF-AS1, HOTAIRM1, EPB41L4A-DT, AP003352.1, and AC145423.2) were identified and integrated into a risk signature, dividing patients into low-risk and high-risk groups. The risk signature was independent of conventional clinical characteristics as a prognostic indicator of ccRCC (HR, 1.074, 95% confidence interval: 1.036-1.113, p<0.001) and was valuable in the prediction of ccRCC progression. Conclusion. Our risk signature has potential prognostic value in ccRCC, and these ARlncRNAs may play a significant role in ccRCC tumor biology

Changing Patterns in Cancer Mortality from 1987 to 2020 in China

Background: China has the highest number of new cancer cases and deaths worldwide, posing huge health and economic burdens to society and affected families. This study comprehensively analyzed secular trends of national cancer mortality statistics to inform future prevention and intervention programs in China. Methods: The annual estimate of overall cancer mortality and its major subtypes were derived from the National Health Commission (NHC). Joinpoint analysis was used to detect changes in trends, and we used age-period-cohort modeling to estimate cohort and period effects in Cancers between 1987 and 2020. Net drift (overall annual percentage change), local drift (annual percentage change in each age group), longitudinal age curves (expected longitudinal age-specific rate), and period (cohort) relative risks were calculated. Results: The age-standardized cancer mortality in urban China has shown a steady downward trend but has not decreased significantly in rural areas. Almost all cancer deaths in urban areas have shown a downward trend, except for colorectal cancer in men. Decreasing mortality from cancers in rural of the stomach, esophagus, liver, leukemia, and nasopharynx was observed, while lung, colorectal cancer female breast, and cervical cancer mortality increased. Birth cohort risks peaked in the cohorts born around 1920–1930 and tended to decline in successive cohorts for most cancers except for leukemia, lung cancer in rural, and breast and cervical cancer in females, whose relative risks were rising in the very recent cohorts. In addition, mortality rates for almost all types of cancer in older Chinese show an upward trend. Conclusions: Although the age-standardized overall cancer mortality rate has declined, and the urban-rural gap narrowed, the absolute cancer cases kept increasing due to the growing elderly population in China. The rising mortality related to lung, colorectal, female breast, and cervical cancer should receive higher priority in managing cancer burden and calls for targeted public health actions to reverse the trend

Comparison of Transperitoneal and Retroperitoneal Robotic Partial Nephrectomy for Patients with Completely Lower Pole Renal Tumors

(1) Background: For completely lower pole renal tumors, we compared the perioperative outcomes of robotic partial nephrectomy via transperitoneal and retroperitoneal approaches. (2) Methods: Complete lower pole renal tumors were defined as tumors that received 1 point for the “L” element of the R.E.N.A.L. and located at the lower pole of kidney. After confirming consistency in baseline characteristics, oncological and functional benefits were compared. Pentafecta achievement was used to represent the perioperative optimal outcome, followed by multivariate analysis of factors associated with the lack of pentafecta achievement. (3) Results: Among 151 patients identified, 116 (77%) underwent robotic partial nephrectomy via a transperitoneal approach and 35 (23%) via a retroperitoneal approach. Patients undergoing transperitoneal robotic partial nephrectomy experienced more blood loss than those undergoing retroperitoneal robotic partial nephrectomy (50 mL vs. 40 mL, p = 0.015). No significant differences were identified for operative time (120 min vs. 120 min), ischemia time (19 min vs. 20 min), positive surgical margins (0.0% vs. 2.86%), postoperative rate of complication (12.07% vs. 5.71%). No significant differences were identified in pathologic variables, eGFR decline in postoperative 12-month (3.9% vs. 5.4%) functional follow-up. Multivariate cox analysis showed that tumor size (OR: 0.523; 95% CI: 0.371–0.736; p < 0.001) alone was independently correlated to the achievement of pentafecta. (4) Conclusions: For completely lower pole renal tumors, transperitoneal and retroperitoneal robotic partial nephrectomy provide similar outcomes. These two surgical approaches remain feasible options for these cases

The protective effects of aqueous extract of Schisandra sphenanthera against alcoholic liver disease partly through the PI3K-AKT-IKK signaling pathway

Purpose: This study aimed to investigated the key chemical components and the effect of the aqueous extract of Schisandra sphenanthera (SSAE) on alcoholic liver disease (ALD) and the related molecular mechanism. Methods: This study employed UPLC-Q-TOF-MS/MS to identify the chemical compositions in SSAE. ALD rat model was established through oral administration of white spirit. Transcriptome sequencing, weighted gene co-expression network construction analysis (WGCNA), and network pharmacology were used to predict key compositions and pathways targeted by SSAE for the treatment of ALD. Enzyme-linked immunosorbent assay (ELISA), biochemical kits, hematoxylin-eosin (HE) staining, Western blotting (WB) analysis, and immunohistochemical analysis were used to validate the mechanism of action of SSAE in treating ALD. Results: Active ingredients such as schisandrin A, schisandrol A, and schisandrol B were found to regulate the PI3K/AKT/IKK signaling pathway. Compared to the model group, the SSAE group demonstrated significant improvements in cellular solidification and tissue inflammation in the liver tissues of ALD model rats. Additionally, SSAE regulated the levels of a spartate aminotransferase (AST), alanine aminotransferase (ALT), alcohol dehydrogenase (ADH), and aldehyde Dehydrogenase (ALDH) in serum (P < 0.05); Western blotting and immunohistochemical analyses showed that the expression levels of phosphorylated PI3K, AKT, IKK, NFκB, and FOXO1 proteins were significantly reduced in liver tissues (P < 0.05), whereas the expression level of Bcl-2 proteins was significantly increased (P < 0.05). Conclusion: The active components of SSAE were schisandrin A, schisandrol A, and schisandrol B, which regulated the phosphorylation levels of PI3K, AKT, IKK, and NFκB and the expression of FOXO1 protein and upregulated the expression of Bcl-2 protein in the liver tissues of ALD rats. These findings indicate that SSAE acts against ALD partly through the PI3K-AKT-IKK signaling pathway. This study provided a reference for future research and treatment of ALD and the development of novel natural hepatoprotective drugs