Conditional survival of trimodal therapy for nonmetastatic muscle-invasive bladder cancer: A SEER database analysis.

OBJECTIVE: Conventional survival analysis plays a limited role in patients who have survived a period after initial treatment. The present study analyzed how conditional survival (CS) predicted survival rate over time for nonmetastatic muscle-invasive bladder cancer (MIBC) patients after trimodal treatment. METHOD: This retrospective study from the SEER database included consecutive patients with nonmetastatic MIBC who received trimodal therapy (TMT) between January 2010 and December 2017. Kaplan-Meier analysis was used to estimate overall survival (OS) and cancer-specific survival (CSS). CS was defined as the rate of surviving y years after already surviving for x years. Multivariate Cox regression analysis was used to identify prognostic factors. RESULT: A total of 1110 nonmetastatic MIBC patients treated with TMT were included. Given a 1-, 2-, 3-, and 4-year after TMT, the rate of surviving to 5-year, respectively, improved by +5.0 (20.0%), +17.0 (32.0%), +30.0 (45.0%), and +52.8 (67.8%) from those calculated at baseline (15.0%). The 2-year CS rate of patients who had survived 1-, 2-, or 3-year after TMT improved, respectively, compared to 3-, 4-, or 5-year actual survival. Multivariate Cox regression analysis demonstrated that adverse variables (T stage, age) of OS and CSS lost their prognostic significance over time. DISCUSSION AND CONCLUSION: Conditional survival rate of surviving to 5-year after TMT kept a relatively stable level over time. In addition, those adverse variables were not always the prognostic factors over time. Only age was always the significant prognostic factor for conditional OS from baseline to 5-year survival. Our results provided real-time survival information and prognosis estimates to adjust follow-up plans for nonmetastatic MIBC patients after TMT.

Selection of Optimal Candidates for Cytoreductive Nephrectomy in Patients with Metastatic Clear Cell Renal Cell Carcinoma: A Predictive Model Based on SEER Database.

BACKGROUND: Currently, the progress of targeted drugs in the treatment of metastatic clear cell renal cell carcinoma (mccRCC) is limited. Cytoreductive nephrectomy (CN), as an alternative treatment, can improve the prognosis of patients with metastatic renal cell carcinoma to some extent. However, it is unclear which patients would benefit from this tumor reduction operation. As a consequence, we developed a predictive model to identify patients who may well benefit from CN in terms of survival. METHODS: We identified patients with metastatic clear cell renal cell carcinoma retrospectively from the Surveillance, Epidemiology, and End Results (SEER) database (2010-2015) and classified them into surgery and non-surgery groups. Propensity score matching (PSM) was performed to balance the baseline characteristics. Patients who survived longer than the median overall survival (OS) of no-surgery group were defined as surgical-benefit patients. Then, we developed a predictive model based on preoperative characteristics using multivariable Logistic regression. Calibration curves and the area under the receiver operating characteristic (AUC) were used to evaluate the efficiency of the predictive model. The clinical value of the nomogram was assessed utilizing decision curve analysis (DCA). RESULTS: Our study collected 5544 patients from the SEER database, with 2352(42.4%) receiving cytoreductive surgery. Overall survival (OS) was longer in the CN group than in the non-surgery group after 1:1 propensity scoring matching (median OS: 19 months vs 7 months; hazard ratio (HR) =0.4106, P< 0.001). In the matched surgery group, 65.7% (367) patients survived more than 7 months after the operation and they were considered to benefit from CN. The predictive model performed well on both the training group (AUC=73.4%) and the validation group (AUC=71.9%) and the calibration curves indicated a high degree of consistency. The decision curve analysis curve demonstrated the clinical utility. We classified surgical patients into the beneficial group and non-beneficial group by using the predictive model, then discovered a substantial difference in OS between the two groups. CONCLUSIONS: We developed a nomogram to select ideal mccRCC patients who might benefit from cytoreductive nephrectomy. Clinicians could make a more precise treatment strategy for mccRCC patients.

Establishment of Sunitinib-Resistant Xenograft Model of Renal Cell Carcinoma and the Identification of Drug-Resistant Hub Genes and Pathways.

INTRODUCTION: Sunitinib is the first-line targeted drug for the treatment of advanced renal cell carcinoma (RCC), but its therapeutic potential is limited by premature drug resistance. In an attempt to overcome this limitation, a sunitinib-resistant cell-derived xenograft (CDX) model of clear cell renal cell carcinoma (ccRCC) in vivo was constructed in this study. The molecular mechanism of drug resistance was analyzed using sequencing and bioinformatics tools. METHODS: First, mice were injected subcutaneously with tumor cells 786-O to create tumors and were simultaneously treated with sunitinib. After three consecutive passages, a drug-resistant xenograft model was obtained. Then, key pathways and genes were identified via second-generation sequencing of the tissue and the examination of differentially expressed genes (DEGs) with bioinformatics tools. RESULTS: Analysis of sequencing data revealed that 646 DEGs were upregulated and 465 were downregulated in the drug-resistant tissues when compared with the sensitive tissues. GO showed that the DEGs were significantly enriched in angiogenesis, cell hypoxia response, and apoptosis. KEGG analysis demonstrated that the main pathways were PI3K-Akt, HIF-1, NF-kappa B, and MAPK. Modular analysis of the PPI network indicated that the GO and KEGG analyses of module 1 with the highest ranking were mainly related to ubiquitinase activity. Similarly, the GO and KEGG analyses of the top 10 hub genes were also chiefly linked to ubiquitinase activity. Then, comprehensive expression analysis of the hub genes, and finally, the genes BTRC and TRIM32 were identified, which were consistent in all observations. CONCLUSION: In this study, through the construction of in vitro models and bioinformatics analysis, the important pathways and key genes related to ccRCC sunitinib resistance were discovered. Among them, ubiquitinase may play an important role in drug resistance and may be a potential therapeutic target and biomarker.

M2 macrophages secrete CXCL13 to promote renal cell carcinoma migration, invasion, and EMT.

OBJECTIVE: M2 macrophages are associated with a poor prognosis in a variety of malignancies. There are, however, few relevant investigations in clear cell renal cell carcinoma (ccRCC). METHODS: The expression of M2 macrophages in ccRCC tissues was first discovered using immunohistochemistry in this study. Then, M2 macrophages were created in vitro to see how they affected the proliferation, migration, invasion, and EMT of ccRCC cells. Using qPCR and prognostic analysis identifies important chemokine. Antibody neutralization tests confirmed the chemokine's involvement and function. Pathway inhibitors confirmed the main pathway of M2 macrophages in ccRCC. Finally, qPCR and IHC were used to confirm the expression of chemokine receptors in ccRCC tissues. RESULTS: The presence of M2 macrophages was linked to a poor outcome in ccRCC. M2 macrophages enhanced the proliferation, migration, invasion, and EMT of ccRCC lines in vitro. CXCL13 was identified as the main chemokine by prognostic analysis and qPCR tests. CXCL13 neutralizing antibodies can inhibit the stimulation of M2 macrophages in ccRCC lines' proliferation, migration, invasion, and EMT. M2 macrophages and CXCL13 may activate the Akt pathway in ccRCC lines, and Akt inhibitors decrease ccRCC lines proliferation, migration, invasion, and EMT. CXCR5 expression is a poor prognostic factor for renal cell carcinoma, according to qPCR and immunohistochemistry. In vivo experiments further proved that CXCL13 secreted by M2 macrophages can promote tumor proliferation. CONCLUSIONS: M2 macrophages in the immunological milieu secrete CXCL13, which promotes ccRCC proliferation, migration, invasion, and EMT. Our findings contribute to a better understanding of the function of the tumor microenvironment in the incidence and progression of ccRCC, and they may point to novel therapeutic targets for ccRCC.

Circular RNA circPPP6R3 upregulates CD44 to promote the progression of clear cell renal cell carcinoma via sponging miR-1238-3p.

Circular RNAs (circRNAs) are a type of covalently closed circular-formed RNAs and play crucial roles in the oncogenesis and progression of various human cancers. Here we identified a novel circRNA, circPPP6R3, to be highly expressed both in clear cell renal cell carcinoma (ccRCC) tissues and cell lines based on analyzing high-throughput sequencing data and qRT-PCR analysis. Highly expressed circPPP6R3 was positively correlated with higher histological grade, T stage, and M stage as well as advanced clinical stage of ccRCC patients. Functionally, knockdown of circPPP6R3 attenuated the proliferation, migration, and invasion of ccRCC cells whereas overexpression had the reverse effects. Mechanistically, the biotin-labeled pull-down assay and dual-luciferase reporter assay revealed that circPPP6R3 directly interacted with miR-1238-3p. miR-1238-3p inhibitors had a rescue effect on the proliferative and metastatic capacities by knockdown of circPPP6R3. Moreover, RNA-sequencing analysis and dual-luciferase reporter assay indicated that circPPP6R3 upregulated CD44, a cell-surface glycoprotein contributed to the cell adhesion and metastasis, via sponging to miR-1238-3p. Further investigation revealed that MMP9 and Vimentin were regulated by CD44 in ccRCC. Our study thus provided evidence that the regulatory network involving circPPP6R3/miR-1238-3p/CD44 axis might provide promising biomarkers as well as a therapeutic approach for ccRCC.

Efficacy and safety of immunological checkpoint inhibitors combined with anti-angiogenic drugs in first-line treatment of metastatic renal cell carcinoma: a systematic review and meta-analysis.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have shown promising results for the second-line treatment of metastatic renal cell carcinoma (mRCC). Several randomized controlled trials have so far also evaluated the efficacy of ICIs for first-line treatment of mRCC. In this study, we conducted a meta-analysis of relevant studies to further clarify the efficacy and safety of ICIs combined with anti-angiogenic drugs for the treatment of mRCC. METHODS: We searched the PubMed, Embase, and Cochrane libraries for RCT trials of ICIs combined with anti-angiogenic drugs for first-line treatment of mRCC published before November 20, 2019. A meta-analysis was conducted based on methodological recommendations by the Cochrane Collaboration. RESULTS: Four articles with a total of 2,967 patients met the inclusion criteria. Our meta-analysis revealed that progression-free survival (PFS) and objective response rate (ORR) were significantly improved in the experimental group while there was no significant difference in overall survival (OS) (HR 0.75, 95% CI: 0.67-0.84; HR 1.43, 95% CI: 1.07-1.91; HR 0.74, 95% CI: 0.53-1.03). After stratification for PD-L1 expression, OS, PFS, and ORR of PD-L1 positive patients were significantly increased in the experimental group (HR 0.74, 95% CI: 0.56-0.96; HR 1.66, 95% CI: 1.11-2.49; HR 0.65, 95% CI: 0.57-0.75). CONCLUSIONS: Immunological checkpoint inhibitors combined with anti-angiogenic drugs as a first-line treatment for mRCC improve PFS and ORR. This effect is more pronounced in PD-L1 positive patients, where ICIs also improve OS. ICIs do not increase the incidence of adverse events.

CircPVT1 promotes progression in clear cell renal cell carcinoma by sponging miR-145-5p and regulating TBX15 expression.

Emerging evidence revealed that circular RNAs (circRNAs) play significant roles in regulating tumorigenesis and cancer progression. However, few circRNAs were well characterized in clear cell renal cell carcinoma (ccRCC). We found that circPVT1 was significantly upregulated in ccRCC tissues and positively associated with the clinical stage. The Area Under Curve of tissue and serum circPVT1 expression in ccRCC were 0.93 and 0.86, respectively. Importantly, we demonstrated that circPVT1 promoted ccRCC growth and metastasis in vitro and in vivo. We also found that circPVT1 directly binds to miRNA-145-5p via the Biotin-labelled miRNA pulldown assay and dual-luciferase reporter assay, and miR-145-5p inhibitor significantly attenuated the effect of circPVT1 knockdown on ccRCC cells. Moreover, through RNA sequencing and bioinformatics analysis, we demonstrated that TBX15 was regulated by the circPVT1/miR-145-5p axis and predicted poor prognosis in ccRCC. These findings suggest that circPVT1 promotes ccRCC growth and metastasis through sponging miR-145-5p and regulating downstream target TBX15 expression. The circPVT1/miR-145-5p/TBX15 axis might be a potential diagnostic marker and therapeutic target in ccRCC.