A postoperative prognostic nomogram predicting recurrence for patients with conventional clear cell renal cell carcinoma

PURPOSE: Few published studies have simultaneously analyzed multiple prognostic factors to predict recurrence after surgery for conventional clear cell renal cortical carcinomas. We developed and performed external validation of a postoperative nomogram for this purpose. We used a prospectively updated database of more than 1,400 patients treated at a single institution. MATERIALS AND METHODS: From January 1989 to August 2002, 833 nephrectomies (partial and radical) for renal cell carcinoma of conventional clear cell histology performed at Memorial Sloan-Kettering Cancer Center were reviewed from the center's kidney database. Patients with von Hippel-Lindau disease or familial syndromes, as well as patients presenting with synchronous bilateral renal masses, or distant metastases or metastatic regional lymph nodes before or at surgery were excluded from study. We modeled clinicopathological data and disease followup for 701 patients with conventional clear cell renal cell carcinoma. Prognostic variables for the nomogram included pathological stage, Fuhrman grade, tumor size, necrosis, vascular invasion and clinical presentation (ie incidental asymptomatic, locally symptomatic or systemically symptomatic). RESULTS: Disease recurrence was noted in 72 of 701 patients. Those patients without evidence of disease had a median and maximum followup of 32 and 120 months, respectively. The 5-year probability of freedom from recurrence for the patient cohort was 80.9% (95% confidence interval 75.7% to 85.1%). A nomogram was designed based on a Cox proportional hazards regression model. Following external validation predictions by the nomogram appeared accurate and discriminating, and the concordance index was 0.82. CONCLUSIONS: A nomogram has been developed that can be used to predict the 5-year probability of freedom from recurrence for patients with conventional clear cell renal cell carcinoma. This nomogram may be useful for patient counseling, clinical trial design and effective patient followup strategies.     

EZH2-regulated immune risk score prognostic model predicts outcome of clear cell renal cell carcinoma

BackgroundThe enhancer of zeste homolog 2 (EZH2) plays an important role in the tumor microenvironment (TME), and EZH2 in shaping the epigenetic landscape of CD8⁺ T cell fate and function, with a particular emphasis on cancer. Here, high EZH2 expression always leads to less CD8⁺ T cell infiltration. However, clear cell renal cell carcinoma (ccRCC) is reportedly a “hot” tumor, with contradictory high EZH2 expression. Our goal was to construct a EZH2-regulated immune risk score prognostic model to predict ccRCC outcomes, and provide a prospect of clinical EZH2 inhibitors in fine-tuning T cell responses with immune therapy.MethodsWe downloaded and analyzed The Cancer Genome Atlas (TCGA), Cancer Cell Line Encyclopedia (CCLE), TISIDB database, and WebGestalt for ccRCC patients, EZH2-related tumor-infiltrating lymphocytes and immunomodulators. R packages “limma”, “BiocManager”, and “preprocessCore”, etc. were downloaded to prepare CIBERSORT files, immune cells heatmap, multivariable Cox model and survival analysis. The EZH2-regulated immune risk model’s prognostic ability was calculated by receiver operating characteristic (ROC) and area under the curve (AUC) analyses in R studio.ResultsEZH2 was highly expressed and related to poor outcome in ccRCC. However, high-expression EZH2 was not related to a “cool” tumor. Of the 49 immunomodulators significantly regulated by EZH2, forest plot showed 26 immunomodulators signatures independently associated with overall survival. The EZH2-regulated immune-risk score prognostic model was an independent prognostic factor (AUC =0.816), especially combined with clinicopathologic parameters in ccRCC overall survival prediction.ConclusionsThe EZH2-regulated immune-risk score prognostic model was an independent prognostic factor, with good accuracy and predictability, and could provide experimental data to the clinical area.     

Molecular markers for predicting prognosis of renal cell carcinoma

Metastatic or recurrent renal cell carcinoma (RCC) carries a poor prognosis and long term survival is rare. However, many small RCCs that are incidentally discovered have an indolent course even without treatment. The variability in clinical outcome is a reflection of the underlying tumor biology. Currently, clinical variables such as tumor stage and histologic grade are widely accepted surrogates for tumor-specific cellular and molecular processes. Ongoing advances in genomic and proteomic technologies have produced an expanding list of molecular markers for predicting prognosis. We review expression array studies evaluating molecular signatures for predicting prognosis in patients with RCC and describe specific prognostic markers that have been validated in at least 50 cases of RCC.     

External validation of the RENAL nephrometry score nomogram for predicting high-grade renal cell carcinoma in solid, enhancing, and small renal masses

Purpose

To confirm predictive accuracies of the RENAL nephrometry score (RNS) nomogram for identifying malignancy and high-grade renal cell carcinoma (RCC) in an external cohort of small renal masses (SRMs).

Methods

A total of 1,129 patients who underwent extirpative renal surgery for solid and enhancing cT1 renal tumors between 2005 and 2012 at a single institution were included in the validation cohort. A single uro-radiologist utilized computed tomography image reconstruction to classify tumors according to the RNS. The area under the curve (AUC) and calibration plots were used to determine predictive accuracies of malignancy and high-grade models of the RNS nomogram.

Results

Malignant and high-grade tumors were identified in 1,012 (89.6 %) and 389 (38.4 %) patients with cT1 tumors, and in 658 (87.3 %) and 215 (32.6 %) patients with cT1a tumors, respectively. Predictive performances of the nomogram for malignancy and high-grade models revealed AUCs of 0.722 and 0.574 for cT1 tumors, and 0.727 and 0.495 for cT1a tumors, respectively. The predictive value of the malignancy model was comparable to that of the model-development cohort (AUC = 0.76); however, the predictive value of the high-grade model was inferior to that of the model-development cohort (AUC = 0.73).

Conclusions

Unlike previous validation studies, we report inferior predictive performance of the RNS nomogram for discriminating high-grade RCC in solid and enhancing SRMs. This suggests that the RNS nomogram may be unreliable for preoperatively predicting high-grade RCC in SRMs, in which tumor size, the key determinant of high-grade RCC, is a limiting factor.     

Comparison of CTS5 risk model and 21-gene recurrence score assay in large-scale breast cancer population and combination of CTS5 and recurrence score to develop a novel nomogram for prognosis prediction

BackgroundBreast cancer is the most common malignancy in women. Clinical models such as Oncotype DX recurrence score (RS) and Clinical Treatment Score post–5 years (CTS5) model for survival prediction are crucial for clinical practice. However, it remains unclear whether CTS5 or RS would be a more powerful clinical model for recurrence risk evaluation. Therefore, we conducted the present study to compare the performance of CTS5 risk model and RS on different recurrence evaluation. And we further integrated the two models into a novel nomogram to improve the power for prognosis prediction.MethodsFemale patients with invasive hormone receptor positive breast cancer in the Surveillance, Epidemiology, and End Results Program (SEER) database with RS data available were included. The clinicopathological data were directly extracted from SEER database. Participants were divided into three subsets according to recurrence timing (<36 months, between 36 and 60 months, and >60 months) for model evaluation. Survival receiver operating characteristic curve and C-index were calculated to evaluate discrimination. Calibration curve were used to visual inspection for calibration. Model comparison was assessed by net reclassification index (NRI) method. Nomogram prognostic model was developed with the combination of CTS5 score and RS and also included other critical clinicopathological parameters.ResultsIn total, 64044 breast cancer patients were enrolled for analysis. The number of patients with survival <36 months (early recurrence subset), 36–60 months (intermediate recurrence subset) and >60 months (late recurrence subset) were 64044, 36878 and 15926, respectively. For model discrimination, CTS5 model was superior to RS for overall survival (OS) prediction (likelihood ratio test P < 0 0.001). RS model showed better performance for breast cancer specific survival (BCSS) in late recurrence subsets and worse performance in early and intermediate recurrence subsets than CTS5 (likelihood ratio test P < 0 0.001). For calibration, CTS5 model was superior to RS model for OS, which overestimated the recurrence risk in low-risk subgroup. Both models overestimated the risk for BCSS. In either early/intermediate/late recurrence patient subsets, there was no significant difference in NRI between two models in terms of both BCSS and OS, indicating the two models had comparable prognostic value. The nomogram which combined these two models largely improved the discrimination and calibration power (C-index 0.70–0.72).ConclusionsOur study proved the CTS5 risk model had comparable prognostic value as RS in HR + breast cancer patients. And the novel nomogram model had better discrimination and calibration than both CTS5 and RS, and future large-scale clinical trials are warranted for further validation.     

Leibovich score is the optimal clinico-pathological system associated with recurrence of non-metastatic clear cell renal cell carcinoma

PurposeTo determine the optimal post-operative risk stratification system associated with survival following surgery for clear cell renal cell carcinoma (ccRCC): tumour grade, tumour stage, Leibovich 2003, Leibovich 2018, Kattan, Stage, size, grade and necrosis (SSIGN) or UCLA Integrated Staging System (UISS) scores.Methods542 patients with non-metastatic ccRCC who underwent nephrectomy 2008?2018 were reviewed. Primary outcome was recurrence-free survival (RFS), with secondary outcomes cancer-specific survival (CSS) and overall survival (OS).ResultsAll systems were significantly associated with RFS, CSS and OS by Kaplan-Meier and unadjusted Cox-regression. ROC analysis identified that Leibovich 2003, Leibovich 2018A or B and SSIGN were optimally association with 5year RFS (AUC (Area under curve) 0.87, 0.86, 0.86 and 0.86), but Leibovich 2003 or 2018A offered additional information on adjusted regression analysis (HR 1.24, P = 0.02; HR 1.17, P = 0.04). ROC analysis identified that Leibovich 2018B, Leibovich 2003, SSIGN and UISS were equally associated with 5 year OS (AUC 0.76, 0.74, 0.73 and 0.72). UISS added additional explanation of the variance in OS on adjusted regression analysis (HR 1.96, P = 0.002). A novel combination of Leibovich 2003 score and Eastern Co-operative Oncology Group (ECOG) performance status improved 5 year OS association compared to the Leibovich 2003 alone (AUC 0.78, P = 0.001), without affecting association with 5year RFS (AUC 0.87, P = 0.75).ConclusionsAll systems were robust tools associated with RFS, CSS and OS in ccRCC. In our cohort, the Leibovich 2003 and Leibovich 2018A scores may be better associated with RFS compared to other strategies. The UISS, Leibovich 2018B or Leibovich 2003 combined with ECOG performance status may stratify OS better than other modalities.     

Impact of modified Glasgow prognostic score on predicting prognosis and modification of risk model for patients with metastatic renal cell carcinoma treated with first line tyrosine kinase inhibitor

Introduction and ObjectivesIntermediate risk group of the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) criteria is thought to consist of patients with different prognoses. This study investigated the impact of a pretreated modified Glasgow prognostic score (mGPS), which is defined on the basis of the pretreated serum albumin and C-reactive protein level, on predicting the prognosis of patients with metastatic renal cell carcinoma (mRCC) and its usefulness for the re-stratification of patients into a more improved risk model.Materials and MethodsOne hundred ninety-six mRCC patients treated with first-line tyrosine kinase inhibitor (TKI) were retrospectively investigated. All patients were classified into either a high-mGPS or a low-mGPS group on the basis of mGPS score upon starting systemic therapy, the overall survival (OS) and cancer specific survival (CSS) rates in each group were compared. We use decision curve analysis and calculate C-index based on OS and CSS to compare IMDC+mGPS model and IMDC model.ResultsThe categories of favorable, intermediate, and poor risk groups in the IMDC model were assessed in 32, 113, and 51 cases, respectively. The low- and high-mGPS groups consisted of 149 and 47 cases. The median OS in the high- and low-mGPS groups were 38.4 months and 5.6 months, and their median CSSs were 41.0 months and 5.6 months, respectively (P < 0.0001). Multivariate analysis showed that a high mGPS, multiple metastatic organs, and hypercalcemia were independent predictive factors for a worse OS (P = 0.0260). Next, we divided the intermediate risk group into two subgroups using the mGPS score. The OS and CSS for the high-mGPS subgroup were significantly worse than those for the low-mGPS one (P = 0.0024, median OS: 21.0 months and 33.7 months, P = 0.0007, median CSS: 21.0 months and 39.8 months), and there was no significant difference in OS between the high-mGPS subgroup in the intermediate risk group and poor risk group (P = 0.2250). The value of C-index based on OS at IMDC and IMDC+mGPS model were 0.6771 and 0.6967, and those based on CSS were 0.6850 and 0.7080, respectively. In decision curve analysis to evaluate the clinical net benefit using the IMDC+mGPS model compared to the IMDC model, there was no significant difference between the two groups.ConclusionmGPS is useful for establishing a more improved prognostic model that is able to stratify mRCC patients treated with first-line TKI.     

Identification and validation of TGFBI as a promising prognosis marker of clear cell renal cell carcinoma

ObjectiveTo identify prognostic biomarkers in clear cell renal cell carcinoma (ccRCC) using a proteomic approach.Material and methodsWe performed a comparative proteomic profiling of ccRCC and normal renal tissues from 9 different human specimens. We assessed differential protein expression by iTRAQ (isobaric tagging reagent for absolute quantify) labeling with regard to tumor aggressiveness according to the stage, size, grade, and necrosis (SSIGN) score and confirmed our results using Western blot (9 patients) and immunohistochemistry (135 patients) analysis.ResultsAfter proteomic analysis, 928 constitutive proteins were identified. Among these proteins, 346 had a modified expression in tumor compared with that of normal tissue. Pathway and integrated analyses indicated the presence of an up-regulation of the pentose phosphate pathway in aggressive tumors. In total, 14 proteins were excreted and could potentially become biomarkers. Overexpression of transforming growth factor, beta-induced (TGFBI) in ccRCC was confirmed using Western blot and immunohistochemistry analysis. A significant association was found between the presence of TGFBI expression with tumor category T3–4 (P<0.0001), Fuhrman grades III and IV (P<0.0001), tumor size>4 cm (P<0.0001), presence of tumor necrosis (P<0.0001), nodal involvement (n = 0.009), metastasis (P = 0.012), SSIGN score≥5 (P<0.0001), cancer progression (P<0.0001), and cancer-specific death (P<0.0001). Cancer-specific survival was significantly better for patients with no cytoplasmic TGFBI expression (1-, 3-, 5-y cancer-specific survival of 94.7%, 87.8%, and 73.4% vs. 92.9%, 71.2%, and 49.8%, respectively; P<0.0001).ConclusionWe identified 346 proteins involved in renal carcinogenesis and confirmed the presence of a metabolic shift in aggressive tumors. TGFBI was overexpressed in tumors with high SSIGN scores and was significantly associated with oncologic outcomes.     

血管生成相关基因多态性与肾透明细胞癌的相关性研究

目的 探讨血管生成相关基因多态性与肾透明细胞癌发病风险的关系. 方法 选取2005年6月至2012年9月收治的859例经病理检查证实的肾透明细胞癌患者及1 004例健康对照人群,采集研究对象外周血,在7个与血管生成有关的基因中(HIF1A,EPAS1,VEGFA,VEGFR1,VEGFR2,VEGFR3和PDGFRB)筛选出24个候选单核苷酸多态性位点,采用单碱基微测序技术进行基因分型.应用Logistic回归模型调整混杂因素后,分析各基因型与肾透明细胞癌发生的关系.结果 24个SNP位点中19个对照组基因型均符合遗传平衡定律.VEGFA基因rs2010963位点,VEGFR1基因rs3812867位点,VEGFR3基因rs1382302、rs448012、rs 1049095位点等5个位点的多态性与肾透明细胞癌发生显著相关(P＜0.05).多重检验校正后,仅有VEGFA基因rs2010963位点和VEGFR3基因的rs448012位点与肾透明细胞癌发生存在相关性(P＜0.05).VEGFA基因rs2010963位点携带CC/GC基因型的患者较携带GG基因型患者的肾透明细胞癌发病率显著升高(FDR=0.048,OR=1.38,95％ CI:1.13 ～ 1.69),VEGFR3基因rs448012位点携带CC/GC基因型的患者肾透明细胞癌的发病率显著高于携带GG基因型的患者(FDR=0.045,OR=1.36,95％CI:1.12～1.66). 结论 VEGFA基因的rs2010963位点与VEGFR3基因的rs448012位点多态性与肾透明细胞癌发病相关.     

建立预测阴茎鳞状细胞癌区域淋巴结转移风险的列线图

目的 根据阴茎癌原发灶的病理指标,建立预测阴茎鳞状细胞癌区域淋巴结转移风险的列线图. 方法 收集1990-2005年73例阴茎鳞状细胞癌患者资料,患者均接受阴茎肿瘤切除和区域淋巴结清扫术.免疫组化法检测分子指标(p53、Ki-67、E-cadherin和MMP-9)的表达水平.采用Logistic回归模型建立列线图.预测淋巴结转移的变量包括年龄、分期、分级、蛋白表达水平(p53、Ki-67、E-cadherin和MMP-9)和脉管侵犯.其中年龄为连续变量,分期、分级、蛋白表达水平和脉管侵犯为分类变量. 结果 肿瘤分级、p53表达水平和脉管侵犯是预测区域淋巴结转移的独立预后因素(P<0.05),回归系数分别为3.97、2.12和2.37,OR值分别为52.99、8.33和10.70.用于预测淋巴结转移风险的列线图显示出良好的一致系数(0.92)和良好的校准. 结论 基于阴茎鳞状细胞癌原发灶的病理特征,构建预测区域淋巴结转移风险的列线图,不仅有助于个体化的判断肿瘤转移的风险,并且有助于与患者的交流和治疗选择.     

免疫相关LncRNA与肾透明细胞癌预后关系分析及预测评分模型建立

目的:探讨肾透明细胞癌(clear cell renal cell carcinoma,ccRCC)中免疫相关LncRNA表达与肿瘤预后的关系,并构建预后相关的预测评分模型.方法:从TCGA数据中下载537例ccRCC转录组测序数据及相应的临床预后信息,采用R软件和Perl软件利用生物信息学方法提取ccRCC免疫相关L...     

Identification of a novel immune-related microRNA prognostic model in clear cell renal cell carcinoma

BackgroundClear cell renal cell carcinoma (ccRCC) is a type of kidney cancer, and one of the most common malignant tumors. Many studies have shown that certain microRNAs (miRNAs) play an important role in the occurrence and development of ccRCC. Nevertheless, the prognosis of ccRCC patients is very rarely based on these “immuno-miRs”. Our aim was thus to determine the relationship between immune-related miRNA signatures and ccRCC.MethodsWe downloaded the miRNA expression data from 521 KIRC and 71 normal tissues in The Cancer Genome Atlas (TCGA). We used “limma” package and univariate Cox regression analysis to identify differentially expressed miRNAs (DEMs) that related to overall survival (OS). We applied lasso and multivariate Cox regression analyses to construct a prognostic model based on immuno-miRs. We evaluated the performance of model by using the Kaplan-Meier method. Furthermore, Cox regression analysis was used to determine independent prognostic signatures in ccRCC.ResultsA total of 59 significant immuno-miRs were identified. We use univariate Cox regression analysis to acquire 18 immune-related miRNAs which were markedly related to OS of ccRCC patients in the training set. We then constructed the 9-immune-related-miRNA prognostic model (miR-21, miR-342, miR-149, miR-130b, miR-223, miR-365a, miR-9-1, and miR-146b) by using lasso and multivariate Cox regression. Further analysis suggested that the immune-related prognostic model could be an independent prognostic indicator for patients with ccRCC. The prognostic performance of the 9-immune-related-miRNA prognostic model was further validated successfully in the testing set.ConclusionsWe established a novel immune-based prognostic model of ccRCC based on potential prognostic immune-related miRNAs. Our results indicated that the 9-miRNA signature could be a practical and reliable prognostic tool for ccRCC.     

Immunohistochemical negative expression of ezrin predicts poor prognosis in clear cell renal cell carcinoma

PurposeTo analyze the immunohistochemical expression of ezrin and moesin in clear cell renal cell carcinoma (ccRCC). These proteins, as part of the ezrin-radixin-moesin complex link the cell membrane to the actin cytoskeleton, affecting such processes as cell adhesion, cell survival, cell motility, and signal transduction. Our aim was to examine the impact of their expression on clinical outcomes and survival rates.Patients and methodsFive hundred seventy-five consecutive patients who had been treated surgically for ccRCC in a single center between 1985 and 2016 were selected. A single pathologist reviewed all cases to perform a uniform reclassification and determined the most representative tumor areas for construction of a tissue microarray.ResultsOf all ccRCC specimens, 106 (18.3%) were negative for ezrin, and 469 (81.7%) had positive ezrin expression; 16 (2.8%) were negative and 559 (97.2%) were positive for moesin, respectively. Ezrin expression was associated with pT stage (P < 0.001), clinical stage (P = 0.012), synchronic metastasis (P < 0.001), incidental tumors (P = 0.007), and International Society of Urological Pathology histological grade (P = 0.025). There was a correlation between moesin expression and clinical stage (P = 0.027), pT stage (P = 0.025), and pN stage (P = 0.007). Ezrin expression significantly influenced tumor-related deaths. By multivariate analysis, negative ezrin expression was an independent risk factor for disease-specific survival (HR 1.89; 95% CI 1.11–3.20).ConclusionsNegativity for ezrin in ccRCC patients significantly impacts survival rates. We encourage further prospective studies to analyze ezrin analysis to evaluate its significance in the prognosis of ccRCC.