Stage, Size, Grade, And Necrosis Research Articles

Establishment and validation of a novel nomogram to predict overall survival after radical nephrectomy

Objective: To establish a nomogram prognostic model for predicting the 5-, 10-, and 15-year overall survival (OS) of non-metastatic renal cell carcinoma patients managed with radical nephrectomy (RN), compare the modelled results with the results of pure pathologic staging, the Karakiewicz nomogram and the Mayo Clinic Stage, Size, Grade, and Necrosis (SSIGN) score commonly used in foreign countries, and stratify the patients into different prognostic risk subgroups. Methods: A total of 1 246 non-metastatic renal cell carcinoma patients managed with RN in Sun Yat-sen University Cancer Center (SYSUCC) from 1999 to 2020 were retrospectively analyzed. Multivariate Cox regression analysis was used to screen the variables that influence the prognosis for nomogram establishment, and the bootstrap random sampling was used for internal validation. The time-receiver operating characteristic curve (ROC), the calibration curve and the clinical decision curve analysis (DCA) were applied to evaluate the nomogram. The prediction efficacy of the nomogram and that of the pure pathologic staging, the Karakiewicz nomogram and the SSIGN score was compared through the area under the curve (AUC). Finally, patients were stratified into different risk subgroups according to our nomogram scores. Results: A total of 1 246 patients managed with RN were enrolled in this study. Multivariate Cox regression analysis showed that age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological T and N stages were independent prognostic factors for RN patients (all P<0.05). A nomogram model named SYSUCC based on these factors was built to predict the 5-, 10-, and 15-year survival rate of the participating patients. In the bootstrap random sampling with 1 000 iterations, all these factors occurred for more than 800 times as independent predictors. The Harrell's concordance index (C-index) of SYSUCC was higher compared with pure pathological staging [0.770 (95% CI: 0.716-0.823) vs 0.674 (95% CI: 0.621-0.728)]. The calibration curve showed that the survival rate as predicted by the SYSUCC model simulated the actual rate, while the clinical DCA showed that the SYSUCC nomogram has a benefit in certain probability ranges. In the ROC analysis that included 857 patients with detailed pathological nuclear stages, the nomogram had a larger AUC (5-/10-year AUC: 0.823/0.804) and better discriminating ability than pure pathological staging (5-/10-year AUC: 0.701/0.658), Karakiewicz nomogram (5-/10-year AUC: 0.772/0.734) and SSIGN score (5-/10-year AUC: 0.792/0.750) in predicting the 5-/10-year OS of RN patients (all P<0.05). In addition, the AUC of the SYSUCC nomogram for predicting the 15-year OS (0.820) was larger than that of the SSIGN score (0.709), and there was no statistical difference (P<0.05) between the SYSUCC nomogram, pure pathological staging (0.773) and the Karakiewicz nomogram (0.826). The calibration curve was close to the standard curve, which indicated that the model has good predictive performance. Finally, patients were stratified into low-, intermediate-, and high-risk subgroups (738, 379 and 129, respectively) according to the SYSUCC nomogram scores, among whom patients in intermediate- and high-risk subgroups had a worse OS than patients in the low-risk subgroup (intermediate-risk group vs. low-risk group: HR=4.33, 95% CI: 3.22-5.81, P<0.001; high-risk group vs low-risk group: HR=11.95, 95% CI: 8.29-17.24, P<0.001), and the high-risk subgroup had a worse OS than the intermediate-risk group (HR=2.63, 95% CI: 1.88-3.68, P<0.001). Conclusions: Age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological stage were independent prognostic factors for non-metastasis renal cell carcinoma patients after RN. The SYSUCC nomogram based on these independent prognostic factors can better predict the 5-, 10-, and 15-year OS than pure pathological staging, the Karakiewicz nomogram and the SSIGN score of patients after RN. In addition, the SYSUCC nomogram has good discrimination, agreement, risk stratification and clinical application potential.

Comparison and validation of different risk models for papillary renal cell carcinoma.

Several prognostic algorithms were specifically or nonspecifically used for papillary renal cell carcinoma (PRCC). No consensus was reached upon their efficacy of discrimination. We aim to compare the stratifying ability of current models or systems in predicting the risk of recurrence of PRCC. A PRCC cohort consisting of 308 patients from our institution and 279 patients from The Cancer Genome Atlas (TCGA) was generated. With ISUP grade, TNM classification, UCLA Integrated Staging System (UISS), STAGE, SIZE, GRADE AND NECROSIS (SSIGN), Leibovich model and VENUSS system, recurrence-free survival (RFS), disease-specific survival (DSS) and overall survival (OS) were studied using Kaplan-Meier method and concordance index (c-index) was compared. Differences between risk groups in gene mutation and infiltration of inhibitory immune cells were studied with TCGA database. All the algorithms were able to stratify patients in RFS as well as DSS and OS (all P < 0.001). VENUSS score and risk group generally had the highest and balanced c-index (0.815 and 0.797 for RFS). ISUP grade, TNM stage and Leibovich model had the lowest c-indexes in all analysis. Among the 25 most frequently mutated genes in PRCC, eight had different mutation frequency between VENUSS low- and intermediate-/high-risk patients and mutated KMT2D and PBRM1 resulted in worsened RFS (P = 0.053 and P = 0.007). Increased Treg cells in tumors of intermediate-/high- risk patients were also identified. VENUSS system showed better predictive accuracy in RFS, DSS and OS compared with SSIGN, UISS and Leibovich risk models. VENUSS intermediate-/high-risk patients had increased frequency of mutation in KMT2D and PBRM1 and increased infiltration of Treg cells.

A preoperative CT-based deep learning radiomics model in predicting the stage, size, grade and necrosis score and outcome in localized clear cell renal cell carcinoma: A multicenter study

Background and purposeThe Stage, Size, Grade and Necrosis (SSIGN) score is the most commonly used prognostic model in clear cell renal cell carcinoma (ccRCC) patients. It is a great challenge to preoperatively predict SSIGN score and outcome of ccRCC patients. The aim of this study was to develop and validate a CT-based deep learning radiomics model (DLRM) for predicting SSIGN score and outcome in localized ccRCC. MethodsA multicenter 784 (training cohort/ test 1 cohort / test 2 cohort, 475/204/105) localized ccRCC patients were enrolled. Radiomics signature (RS), deep learning signature (DLS), and DLRM incorporating radiomics and deep learning features were developed for predicting SSIGN score. Model performance was evaluated with area under the receiver operating characteristic curve (AUC). Kaplan-Meier survival analysis was used to assess the association of the model-predicted SSIGN with cancer-specific survival (CSS). Harrell’s concordance index (C-index) was calculated to assess the CSS predictive accuracy of these models. ResultsThe DLRM achieved higher micro-average/macro-average AUCs (0.913/0.850, and 0.969/0.942, respectively in test 1 cohort and test 2 cohort) than the RS and DLS did for the prediction of SSIGN score. The CSS showed significant differences among the DLRM-predicted risk groups. The DLRM achieved higher C-indices (0.827 and 0.824, respectively in test 1 cohort and test 2 cohort) than the RS and DLS did in predicting CSS for localized ccRCC patients. ConclusionThe DLRM can accurately predict the SSIGN score and outcome in localized ccRCC.

Preoperative Inflammation-Associated Blood Cell Markers in Patients with Non-Metastatic Clear Cell Renal Cell Carcinoma: A Retrospective Study.

This study aimed to investigate the association between preoperative inflammation-associated blood cell markers and the prognosis of patients with non-metastatic clear cell renal cell carcinoma (ccRCC) who underwent nephrectomy. We retrospectively analyzed data from our single-center cohort of patients who underwent radical or partial nephrectomy for non-metastatic ccRCC. The optimal cutoff values for red blood cell distribution width (RDW), platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), and lymphocyte-to-monocyte ratio (LMR) were determined using X-tile software. We evaluated recurrence-free survival (RFS), cancer-specific survival (CSS), and overall survival (OS) using the Kaplann-Meier method. Cox proportional-hazards regression models were utilized to assess predictors of RFS, CSS, and OS. The predictive accuracy was evaluated using Harrell's Concordance Index (C-index). A total of 444 patients who underwent nephrectomy were included in the study. The optimal cutoff values for RDW, PLR, NLR, and LMR were determined as 13.1, 157.3, 3.4, and 2.7, respectively. On univariate Cox regression analysis, NLR, PLR, and LMR were significant predictors for RFS, CSS, and OS. After adjusting for important prognostic factors, only NLR remained a significant prognostic marker for both CSS and OS. When NLR was added to the stage, size, grade, and necrosis (SSIGN) model, the C-index increased from 0.777 to 0.826 for CSS and from 0.703 to 0.734 for OS. Similarly, when NLR was added to the University of California, Los Angeles, Integrated Staging System (UISS), the C-index increased from 0.796 to 0.811 for CSS and from 0.735 to 0.745 for OS. NLR is a reliable prognostic biomarker for patients with non-metastatic ccRCC. The prognostic capabilities of UISS and SSIGN models could be improved by adding NLR to UISS and SSIGN models.

Transcriptomic recurrence score improves recurrence prediction for surgically treated patients with intermediate-risk clear cell kidney cancer.

Risk stratification of kidney cancer patients after nephrectomy may tailor surveillance intensity and selection for adjuvant therapy. Transcriptomic approaches are effective in predicting recurrence, but whether they add value to clinicopathologic models remains unclear. Data from patients with clear cell renal cell carcinoma (ccRCC) was downloaded from The Cancer Genome Atlas. Clinicopathologic variables were used to calculate SSIGN (stage, size, grade, and necrosis) scores. The 16 gene recurrence score (RS) signature was generated using RNA-seq data. Transcriptomic risk groups were calculated using the original thresholds. SSIGN groups were divided into low, intermediate, and high risk. Disease-free status was the primary endpoint assessed. SSIGN and RS were calculated for 428 patients with non-metastatic ccRCC. SSIGN low-, intermediate-, and high-risk groups demonstrated 2.7%, 15.2%, and 27.5%, 3-year recurrence risk, respectively. On multivariable analysis, the RS was associated with disease-free status (sub-distribution hazard ratio (sHR) 1.43 per 25 RS [95% CI (1.00-1.43)], p= 0.05). By risk groups, RS further risk stratified the SSIGN intermediate-risk group (sHR 2.22 [95% CI 1.10-4.50], p= 0.03). SSIGN intermediate-risk patients with low and high RS had a 3-year recurrence rate of 8.0% and 25.2%, respectively. Within this risk group, the area under the curve (AUC) at 3 years was 0.69 for SSIGN, 0.74 for RS, and 0.78 for their combination. Transcriptomic recurrence scores improve risk prediction even when controlling for clinicopathologic factors. Utility may be best suited for intermediate-risk patients who have heterogeneous outcomes and further refinement for clinical utility is warranted.

Association between decreased ipsilateral renal function and aggressive behavior in renal cell carcinoma

BackgroundTo assess prognostic value of pre-operative ipsilateral split renal function (SRF) on disease-free survival (DFS) and its association with aggressive pathological features in renal cell carcinoma (RCC) patients. MethodsWe examined patients registered in SNUG-RCC-Nx who underwent partial or radical nephrectomy at Seoul National University Hospital between January 1, 2010 and December 31, 2020. Patients with the following criteria were excluded from the study. 1) non-kidney origin cancer or benign renal tumor, 2) no pre-operative Tc 99 m-DTPA renal scan, 3) single kidney status or previous partial or radical nephrectomy, and 4) bilateral renal mass. Finally, 1,078 patients were included.ResultsAmong 1,078 patients, 899 (83.4%) showed maintained ipsilateral SRF on DTPA renal scan; 179 patients (16.6%) showed decreased SRF. The decreased SRF group showed significantly large tumor size (maintained vs. decreased SRF; 3.31 ± 2.15 vs. 6.85 ± 3.25, p < 0.001), high Fuhrman grade (grade 3–4) (41.7% vs. 55.6%, p < 0.001), and high T stage (T stage 3–4) (9.0% vs. 20.1%, p < 0.001). Pathological invasive features, including invasion of the renal capsule, perirenal fat, renal sinus fat, vein, and collecting duct system, were associated with low SRF of the ipsilateral kidney. Univariate Cox regression analysis identified higher SSIGN (The stage, size, grade, and necrosis) score and decreased ipsilateral SRF as significant risk factors, while multivariate analysis showed SSIGN (5–7) (hazard ratio [HR] 11.9, p < 0.001) and SSIGN (8–10) (HR 69.2, p < 0.001) were significantly associated with shortened DFS, while decreased ipsilateral SRF (HR 1.75, p = 0.065) showed borderline significance. Kaplan–Meier analysis showed that decreased ipsilateral SRF (< 45%) group had shorter DFS than the other group (median DFS: 90.3 months vs. not reached, p < 0.001).ConclusionsAmong unilateral RCC patients, those with low ipsilateral SRF showed poor prognosis with pathologically invasive features. Our novel approach may facilitate risk stratification in RCC patients, helping formulate a treatment strategy.

Predicting Oncologic Outcomes in Small Renal Tumors

BackgroundMost patients diagnosed with renal cancer today present with small renal masses (SRMs). Although these patients have a low risk of dying from their disease and many are followed with active surveillance protocols, a small subset of renal cell carcinomas (RCCs) behave aggressively. Knowledge regarding features of aggressive behavior would enable better adoption of active surveillance strategies among these patients. ObjectiveWe sought to improve prognostic models to predict metastasis-free survival after nephrectomy through focused analyses of clinicopathologic characteristics of SRMs associated with adverse outcomes. Design, setting, and participantsWe identified consecutive patients with surgically resected SRMs (≤4 cm) at the University of Texas Southwestern Kidney Cancer Program between 1998 and 2020. In addition, we evaluated the ability of SRMs to form tumors when implanted in mice, an indicator of tumor aggressiveness. Outcome measurements and statistical analysisWe examined the clinicopathologic factors associated with metastasis including prospectively performed BAP1 immunohistochemistry at our Clinical Laboratory Improvement Amendments laboratory. Multivariable Cox proportional hazard regression was used to predict metastasis-free survival. Results and limitationsA total of 3900 evaluable nephrectomies (from 3674 ethnically diverse patients) were identified, of which 1984 (51%) were SRMs including 1720 RCC. Of these patients with RCC (SRMRCC), 1576 did not have synchronous or metachronous larger RCCs and among these, 37 (2%) developed metastases. SRMRCC that metastasized were significantly enriched for aggressive morphologic phenotypes and engrafted in mice at comparable rates as larger metastatic tumors. BAP1 loss remained significantly associated with metastasis-free survival after accounting for TNM (tumor-node-metastasis) stage and SSIGN (stage, size, grade, and necrosis) score in multivariable analysis. ConclusionsWe identified clinicopathologic features that influence metastasis-free survival for patients with SRMRCC. If validated independently, these data should assist with patient prognosis and help with active surveillance strategies. Patient summaryWe report the identification of features of aggressiveness in small renal tumors that influence the likelihood of metastases after surgery.

Risk of recurrence after nephrectomy: Comparison of predictive ability of validated risk models.

To assess accuracy of University of California Los Angeles Integrated Staging System (UISS), Stage, Size, Grade and Necrosis (SSIGN) score, Leibovich score and GRade, Age, Nodes and Tumor (GRANT) score, the ASSURE (Adjuvant Sunitinib or Sorafenib vs. placebo in resected Unfavorable REnal cell carcinoma) score models and seventh American Joint Committee on Cancer (AJCC)/TNM staging system in predicting recurrence-free survival (RFS) in surgically-treated non-metastatic clear cell renal cell carcinoma (ccRCC) patients. Kaplan-Meier curves and the log-rank test tested RFS according to risk groups among the UISS, SSIGN, Leibovich and GRANT models and the AJCC/TNM system. The Heagerty's C-index for survival tested for discrimination of each model at different time points after nephrectomy. Three hundred and fifty-eight M0 ccRCC patients were included. RFS significantly differed among each risk category for all models (P < 0.001). SSIGN showed the highest c-index over time (from 0.89 at 6-month to 0.82 at 60-month), followed by Leibovich (from 0.89-0.82), AJCC/TNM stage (from 0.82-0.77), ASSURE (from 0.81 to 0.76), GRANT (from 0.83-0.73) and UISS (from 0.76-0.72). For all models, peak discriminatory ability was reached before 12 months. The most prominent decline occurred within 24 months and reaches the lowest discriminatory ability at 60 months. Predictive models, with preference for SSIGN and Leibovich scores, are reliable to predict recurrence after nephrectomy and should be recommended to tailor postoperative surveillance protocols.

Preoperative systemic inflammation response index indicates poor prognosis in patients treated with resection of renal cell carcinoma with inferior vena cava tumor thrombus.

To evaluate the prognostic value of systemic Inflammation Response Index (SIRI) in patients with renal cell carcinoma and inferior vena cava tumor thrombus (RCC-IVCTT) treated with radical nephrectomy and IVCTT thrombectomy. We retrospectively reviewed the clinical data of 144 consecutive patients with RCC-IVCTT who received radical nephrectomy and IVCTT thrombectomy at our center from January 2008 to August 2018. Receiver operating characteristic curve analysis was performed to calculate the optimal cutoff value of preoperative SIRI. Kaplan-Meier analysis was used to compare progression-free survival (PFS) and overall survival (OS). Univariable and multivariable Cox proportional hazard models were constructed to identify the independent prognostic factor for OS and PFS. The Harrell concordance index (C-index) was used to assess whether preoperative SIRI could improve the predictive accuracy of the existent prognostic models including Tumor, Node, Metastasis (TNM) stage model, University of California at Los Angeles Integrated Staging System (UISS) model and Stage, Size, Grade and Necrosis (SSIGN) model. Elevated preoperative SIRI was significantly correlated with clinicopathologic features that are associated with tumor progression. Patients were divided into a high or low SIRI group by the optimal cutoff value of SIRI. Patients in the high SIRI group had longer postoperative hospital stays and lost more blood during surgery. Kaplan Meier curve showed that high SIRI was correlated with decreased OS (P = 0.036) and PFS (P = 0.039) for patients with RCC-IVCTT after surgery. Increased preoperative SIRI was an independently risk factor for decreased OS (P = 0.038) and PFS (P = 0.021). To evaluate PFS, integrating SIRI to each model led to an increased predictive accuracy of 13.2% for TNM staging model (P = 0.007), 14.4% for UISS model (P = 0.000), 12.9% for SSIGN model (P = 0.003). To evaluate OS, integrating SIRI to each model led to an increased predictive accuracy of 13.2% for TNM staging model (P = 0.006), 12.8% for UISS model (P = 0.004), 12.4% for SSIGN model (P = 0.008). Preoperative SIRI serves as an independent predictor of prognosis for patients with RCC-IVCTT after surgery. Adding preoperative SIRI to the established prognostic models enhance their predictive accuracy.

The radiomics-based tumor heterogeneity adds incremental value to the existing prognostic models for predicting outcome in localized clear cell renal cell carcinoma: a multicenter study.

Tumor heterogeneity, which is associated with poor outcomes, has not been exhibited in the University of California, Los Angeles, Integrated Staging System (UISS), and the Stage, Size, Grade and Necrosis (SSIGN) scores. Radiomics allows an in-depth characterization of heterogeneity across the tumor, but its incremental value to the existing prognostic models for clear cell renal cell carcinoma (ccRCC) outcome is unknown. The purpose of this study was to evaluate the association between the radiomics-based tumor heterogeneity and postoperative risk of recurrence in localized ccRCC, and to assess its incremental value to UISS and SSIGN. A multicenter 866 ccRCC patients derived from 12 Chinese hospitals were studied. The endpoint was recurrence-free survival (RFS). A CT-based radiomics signature (RS) was developed and assessed in the whole cohort and in the subgroups stratified by UISS and SSIGN. Two combined nomograms, the R-UISS (combining RS and UISS) and R-SSIGN (combining RS and SSIGN), were developed. The incremental value of RS to UISS and SSIGN in RFS prediction was evaluated. R statistical software was used for statistics. Patients with low radiomics scores were 4.44 times more likely to experience recurrence than those with high radiomics scores (P<0.001). Stratified analysis suggested the association is significant among low- and intermediate-risk patients identified by UISS and SSIGN. The R-UISS and R-SSIGN showed better predictive capability than UISS and SSIGN did with higher C-indices (R-UISS vs. UISS, 0.74 vs. 0.64; R-SSIGN vs. SSIGN, 0.78 vs. 0.76) and higher clinical net benefit. The radiomics-based tumor heterogeneity can predict outcome and add incremental value to the existing prognostic models in localized ccRCC patients. Incorporating radiomics-based tumor heterogeneity in ccRCC prognostic models may provide the opportunity to better surveillance and adjuvant clinical trial design.

Transcriptomic signatures can aid in post-operative risk stratification of clear cell renal cell carcinoma.

383 Background: The ability to risk stratify patient’s post-nephrectomy is critical to select candidates for surveillance and adjuvant therapy. Whether transcriptomic information adds value to current prognostic information is unclear. Methods: Data from confirmed clear cell renal cell carcinoma (ccRCC) used in the TCGA Pan-RCC analysis was downloaded from cBioportal and GDC bioportal. Clinicopathologic variables were used to calculate the integrated staging system, SSIGN (stage, size, grade, and necrosis). The 16 gene recurrence score (RS) signature was generated as described in Rini 2015 using the TCGA data with log TPM normalization. The RS was stratified into high and low risk groups by median. SSIGN was divided into low (0-1) intermediate (2-4) and high ( &gt; = 5) risk groups. RS and SSIGN prognostic significance were evaluated using disease recurrence as an end point, censoring by death. Results: SSIGN and recurrence scores (RS) were calculated for 369 (71.2%) of 518 available TCGA subjects with non-metastatic clear cell renal carcinoma. On multivariable analysis, the RS (continuous variable) was independently associated with disease-free status (HR 1.18 [95%CI (1.02-1.37)], p = 0.031) for each 10 point increase in RS) after adjusting for SSIGN. Categorizing SSIGN into low, intermediate and high-risk groups showed 3.9%, 18.5% and 39.8% 3-year recurrence rates. Stratifying SSIGN risk groups by RS scores we found an RS to further risk stratify the SSIGN intermediate risk group (HR 1.60 [95%CI 1.21-2.12], p &lt; 0.001]). The AUC for at 3 years for SSIGN in the intermediate risk group was 0.68, for RS was 0.74 and the combination was 0.78 (with boot-strapping for optimism adjustment). At 3 years, patients with SSIGN intermediate risk disease (n = 135) with low RS had 3-year recurrence rate of 7.1% compared to 31.0% for those with high RS scores. Conclusions: Transcriptomic recurrence scores can risk stratify intermediate SSIGN clinical risk patients. Patients with intermediate risk disease but a high RS score had poorer outcomes similar to clinically high risk patients. Transcriptomic signatures may add value to existing clinicopathologic variables in ccRCC and clinical implementation is warranted.

Prognostic Impact of Membranous/Nuclear Epidermal Growth Factor Receptor Localization in Clear Cell Renal Cell Carcinoma.

EGFR is overexpressed in the majority of clear cell renal cell carcinomas (CCRCCs). Although EGFR deregulation was found to be of great significance in CCRCC biology, the EGFR overexpression is not associated with EGFR-targeted therapy responsiveness. Moreover, the prognostic role of EGFR expression remains controversial. In the present study, we evaluated the role played by EGFR overexpression in CCRCC and its prognostic significance associated with different immunohistochemical localization patterns. In our study, the Total Score (TS) related to membranous-cytoplasmic EGFR expression showed a significant correlation with grade, pathologic stage (pT), and Stage, Size, Grade, and Necrosis (SSIGN) score, and a negative correlation with nuclear EGFR expression. No significant correlations were shown between nuclear EGFR and clinic-pathological features. Additionally, a correlation between SGLT1 expression levels and pT was described. Multivariate analysis identifies pT and SSIGN score as independent prognostic factors for CCRCC. A significantly increased survival rate was found in the case of positive expression of nuclear EGFR and SGLT1. Based on our findings, SGLT1 and nuclear EGFR overexpression defines a subgroup of CCRCC patients with good prognosis. Membranous-cytoplasmic EGFR expression was shown to be a poor prognostic factor and could define a CCRCC subgroup with poor prognosis that should be responsive to anti-EGFR therapies.

Integrating HECW1 expression into the clinical indicators exhibits high accuracy in assessing the prognosis of patients with clear cell renal cell carcinoma

sBackgroundAlthough many intratumoral biomarkers have been reported to predict clear cell renal cell carcinoma (ccRCC) patient prognosis, combining intratumoral and clinical indicators could predict ccRCC prognosis more accurately than any of these markers alone. This study mainly examined the prognostic value of HECT, C2 and WW domain-containing E3 ubiquitin protein ligase 1 (HECW1) expression in ccRCC patients in combination with established clinical indicators.MethodsThe expression level of HECW1 was screened out by data-independent acquisition mass spectrometry (DIA-MS) and analyzed in ccRCC patients from the The Cancer Genome Atlas (TCGA) database and our cohort. A total of 300 ccRCC patients were stochastically divided into a training cohort and a validation cohort, and real-time PCR, immunohistochemistry (IHC) and statistical analyses were employed to examine the prognostic value of HECW1 in ccRCC patients.ResultsThe expression level of HECW1 usually decreased in human ccRCC specimens relative to control specimens in TCGA (p < 0.001). DIA-MS, Real-time PCR, and IHC analyses also showed that the majority of ccRCCs harbored decreased HECW1 expression compared with that in normal adjacent tissues (p < 0.001). Additionally, HECW1 expression was reduced in ccRCC cell lines compared with the normal renal cell line HK-2 (p < 0.001). Moreover, lower HECW1 expression was found in ccRCC patients with a higher tumor node metastasis (TNM) stage, bone metastasis, or first-line targeted drug resistance (p < 0.001). Low HECW1 expression indicated higher TNM stage, SSIGN (Stage, Size, Grade, and Necrosis) score and WHO/ISUP grade and poor prognosis in ccRCC patients (p < 0.05). Even after multivariable adjustment, HECW1, TNM stage, and SSIGN score served as independent risk factors. The c-index analysis showed that integrating intratumoral HECW1 expression into TNM stage or SSIGN score resulted in a higher c-index value than these indicators alone for predicting ccRCC patient prognosis.ConclusionHECW1 is a novel prognostic biomarker and therapeutic target in ccRCC, and integrating intratumoral HECW1 expression with established clinical indicators yields higher accuracy in assessing the postoperative prognosis of ccRCC patients.

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.

Sarcopenia and modified Glasgow Prognostic Score predict postsurgical outcomes in localized renal cell carcinoma.

Body composition and inflammation are gaining importance for prognostication in cancer. This study investigated the individual and combined utility of the preoperative skeletal muscle index (SMI) and the modified Glasgow Prognostic Score (mGPS) for estimating postoperative outcomes in patients with localized renal cell carcinoma (RCC) undergoing nephrectomy. The authors performed a retrospective review of 352 patients with localized RCC. SMI was measured via computed tomography or magnetic resonance imaging. Patients met the criteria for sarcopenia by body mass index- and sex-stratified thresholds. Multivariable and Kaplan-Meier analyses of associations of sarcopenia and mGPS with overall survival (OS), recurrence-free survival (RFS), and cancer-specific survival (CSS) were performed. Variables were analyzed independently and combined into risk groups: low risk (nonsarcopenic, low mGPS), medium risk (sarcopenia only), medium risk (inflammation only), and high risk (sarcopenic, high mGPS). Receiver operating characteristic (ROC) curves were used to analyze risk groups in comparison with the Stage, Size, Grade, and Necrosis (SSIGN) score and the modified International Metastatic RCC Database Consortium (IMDC) score. The majority of the patients were at stage pT3 (63%), 39.5% of the patients were sarcopenic, and 19.3% had an elevated mGPS at the baseline. The median follow-up time was 30.4 months. Sarcopenia and mGPS were independently associated with worse OS (hazard ratio for sarcopenia, 1.64; P = .006; hazard ratio for mGPS, 1.72; P = .012), CSS, and RFS. Risk groups had an increasing association with worse RFS (P = .015) and CSS (P = .004) but not OS (P = .087). ROC analyses demonstrated a higher area under the curve for risk groups in comparison with the SSIGN and IMDC scores at 5 years. Sarcopenia and an elevated mGPS were associated with worse clinical outcomes in this study of patients with localized RCC. This has implications for preoperative prognostication and treatment decision-making. Kidney cancer is a disease with a wide variety of outcomes. Among patients undergoing surgical removal of the kidney for cancer that has not spread beyond the kidney, many are cured, but some experience recurrence. Physicians are seeking ways to better predict who is at risk for recurrence or death from kidney cancer. This study has evaluated body composition and markers of inflammation before surgery to predict the risk of recurrence or death after surgery. Specifically, low muscle mass and an elevated inflammation score (the modified Glasgow Prognostic Score) have been associated with an increased likelihood of recurrence of kidney cancer and death.

Prognostic role of bland thrombus in patients treated with resection of renal cell carcinoma with inferior vena cava tumor thrombus

ObjectivesTo assess the impact of the presence of bland thrombus (BT) on prognosis of patients treated with resection of renal cell carcinoma (RCC) with inferior vena cava tumor thrombus (IVCTT). Materials and methodsThe medical records of a total of 145 consecutive postsurgical RCC patients with level I-IV IVCTT were reviewed from January 2008 to August 2018. Associations of BT with clinicopathological variables were estimated by chi-square test or Student's t-test. Kaplan-Meier method and multivariate Cox proportional hazard model were used. The eighth TNM staging system, “Spiess PE” model, University of California at Los Angeles Integrated Staging System and Stage, Size, Grade, and Necrosis (SSIGN) score were selected to assess whether BT could improve their predictive abilities. ResultsBT was observed in 34 (23.4%) patients and was significantly associated with increased levels of IVCTT (P = 0.004) and invasion of IVC wall (P = 0.030). Multivariable Cox analyses revealed that tumor grade, T stage, M stage, tumor thrombus consistency and BT were independent risk factors for both progression-free survival and overall survival. The concordance indexes ranged from a low of 0.652 in TNM to a high of 0.731 in SSIGN, and integrating BT into each base model led to an increased predictive accuracies of 6.2% for TNM (P = 0.025), 4.0% for “Spiess PE” model (P = 0.069), 2.1% for University of California at Los Angeles Integrated Staging System (P = 0.149) and 1.2% for SSIGN (P = 0.290), respectively. ConclusionsPresence of BT was independently associated with survival in postsurgical patients with RCC-IVCTT. Routine consideration of BT as an adjunct to TNM staging system may be suggested.

Identification of DNA methylation signatures associated with poor outcome in lower-risk Stage, Size, Grade and Necrosis (SSIGN) score clear cell renal cell cancer

BackgroundDespite using prognostic algorithms and standard surveillance guidelines, 17% of patients initially diagnosed with low risk clear cell renal cell carcinoma (ccRCC) ultimately relapse and die of recurrent disease, indicating additional molecular parameters are needed for improved prognosis.ResultsTo address the gap in ccRCC prognostication in the lower risk population, we performed a genome-wide analysis for methylation signatures capable of distinguishing recurrent and non-recurrent ccRCCs within the subgroup classified as ‘low risk’ by the Mayo Clinic Stage, Size, Grade, and Necrosis score (SSIGN 0–3). This approach revealed that recurrent patients have globally hypermethylated tumors and differ in methylation significantly at 5929 CpGs. Differentially methylated CpGs (DMCpGs) were enriched in regulatory regions and genes modulating cell growth and invasion. A subset of DMCpGs stratified low SSIGN groups into high and low risk of recurrence in independent data sets, indicating that DNA methylation enhances the prognostic power of the SSIGN score.ConclusionsThis study reports a global DNA hypermethylation in tumors of recurrent ccRCC patients. Furthermore, DMCpGs were capable of discriminating between aggressive and less aggressive tumors, in addition to SSIGN score. Therefore, DNA methylation presents itself as a potentially strong biomarker to further improve prognostic power in patients with low risk SSIGN score (0–3).

Preoperative prediction of the stage, size, grade, and necrosis score in clear cell renal cell carcinoma using MRI-based radiomics.

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma. Currently, there is a lack of noninvasive methods to stratify ccRCC prognosis prior to any invasive therapies. The purpose of this study was to preoperatively predict the tumor stage, size, grade, and necrosis (SSIGN) score of ccRCC using MRI-based radiomics. A multicenter cohort of 364 histopathologically confirmed ccRCC patients (272 low [< 4] and 92 high [≥ 4] SSIGN score) with preoperative T2-weighted and T1-contrast-enhanced MRI were retrospectively identified and divided into training (254 patients) and testing sets (110 patients). The performance of a manually optimized radiomics model was assessed by measuring accuracy, sensitivity, specificity, area under receiver operating characteristic curve (AUROC), and area under precision-recall curve (AUPRC) on an independent test set, which was not included in model training. Lastly, its performance was compared to that of a machine learning pipeline, Tree-Based Pipeline Optimization Tool (TPOT). The manually optimized radiomics model using Random Forest classification and Analysis of Variance feature selection methods achieved an AUROC of 0.89, AUPRC of 0.81, accuracy of 0.89 (95% CI 0.816-0.937), specificity of 0.95 (95% CI 0.875-0.984), and sensitivity of 0.72 (95% CI 0.537-0.852) on the test set. The TPOT using Extra Trees Classifier achieved an AUROC of 0.94, AUPRC of 0.83, accuracy of 0.89 (95% CI 0.816-0.937), specificity of 0.95 (95% CI 0.875-0.984), and sensitivity of 0.72 (95% CI 0.537-0.852) on the test set. Preoperative MR radiomics can accurately predict SSIGN score of ccRCC, suggesting its promise as a prognostic tool that can be used in conjunction with diagnostic markers.

Combination of Hematology Indicators and Oncological Characteristics as a New Promising Prognostic Factor in Localized Clear Cell Renal Cell Carcinoma.

PurposeThis study aimed to construct a predictive model for recurrence and metastasis in patients with localized clear cell renal cell carcinoma (ccRCC) based on multiple preoperative blood indexes and oncological characteristics.Patients and MethodsOverall, 442 patients with localized ccRCC between 2013 and 2015 were included. Using least absolute shrinkage and selection operator (LASSO) Cox regression analysis, the top three risk factors from the peripheral blood indicators were screened to construct a risk score, and a prognostic model was established. Harrell’s concordance index (C-index) was applied to evaluate the predictive accuracy of the model for predicting disease-free survival (DFS) in ccRCC.ResultsOut of 38 blood indexes, the top three predictors were fibrinogen (FIB), C-reactive protein (CRP) and neutrophil-lymphocyte ratio (NLR). The FIB-CRP-NLR (FCN) score (hazard ratio [HR]: 1.86, 95% confidence interval [CI]: 1.21–2.9, P = 0.005) was an independent prognostic factor in multivariate analysis. Furthermore, the FIB-CRP-NLR-T-Grade (FCNTG) risk model combining FCN score, T stage and Furhman grade achieved a higher prognostic accuracy (mean C-index, 0.728) than both the FCN score alone (mean C-index, 0.675) and the stage, size, grade, and necrosis (SSIGN) score (mean C-index, 0.686) in the validation cohort.ConclusionThe FCN score combining peripheral blood indicators of inflammation and coagulation is an independent prognostic marker of ccRCC. The FCNTG model, which systemically incorporates preoperative blood indexes to oncological characteristics, shows its advantages of convenience and high prediction efficiency.

SUV39H1 deficiency suppresses clear cell renal cell carcinoma growth by inducing ferroptosis

Clear cell renal cell carcinoma (ccRCC) is a common kidney malignancy characterized by a poor prognosis. Suppressor of variegation 3–9 homolog 1 (SUV39H1), which encodes a histone H3 lysine 9 methyltransferase, has been reported to act as an oncogene in many cancers. However, it is unclear whether SUV39H1 is involved in ccRCC. Here, we report that SUV39H1 expression is frequently upregulated in ccRCC tumors and is significantly correlated with ccRCC progression. SUV39H1 expression level is an independent risk factor for cancer prognosis, and integration with several known prognostic factors predicted ccRCC patient prognosis with improved accuracy than the conventional SSIGN (stage, size, grade and necrosis) prognostic model. Mechanistically, we discovered that siRNA knockdown or pharmacological inhibition of SUV39H1 induced iron accumulation and lipid peroxidation, leading to ferroptosis that disrupted ccRCC cell growth in vitro and in vivo. We also show that SUV39H1 deficiency modulated the H3K9me3 status of the DPP4 (dipeptidyl-peptidase-4) gene promoter, resulting in upregulation of its expression that contributes to ferroptosis. Taken together, our findings provide the mechanistic insight into SUV39H1-dependent epigenetic control of ccRCC tumor growth and indicate that SUV39H1 may serve as a potential therapeutic target for ccRCC treatment.