scholarly journals MR texture analysis in differentiating renal cell carcinoma from lipid-poor angiomyolipoma and oncocytoma

2020 ◽  
Vol 93 (1114) ◽  
pp. 20200569
Author(s):  
Abdul Razik ◽  
Ankur Goyal ◽  
Raju Sharma ◽  
Devasenathipathy Kandasamy ◽  
Amlesh Seth ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Texture Analysis ◽  
Renal Cell ◽  
Roc Curve Analysis ◽  
Class Separation ◽  
Texture Parameters ◽  
Polygonal Region ◽  
Significant Difference ◽  
Separation Capacity

Objectives: To assess the utility of magnetic resonance texture analysis (MRTA) in differentiating renal cell carcinoma (RCC) from lipid-poor angiomyolipoma (lpAML) and oncocytoma. Methods: After ethical approval, 42 patients with 54 masses (34 RCC, 14 lpAML and six oncocytomas) who underwent MRI on a 1.5 T scanner (Avanto, Siemens, Erlangen, Germany) between January 2011 and December 2012 were retrospectively included in the study. MRTA was performed on the TexRAD research software (Feedback Plc., Cambridge, UK) using free-hand polygonal region of interest (ROI) drawn on the maximum cross-sectional area of the tumor to generate six first-order statistical parameters. The Mann-Whitney U test was used to look for any statically significant difference. The receiver operating characteristic (ROC) curve analysis was done to select the parameter with the highest class separation capacity [area under the curve (AUC)] for each MRI sequence. Results: Several texture parameters on MRI showed high-class separation capacity (AUC > 0.8) in differentiating RCC from lpAML and oncocytoma. The best performing parameter in differentiating RCC from lpAML was mean of positive pixels (MPP) at SSF 2 (AUC: 0.891) on DWI b500. In differentiating RCC from oncocytoma, the best parameter was mean at SSF 0 (AUC: 0.935) on DWI b1000. Conclusions: MRTA could potentially serve as a useful non-invasive tool for differentiating RCC from lpAML and oncocytoma. Advances in knowledge: There is limited literature addressing the role of MRTA in differentiating RCC from lpAML and oncocytoma. Our study demonstrated several texture parameters which were useful in this regard.

scholarly journals A novel prognostic cancer-related lncRNA signature in papillary renal cell carcinoma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Binghai Chen ◽  
Di Dong ◽  
Qin Yao ◽  
Yuanzhang Zou ◽  
Wei Hu
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
High Efficiency ◽  
Risk Model ◽  
Cox Regression ◽  
Papillary Renal Cell Carcinoma ◽  
Clinical Feature ◽  
Roc Curve Analysis ◽  
Significant Difference

Abstract Background Papillary renal cell carcinoma (pRCC) ranks second in renal cell carcinoma and the prognosis of pRCC remains poor. Here, we aimed to screen and identify a novel prognostic cancer-related lncRNA signature in pRCC. Methods The RNA-seq profile and clinical feature of pRCC cases were downloaded from TCGA database. Significant cancer-related lncRNAs were obtained from the Immlnc database. Differentially expressed cancer-related lncRNAs (DECRLs) in pRCC were screened for further analysis. Cox regression report was implemented to identify prognostic cancer-related lncRNAs and establish a prognostic risk model, and ROC curve analysis was used to evaluate its precision. The correlation between RP11-63A11.1 and clinical characteristics was further analyzed. Finally, the expression level and role of RP11-63A11.1 were studied in vitro. Results A total of 367 DECRLs were finally screened and 26 prognostic cancer-related lncRNAs were identified. Among them, ten lncRNAs (RP11-573D15.8, LINC01317, RNF144A-AS1, TFAP2A-AS1, LINC00702, GAS6-AS1, RP11-400K9.4, LUCAT1, RP11-63A11.1, and RP11-156L14.1) were independently associated with prognosis of pRCC. These ten lncRNAs were incorporated into a prognostic risk model. In accordance with the median value of the riskscore, pRCC cases were separated into high and low risk groups. Survival analysis indicated that there was a significant difference on overall survival (OS) rate between the two groups. The area under curve (AUC) in different years indicated that the model was of high efficiency in prognosis prediction. RP11-63A11.1 was mainly expressed in renal tissues and it correlated with the tumor stage, T, M, N classifications, OS, PFS, and DSS of pRCC patients. Consistent with the expression in pRCC tissue samples, RP11-63A11.1 was also down-regulated in pRCC cells. More importantly, up-regulation of RP11-63A11.1 attenuated cell survival and induced apoptosis. Conclusions Ten cancer-related lncRNAs were incorporated into a powerful model for prognosis evaluation. RP11-63A11.1 functioned as a cancer suppressor in pRCC and it might be a potential therapeutic target for treating pRCC.

scholarly journals A Novel Prognostic Cancer-related lncRNA Signature in Papillary Renal Cell Carcinoma

2021 ◽  
Author(s):  
Binghai Chen ◽  
Di Dong ◽  
Qin Yao ◽  
Yuanzhang Zou ◽  
Wei Hu
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
High Efficiency ◽  
Risk Model ◽  
Cox Regression ◽  
Clinical Feature ◽  
Roc Curve Analysis ◽  
Significant Difference

Abstract BackgroundPapillary renal cell carcinoma (pRCC) ranks second in renal cell carcinoma and the prognosis of pRCC remains poor. Here, we aimed to screen and identify a novel prognostic cancer-related lncRNA signature in pRCC. MethodsThe RNA-seq profile and clinical feature of pRCC cases were downloaded from TCGA database. Significant cancer-related lncRNAs were obtained from the Immlnc database. Differentially expressed cancer-related lncRNAs (DECRLs) in pRCC were screened for further analysis. Cox regression report was implemented to identify prognostic cancer-related lncRNAs and establish a prognostic risk model, and ROC curve analysis was used to evaluate its precision. The correlation between RP11-63A11.1 and clinical characteristics was further analyzed. Finally, the expression level and role of RP11-63A11.1 were studied in vitro. ResultsA total of 367 DECRLs were finally screened and 26 prognostic cancer-related lncRNAs were identified. Among them, ten lncRNAs (RP11-573D15.8, LINC01317, RNF144A-AS1, TFAP2A-AS1, LINC00702, GAS6-AS1, RP11-400K9.4, LUCAT1, RP11-63A11.1, and RP11-156L14.1) were independently connected with prognosis of pRCC. These ten lncRNAs were incorporated into a prognostic risk model. In accordance with the median value of the riskscore, pRCC cases were separated into high and low risk groups. Survival analysis indicated that there was a significant difference on overall survival (OS) rate between the two groups. The area under curve (AUC) in different years indicated that the model was of high efficiency in prognosis prediction. RP11-63A11.1 was mainly expressed in renal tissues and it correlated with the tumor stage, T, M, N classifications, OS, PFS, and DSS of pRCC patients. Consistent with the expression in pRCC tissue samples, RP11-63A11.1 was also downregulated in pRCC cells. More importantly, upregulation of RP11-63A11.1 attenuated cell survival and induced apoptosis. ConclusionsTen cancer-related lncRNAs were incorporated into a powerful model for prognosis evaluation. RP11-63A11.1 functioned as a cancer suppressor in pRCC and it might be a potential therapeutic target for treating pRCC.

scholarly journals Prognostic Value of Plasma hPG80 (Circulating Progastrin) in Metastatic Renal Cell Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 375
Author(s):  
Manish Kohli ◽  
Winston Tan ◽  
Bérengère Vire ◽  
Pierre Liaud ◽  
Mélina Blairvacq ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Prognostic Value ◽  
Risk Model ◽  
Predictive Accuracy ◽  
Area Under The Curve ◽  
Risk Groups ◽  
Prognostic Impact ◽  
Significant Difference

Precise management of kidney cancer requires the identification of prognostic factors. hPG80 (circulating progastrin) is a tumor promoting peptide present in the blood of patients with various cancers, including renal cell carcinoma (RCC). In this study, we evaluated the prognostic value of plasma hPG80 in 143 prospectively collected patients with metastatic RCC (mRCC). The prognostic impact of hPG80 levels on overall survival (OS) in mRCC patients after controlling for hPG80 levels in non-cancer age matched controls was determined and compared to the International Metastatic Database Consortium (IMDC) risk model (good, intermediate, poor). ROC curves were used to evaluate the diagnostic accuracy of hPG80 using the area under the curve (AUC). Our results showed that plasma hPG80 was detected in 94% of mRCC patients. hPG80 levels displayed high predictive accuracy with an AUC of 0.93 and 0.84 when compared to 18–25 year old controls and 50–80 year old controls, respectively. mRCC patients with high hPG80 levels (>4.5 pM) had significantly lower OS compared to patients with low hPG80 levels (<4.5 pM) (12 versus 31.2 months, respectively; p = 0.0031). Adding hPG80 levels (score of 1 for patients having hPG80 levels > 4.5 pM) to the six variables of the IMDC risk model showed a greater and significant difference in OS between the newly defined good-, intermediate- and poor-risk groups (p = 0.0003 compared to p = 0.0076). Finally, when patients with IMDC intermediate-risk group were further divided into two groups based on hPG80 levels within these subgroups, increased OS were observed in patients with low hPG80 levels (<4.5 pM). In conclusion, our data suggest that hPG80 could be used for prognosticating survival in mRCC alone or integrated to the IMDC score (by adding a variable to the IMDC score or by substratifying the IMDC risk groups), be a prognostic biomarker in mRCC patients.

Can Quantitative CT Texture Analysis be Used to Differentiate Fat-poor Renal Angiomyolipoma from Renal Cell Carcinoma on Unenhanced CT Images?

Radiology ◽  
2015 ◽  
Vol 276 (3) ◽  
pp. 787-796 ◽  
Author(s):  
Taryn Hodgdon ◽  
Matthew D. F. McInnes ◽  
Nicola Schieda ◽  
Trevor A. Flood ◽  
Leslie Lamb ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Texture Analysis ◽  
Renal Cell ◽  
Ct Images ◽  
Renal Angiomyolipoma ◽  
Quantitative Ct ◽  
Unenhanced Ct ◽  
Ct Texture Analysis

Comparison of First-line Pazopanib and Sunitinib in Metastatic Renal Cell Carcinoma: Experiences of the Urologic Cancer Centre for Research and Innovation

2019 ◽  
Author(s):  
Emily C.L. Wong ◽  
Camilla Tajzler ◽  
Gaurav Vasisth ◽  
Amanda Zhu ◽  
Mathilda Chow ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Side Effects ◽  
Cell Carcinoma ◽  
Disease Progression ◽  
Metastatic Renal Cell Carcinoma ◽  
Renal Cell ◽  
First Line ◽  
First Line Therapy ◽  
Line Therapy ◽  
Significant Difference

Abstract Background: Sunitinib and pazopanib are orally-administered tyrosine kinase receptor inhibitors (TKIs) approved as first-line therapy for the treatment of metastatic renal cell carcinoma (mRCC). The IMDC criteria are a predictive prognostic model for patients with mRCC when stratified into three prognosis groups: favourable, intermediate and poor. We retrospectively compared the efficacy and safety of sunitinib and pazopanib as first-line therapy for patients with mRCC in our single institution database. Methods: Retrospective analysis was done to compare progression-free survival (PFS) and side effects of sunitinib and pazopanib as first-line therapy in patients with mRCC. Patients were stratified into prognosis groups according to IMDC criteria. Disease assessment was performed on measurable aspects of disease based on computed tomography or magnetic resonance imaging reports. Survival analysis was performed using the Kaplan-Meier method and Cox regression, with disease progression as the endpoint.Results: Data was obtained from 228 patients with mRCC who were treated with either pazopanib (n=57) or sunitinib (n=171). No significant difference in PFS was found between sunitinib and pazopanib (HR for disease progression or all-cause death, 1.10; 95%CI: 0.76-1.57, p=0.62). Median PFS time for patients receiving sunitinib was 9.4 months and for pazopanib, 8.5 months. Median PFS for patients with intermediate-risk disease was similar between groups (9.4 months vs. 9.2 months, respectively, p=0.93). However, patients treated with sunitinib experienced a greater number of side effects compared to pazopanib. Conclusions: Sunitinib and pazopanib are similarly efficacious as first-line therapy for mRCC. However, adverse events are lower with pazopanib.

scholarly journals Contrast-Enhanced CT Texture Analysis for Distinguishing Fat-Poor Renal Angiomyolipoma From Chromophobe Renal Cell Carcinoma

2019 ◽  
Vol 18 ◽  
pp. 153601211988316 ◽  
Author(s):  
Guangjie Yang ◽  
Aidi Gong ◽  
Pei Nie ◽  
Lei Yan ◽  
Wenjie Miao ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Texture Analysis ◽  
Renal Cell ◽  
Texture Features ◽  
Regions Of Interest ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
2D And 3D

Objective: To evaluate the value of 2-dimensional (2D) and 3-dimensional (3D) computed tomography texture analysis (CTTA) models in distinguishing fat-poor angiomyolipoma (fpAML) from chromophobe renal cell carcinoma (chRCC). Methods: We retrospectively enrolled 32 fpAMLs and 24 chRCCs. Texture features were extracted from 2D and 3D regions of interest in triphasic CT images. The 2D and 3D CTTA models were constructed with the least absolute shrinkage and selection operator algorithm and texture scores were calculated. The diagnostic performance of the 2D and 3D CTTA models was evaluated with respect to calibration, discrimination, and clinical usefulness. Results: Of the 177 and 183 texture features extracted from 2D and 3D regions of interest, respectively, 5 2D features and 8 3D features were selected to build 2D and 3D CTTA models. The 2D CTTA model (area under the curve [AUC], 0.811; 95% confidence interval [CI], 0.695-0.927) and the 3D CTTA model (AUC, 0.915; 95% CI, 0.838-0.993) showed good discrimination and calibration ( P > .05). There was no significant difference in AUC between the 2 models ( P = .093). Decision curve analysis showed the 3D model outperformed the 2D model in terms of clinical usefulness. Conclusions: The CTTA models based on contrast-enhanced CT images had a high value in differentiating fpAML from chRCC.

CT texture analysis in the differentiation of major renal cell carcinoma subtypes and correlation with Fuhrman grade

2019 ◽  
Vol 29 (12) ◽  
pp. 6922-6929 ◽  
Author(s):  
Yu Deng ◽  
Erik Soule ◽  
Aster Samuel ◽  
Sakhi Shah ◽  
Enming Cui ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Texture Analysis ◽  
Renal Cell ◽  
Fuhrman Grade ◽  
Ct Texture Analysis

Differentiation of Papillary Renal Cell Carcinoma Subtypes on MRI: Qualitative and Texture Analysis

2018 ◽  
Vol 211 (6) ◽  
pp. 1234-1245 ◽  
Author(s):  
Camila Lopes Vendrami ◽  
Yuri S. Velichko ◽  
Frank H. Miller ◽  
Argha Chatterjee ◽  
Carolina Parada Villavicencio ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Texture Analysis ◽  
Renal Cell ◽  
Papillary Renal Cell Carcinoma

scholarly journals European Medicines Agency extension of indication to include the combination immunotherapy cancer drug treatment with nivolumab (Opdivo) and ipilimumab (Yervoy) for adults with intermediate/poor-risk advanced renal cell carcinoma

ESMO Open ◽  
2020 ◽  
Vol 5 (6) ◽  
pp. e000798
Author(s):  
Sahra Ali ◽  
Jorge Camarero ◽  
Paula van Hennik ◽  
Bjorg Bolstad ◽  
Maja Sommerfelt Grønvold ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Phase Iii ◽  
Advanced Renal Cell Carcinoma ◽  
Cancer Drug ◽  
European Medicines Agency ◽  
Poor Risk ◽  
Significant Difference ◽  
Risk Patients

On the 15 November 2018, the Committee for Medicinal Products for Human Use adopted an extension to an existing indication for the use of nivolumab (Opdivo) in combination with ipilimumab (Yervoy) for the first-line treatment of adult patients with intermediate/poor-risk advanced renal cell carcinoma (RCC). The approval was based on results from the Pivotal CA209214 study, a randomised, open-label, phase III study, comparing nivolumab +ipilimumab with sunitinib in subjects≥18 years of age with previously untreated advanced RCC (not amenable for surgery or radiotherapy) or metastatic RCC, with a clear-cell component. A total of 1096 patients were randomised in the trial, of which 847 patients had intermediate/poor-risk RCC and received either nivolumab (n=425) in combination with ipilimumab administered every 3 weeks for 4 doses followed by nivolumab monotherapy 3 mg/kg every 2 weeks or sunitinib (n=422) administered orally for 4 weeks followed by 2 weeks off, every cycle. A statistically significant difference in overall survival (OS) was observed in the nivolumab + ipilimumab group compared with the sunitinib group in intermediate/poor-risk subjects (HR 0.63 (99.8% CI 0.44 to 0.89); stratified log-rank 2-sided p-value<0.0001). The median OS was not reached for the nivolumab + ipilimumab group and was 25.95 months for the sunitinib group. The OS rates were 89.5% and 86.2% at 6 months, and 80.1% and 72.1% at 12 months in the nivolumab +ipilimumab and the sunitinib groups, respectively. K-M curves separated after approximately 3 months, favouring nivolumab + ipilimumab. This was not mirrored in the favourable-risk patients where no statistically significant difference was observed between nivolumab + ipilimumab and sunitinib in favourable-risk patients (HR 1.45 (descriptive 99.8% CI 0.51 to 4.12), p =0.2715).

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