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Oncocytomas are referred to as benign kidney neoplasms. They primarily affect adults, with patients over 70 years old being the most affected. Renal oncocytomas (ROs) are frequently detected by excision, biopsy, or scan. Hematuria, flank pain, and a palpable mass are the traditional trio of symptoms. Oncocytomas appear as well-circumscribed, tan or mahogany-coloured masses with a central scar that is stellate. Histological features include well-circumscribed lesions, bland cytology, eosinophilic cytoplasm, regular nuclei with prominent central nucleoli, and nested architecture. ROs are rarely linked to an aggressive clinical course and have an excellent prognosis. There is proof that the disease can spread to the liver and bones. Some literature has also reported oncocytoma metastases to the lung and liver. This systematic review of the literature examines and evaluates the malignant potential of oncocytoma. The purpose of the study was to determine whether ROs can be diagnosed as a benign condition or if malignancy needs to be considered and investigated. Seventeen studies were analysed which had a total of 412 ROs. Four patients (one percent) died as a result of their illness. There was evidence of disease progression in every patient who passed away from their illness. Six patients (1.5%) experienced disease progression in total. Three hundred and seventeen patients (80%) underwent radical nephrectomy, while 81 patients (20%) underwent partial nephrectomy. Liver, bone, lung, lymphadenopathy, and local recurrence were among the metastasis sites. Perinephric fat invasion, renal sinus fat invasion, renal capsular invasion, and vascular invasion are characteristics of metastatic behavior that have been found. Despite this, the small number of patients who experienced disease progression and/or death as a result of ROs implies that aggressive malignant behavior is not always correlated with the presence of metastatic features or disease. Oncocytomas should be viewed as having a low potential for malignancy rather than as benign. Individuals who exhibit aggressive characteristics, such as vascular invasion and/or perinephric fat invasion, have an atypically good prognosis. Despite advancements in imaging and immunochemical techniques, it is indisputable that ROs, which were first classified as renal tumours in 1976, continue to pose a diagnostic challenge for multidisciplinary teams. There is considerable variation in practice across the globe due to difficulties in confirming ROs, especially when it comes to metastatic disease. There is even more variation in the management of follow-up care that follows. This will remain the MDT's current state until randomised controlled trials, long-term results, and a better comprehension of the behavior of this tumour are obtained., Competing Interests: Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Rajagopal et al.)

Objectives: To investigate different radiomics models based on single phase and the different phase combinations of radiomics features from 3D tri-phasic CT to distinguish RO from chRCC., Methods: A total of 96 patients (30 RO and 66 chRCC) were enrolled in this study. Radiomics features were extracted from unenhanced phase (UP), corticomedullary phase (CMP), and nephrographic phase (NP) CT images. Feature selection was based on the least absolute shrinkage and selection operator regression (LASSO) method. The selected features were used to develop different radiomics models using logistic regression (LR) analysis, including model 1 (UP), model 2(CMP), model 3(NP), model 4(UP+CMP), model 5(UP+NP), model 6(CMP+NP), and model 7(UP+CMP+NP). The radiomics model demonstrating the highest discrimination performance was utilized to construct the combined model (model 8) with clinical factors. A nomogram based on the model 8 was established. To evaluate the diagnostic performance of the different models, the receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used. Delong's test was utilized to assess the statistical significance of the AUC improvement across the models., Results: Among the seven radiomics models, model 7 exhibited the highest AUC of 0.84 (95% CI 0.69, 0.99), and model 7 demonstrated a significantly superior AUC compared to the other radiomics models (all P < 0.05). The AUC values of radiomics models based on two phases (model4, mode5, mode6) were greater than the models based on single phase (model1, mode2, mode3) (all P < 0.05). Model 3 illustrated the best performance of the three radiomics models based on single phase with an AUC of 0.76 (95% CI 0.57, 099). Model 6 illustrated the best performance of the three radiomics models based on two-phases combination with an AUC of 0.83 (0.66, 0.99). Model 8 achieved an AUC of 0.93 (95% CI 0.83, 1.00) which is higher than those all radiomics models., Conclusion: Radiomics models based on combination of radiomics features from UP, CMP, and NP can be a useful and promising technique to differentiate RO from chRCC. Moreover, the model combining clinical factors and radiomics features showed better classification performance to distinguish them., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: This study investigates the proteomic landscapes of chromophobe renal cell carcinoma (chRCC) and renal oncocytomas (RO), two subtypes of renal cell carcinoma that together account for approximately 10% of all renal tumors. Despite their histological similarities and shared origins, chRCC is a malignant tumor necessitating aggressive intervention, while RO, a benign growth, is often subject to overtreatment due to difficulties in accurate differentiation., Methods: We conducted a label-free quantitative proteomic analysis on solid biopsies of chRCC (n = 5), RO (n = 5), and normal adjacent tissue (NAT, n = 5). The quantitative analysis was carried out by comparing protein abundances between tumor and NAT specimens. Our analysis identified a total of 1610 proteins across all samples, with 1379 (85.7%) of these proteins quantified in at least seven out of ten LC‒MS/MS runs for one renal tissue type (chRCC, RO, or NAT)., Results: Our findings revealed significant similarities in the dysregulation of key metabolic pathways, including carbohydrate, lipid, and amino acid metabolism, in both chRCC and RO. Compared to NAT, both chRCC and RO showed a marked downregulation in gluconeogenesis proteins, but a significant upregulation of proteins integral to the citrate cycle. Interestingly, we observed a distinct divergence in the oxidative phosphorylation pathway, with RO showing a significant increase in the number and degree of alterations in proteins, surpassing that observed in chRCC., Conclusions: This study underscores the value of integrating high-resolution mass spectrometry protein quantification to effectively characterize and differentiate the proteomic landscapes of solid tumor biopsies diagnosed as chRCC and RO. The insights gained from this research offer valuable information for enhancing our understanding of these conditions and may aid in the development of improved diagnostic and therapeutic strategies., (© 2023. The Author(s).)

The increasing evidence of oncocytic renal tumors positive in 99m Tc Sestamibi Single Photon Emission Tomography/Computed Tomography (SPECT/CT) examination calls for the development of diagnostic tools to differentiate these tumors from more aggressive forms. This study combined radiomics analysis with the uptake of 99m Tc Sestamibi on SPECT/CT to differentiate benign renal oncocytic neoplasms from renal cell carcinoma. A total of 57 renal tumors were prospectively collected. Histopathological analysis and radiomics data extraction were performed. XGBoost classifiers were trained using the radiomics features alone and combined with the results from the visual evaluation of 99m Tc Sestamibi SPECT/CT examination. The combined SPECT/radiomics model achieved higher accuracy (95%) with an area under the curve (AUC) of 98.3% (95% CI 93.7-100%) than the radiomics-only model (71.67%) with an AUC of 75% (95% CI 49.7-100%) and visual evaluation of 99m Tc Sestamibi SPECT/CT alone (90.8%) with an AUC of 90.8% (95%CI 82.5-99.1%). The positive predictive values of SPECT/radiomics, radiomics-only, and 99m Tc Sestamibi SPECT/CT-only models were 100%, 85.71%, and 85%, respectively, whereas the negative predictive values were 85.71%, 55.56%, and 94.6%, respectively. Feature importance analysis revealed that 99m Tc Sestamibi uptake was the most influential attribute in the combined model. This study highlights the potential of combining radiomics analysis with 99m Tc Sestamibi SPECT/CT to improve the preoperative characterization of benign renal oncocytic neoplasms. The proposed SPECT/radiomics classifier outperformed the visual evaluation of 99m Tc Sestamibii SPECT/CT and the radiomics-only model, demonstrating that the integration of 99m Tc Sestamibi SPECT/CT and radiomics data provides improved diagnostic performance, with minimal false positive and false negative results.

Introduction and Objective: To evaluate whether significant loss in ipsilateral renal parenchymal volume (IRPV) and renal function occurs during active surveillance (AS) of renal oncocytoma (RO) patients., Methods: Renal function (estimated glomerular filtration rate, eGFR) dynamics were retrospectively analyzed in 32 consecutive biopsy-diagnosed RO patients managed with AS at a National Comprehensive Cancer Network institute. Three-dimensional kidney and tumor reconstructions were generated and IRPV was calculated using volumetry software (Myrian®) for all patients with manually estimated RO growth >+10 cm 3 . GFR and IRPV were compared at AS initiation vs. the last follow-up using 2-sided paired t-tests. The correlation between change in IRPV and change in RO size or GFR was tested using a Spearman coefficient., Results: With median follow-up of 37 months, there was no significant change between initial vs. last eGFR (median 71.0 vs. 70.5 ml/min/1.73 m 2 , P = 0.50; median change -3.0 ml/min/1.73 m 2 ). Among patients (n = 17) with RO growth >+10 cm 3 during AS (median growth +28.6 cm 3 , IQR +16.9- + 46.5 cm 3 ), IRPV generally remained stable (median change +0.5%, IQR -1.2%- + 1.2%), with only 2 cases surpassing 5% loss. No IRPV loss was detected among any patient within the top tertile of RO growth magnitude. RO growth magnitude did not correlate with loss of either IRPV (ρ = -0.30, P = 0.24) or eGFR (ρ = -0.16, P = 0.40), including among patient subsets with lower initial eGFR. Study limitations include a lack of long-term follow-up., Conclusions: Volumetry is a promising novel tool to measure kidney and tumor tissue changes during AS. Our study using volumetry indicates that clinically significant loss of IRPV or eGFR is uncommon and unrelated to tumor growth among untreated RO patients with intermediate follow-up. These findings support that AS is in general functionally safe for RO patients, however longer study is needed to determine safety durability, particularly among uncommon ≥cT2 RO variants., Competing Interests: Conflict of interest The authors report no potential conflicts of interest relevant to this study., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Background: Benign renal tumors, such as renal oncocytoma (RO), can be erroneously diagnosed as malignant renal cell carcinomas (RCC), because of their similar imaging features. Computer-aided systems leveraging radiomic features can be used to better discriminate benign renal tumors from the malignant ones. The purpose of this work was to build a machine learning model to distinguish RO from clear cell RCC (ccRCC)., Method: We collected CT images of 77 patients, with 30 cases of RO (39%) and 47 cases of ccRCC (61%). Radiomic features were extracted both from the tumor volumes identified by the clinicians and from the tumor's zone of transition (ZOT). We used a genetic algorithm to perform feature selection, identifying the most descriptive set of features for the tumor classification. We built a decision tree classifier to distinguish between ROs and ccRCCs. We proposed two versions of the pipeline: in the first one, the feature selection was performed before the splitting of the data, while in the second one, the feature selection was performed after, i.e., on the training data only. We evaluated the efficiency of the two pipelines in cancer classification., Results: The ZOT features were found to be the most predictive by the genetic algorithm. The pipeline with the feature selection performed on the whole dataset obtained an average ROC AUC score of 0.87 ± 0.09. The second pipeline, in which the feature selection was performed on the training data only, obtained an average ROC AUC score of 0.62 ± 0.17., Conclusions: The obtained results confirm the efficiency of ZOT radiomic features in capturing the renal tumor characteristics. We showed that there is a significant difference in the performances of the two proposed pipelines, highlighting how some already published radiomic analyses could be too optimistic about the real generalization capabilities of the models.

Artificial intelligence (AI)-based techniques are increasingly being explored as an emerging ancillary technique for improving accuracy and reproducibility of histopathological diagnosis. Renal cell carcinoma (RCC) is a malignancy responsible for 2% of cancer deaths worldwide. Given that RCC is a heterogenous disease, accurate histopathological classification is essential to separate aggressive subtypes from indolent ones and benign mimickers. There are early promising results using AI for RCC classification to distinguish between 2 and 3 subtypes of RCC. However, it is not clear how an AI-based model designed for multiple subtypes of RCCs, and benign mimickers would perform which is a scenario closer to the real practice of pathology. A computational model was created using 252 whole slide images (WSI) (clear cell RCC: 56, papillary RCC: 81, chromophobe RCC: 51, clear cell papillary RCC: 39, and, metanephric adenoma: 6). 298,071 patches were used to develop the AI-based image classifier. 298,071 patches (350 × 350-pixel) were used to develop the AI-based image classifier. The model was applied to a secondary dataset and demonstrated that 47/55 (85%) WSIs were correctly classified. This computational model showed excellent results except to distinguish clear cell RCC from clear cell papillary RCC. Further validation using multi-institutional large datasets and prospective studies are needed to determine the potential to translation to clinical practice., (© 2023 The Authors.)

Background: Correct tumor subtyping of primary renal tumors is essential for treatment decision in daily routine. Most of the tumors can be classified based on morphology alone. Nevertheless, some diagnoses are difficult, and further investigations are needed for correct tumor subtyping. Besides histochemical investigations, high-mass-resolution matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can detect new diagnostic biomarkers and hence improve the diagnostic., Patients and Methods: Formalin-fixed paraffin embedded tissue specimens from clear cell renal cell carcinoma (ccRCC, n = 552), papillary renal cell carcinoma (pRCC, n = 122), chromophobe renal cell carcinoma (chRCC, n = 108), and renal oncocytoma (rO, n = 71) were analyzed by high-mass-resolution MALDI fourier-transform ion cyclotron resonance (FT-ICR) MSI. The SPACiAL pipeline was executed for automated co-registration of histological and molecular features. Pathway enrichment and pathway topology analysis were performed to determine significant differences between RCC subtypes., Results: We discriminated the four histological subtypes (ccRCC, pRCC, chRCC, and rO) and established the subtype-specific pathways and metabolic profiles. rO showed an enrichment of pentose phosphate, taurine and hypotaurine, glycerophospholipid, amino sugar and nucleotide sugar, fructose and mannose, glycine, serine, and threonine pathways. ChRCC is defined by enriched pathways including the amino sugar and nucleotide sugar, fructose and mannose, glycerophospholipid, taurine and hypotaurine, glycine, serine, and threonine pathways. Pyrimidine, amino sugar and nucleotide sugar, glycerophospholipids, and glutathione pathways are enriched in ccRCC. Furthermore, we detected enriched phosphatidylinositol and glycerophospholipid pathways in pRCC., Conclusion: In summary, we performed a classification system with a mean accuracy in tumor discrimination of 85.13%. Furthermore, we detected tumor-specific biomarkers for the four most common primary renal tumors by MALDI-MSI. This method is a useful tool in differential diagnosis and biomarker detection., (© 2022 S. Karger AG, Basel.)

Background: 99m Tc-Sestamibi Single Photon Emission Computed Tomography/Computed Tomography (SPECT/CT) contributes to the non-invasive differentiation of renal oncocytoma (RO) from renal cell carcinoma (RCC) by characterising renal tumours as Sestamibi positive or Sestamibi negative regarding their 99m Tc-Sestamibi uptake compared to the non-tumoral renal parenchyma., Purpose: To determine whether 99m Tc- Sestamibi uptake in renal tumour and the non-tumoral renal parenchyma measured using Standard Uptake Value (SUV) SPECT, has a beneficial role in differentiating RO from RCC., Material and Methods: Fifty-seven renal tumours from 52 patients were evaluated. In addition to visual evaluation of 99m Tc-Sestamibi uptake, SUV max measurements were performed in the renal tumour and the ipsilateral non-tumoral renal parenchyma. Analysis of the area under the receiver operating characteristic curve identified an optimal cut-off value for detecting RO, based on the relative ratio of 99m Tc- Sestamibi uptake., Results: Semiquantitative evaluation of 99m Tc-Sestamibi uptake did not improve the performance of 99m Tc- Sestamibi SPECT/CT in detecting RO. 99m Tc- Sestamibi SPECT/CT identifies a group of mostly indolent Sestamibi-positive tumours with low malignant potential containing RO, Low-Grade Oncocytic Tumours, Hybrid Oncocytic Tumours, and a subset of chromophobe RCCs., Conclusion: The imaging limitations for accurate differentiation of Sestamibi-positive renal tumours mirror the recognised diagnostic complexities of the histopathologic evaluation of oncocytic neoplasia. Patients with Sestamibi-positive renal tumours could be better suited for biopsy and follow-up, according to the current active surveillance protocols.

Renal tumors with oncocytic or chromophobe-like morphology can be a common source of diagnostic difficulty. In some series, they constitute the largest group of unclassified renal cell carcinomas, a term used for neoplasms that do not fit the current classification of renal tumors. We describe the histological, immunohistochemical, and molecular findings of an eosinophilic renal neoplasm which presented with rib and liver metastases, and provide a review of the literature. The possibility of a renal oncocytoma with metastases was initially considered but excluded on the basis of several morphological and immunohistochemical features. Additionally, the tumor did not correspond with other traditional or newly emerging categories of renal neoplasms. It was therefore regarded as an unclassified oncocytic renal neoplasm which demonstrated evidence of malignant potential due to the presence of multiple metastases.

Background: To investigate the value of computed tomography (CT)-based radiomics model analysis in differentiating renal oncocytoma (RO) from renal cell carcinoma subtypes (chromophobe renal cell carcinoma, clear cell carcinoma) and predicting the expression of Cytokeratin 7 (CK7)., Methods: In this retrospective study, radiomics was applied for patients with RO, chRCC and ccRCC who underwent surgery between January 2013 and December 2019 comprised the training cohort, and the testing cohort was collected between January and October 2020. The corticomedullary (CMP) and nephrographic phases (NP) were manually segmented, and radiomics texture parameters were extracted. Support vector machine was generated from CMP and NP after feature selection. Shapley additive explanations were applied to interpret the radiomics features. A radiomics signature was built using the selected features from the two phases, and the radiomics nomogram was constructed by incorporating the radiomics features and clinical factors. Receiver operating characteristic curve was calculated to evaluate the above models in the two sets. Furthermore, Rad-score was used for correlation analysis with CK7., Results: A total of 123 patients with RO, chRCC and ccRCC were analyzed in the training cohort and 57 patients in the testing cohort. Subsequently, 396 radiomics features were selected from each phase. The radiomics features combining two phases yielded the highest area under the curve values of 0.941 and 0.935 in the training and testing sets, respectively. The Pearson's correlation coefficient was statistically significant between Rad-score and CK7., Conclusion: We proposed a non-invasive and individualized CT-based radiomics nomogram to differentiation among RO, chRCC and ccRCC preoperatively and predict the immunohistochemical protein expression for accurate clinical diagnosis and treatment decision., (© 2022. The Author(s).)

Here we report a case of renal oncocytoma in a 68 year-old male. The diagnosis was initially made on a needle biopsy 6 years prior to the partial nephrectomy. The case is unique that in addition to the gross and microscopic features commonly seen in renal oncocytomas, both lymphovascular invasion and prominent intracytoplasmic vacuole-like spaces are also present in this tumor. Although vascular invasion is increasingly recognized as compatible with renal oncocytoma, intracytoplasmic vacuoles are a rare and unusual finding that may lead to diagnostic difficulty. The diagnosis of renal oncocytoma was confirmed after immunohistochemistry was performed to argue against succinate dehydrogenase deficient renal cell carcinoma (RCC) and chromophobe RCC. This case highlights the importance for practicing pathologists to recognize the rare co-occurrence of lymphovascular invasion and large intracytoplasmic vacuole-like spaces in renal oncocytoma. Other differential diagnoses may include emerging renal tumor entities, such as the recently-proposed eosinophilic vacuolated tumor.

Renal oncocytomas are rare benign epithelial tumors of the kidney. However, they are easily misdiagnosed as renal cancers, resulting in unnecessary radical nephrectomy. This review summarizes the use of ultrasound for the diagnosis of renal oncocytomas. On two-dimensional grayscale ultrasound, renal oncocytomas appear as solid, well-defined, round or oval, and relatively isoechoic or slightly hyperechoic masses. On color Doppler flow imaging, the "spoke-wheel" sign is evident. On power Doppler flow imaging, renal oncocytomas show mixed penetrating and peripheral patterns. Renal oncocytomas usually appear as highly enhanced on contrast-enhanced ultrasound images, and irregular nonenhanced areas in larger tumors. This review will help sonographers recognize renal oncocytomas., (© 2021. The Author(s), under exclusive licence to The Japan Society of Ultrasonics in Medicine.)

Objective: Differentiation between renal oncocytoma (RON) and chromophobe renal cell carcinoma (chRCC) remains challenging. We aimed to assess the accurate apparent diffusion coefficient (ADC) radiomics features in differentiating these tumors., Materials and Methods: This single-center retrospective study included 14 patients with histopathologically proven RON (n = 6) and chRCC (n = 8) who underwent magnetic resonance imaging. Features were extracted from ADC maps. Features with an intraclass correlation coefficient >0.90, an intergroup p < 0.01 and interrater differences with normal distribution underwent agreement and receiver operating characteristic curve analyses., Results: Overall, 6 features qualified for further analysis and Bland-Altman plots revealed acceptable agreement for all. Only 1 first order feature and 5 high order texture features successfully predicted RON with more than 90% sensitivities and specificities more than 80%., Conclusion: Squared mean ADC and certain gray level run length matrix features extracted by radiomics of ADC mapping provide quite high diagnostic precision in terms of distinguishing between RON and chRCC., (Copyright © 2021 AEU. Published by Elsevier España, S.L.U. All rights reserved.)

Background: Renal oncocytoma (RO) and chromophobe renal cell carcinoma (chRCC) have a common cellular origin and different clinical management and prognosis., Purpose: To explore the utility of computed tomography (CT) in the differentiation of RO and chRCC., Material and Methods: Twenty-five patients with RO and 73 patients with chRCC presenting with the central scar were included retrospectively. Two experienced radiologists independently reviewed the CT imaging features, including location, tumor size, relative density ratio, segmental enhancement inversion (SEI), necrosis, and perirenal fascia thickening, among others. Interclass correlation coefficient (ICC, for continuous variables) or Kappa coefficient test (for categorical variables) was used to determine intra-observer and inter-observer bias between the two radiologists., Results: The inter- and intra-reader reproducibility of the other CT imaging parameters were nearly perfect (>0.81) except for the measurements of fat (0.662). RO differed from chRCC in the cortical or medullary side ( P  = 0.005), relative density ratio ( P  = 0.020), SEI ( P  < 0.001), and necrosis ( P  = 0.045). The logistic regression model showed that location (right kidney), hypo-density on non-enhanced CT, SEI, and perirenal fascia thickening were highly predictive of RO. The combined indicators from logistic regression model were used for ROC analysis. The area under the ROC curve was 0.923 ( P  < 0.001). The sensitivity and specificity of the four factors combined for diagnosing RO were 88% and 86.3%, respectively. The correlation coefficient between necrosis and tumor size in all tumors including both of RO and chRCC was 0.584, indicating a positive correlation ( P  < 0.001)., Conclusion: The CT imaging features of location (right kidney), hypo-density on non-enhanced CT, SEI, and perirenal fascia thickening were valuable indicators in distinguishing RO from chRCC.

Objectives: To study the natural history of renal oncocytomas and address indications for intervention by determining how growth is associated with renal function over time, the reasons for surgery and ablation, and disease-specific survival., Patients and Methods: The study was conducted in a retrospective cohort of consecutive patients with renal oncocytoma on active surveillance reviewed at the Specialist Centre for Kidney Cancer at the Royal Free London NHS Foundation Trust (2012 to 2019). Comparison between groups was performed using Mann-Whitney U-tests and chi-squared tests. A mixed-effects model with a random intercept for patient was used to study the longitudinal association between tumour size and estimated glomerular filtration rate (eGFR)., Results: Longitudinal data from 98 patients with 101 lesions were analysed. Most patients were men (68.3%) and the median (interquartile range [IQR]) age was 69 (13) years. The median (IQR) follow-up was 29 (26) months. Most lesions were small renal masses, and 24% measured over 4 cm. Over half (64.4%) grew at a median (IQR) rate of 2 (4) mm per year. No association was observed between tumour size and eGFR over time (P = 0.871). Nine lesions (8.9%) were subsequently treated. Two deaths were reported, neither were related to the diagnosis of renal oncocytoma., Conclusion: Natural history data from the largest active surveillance cohort of renal oncocytomas to date show that renal function does not seem to be negatively impacted by growing oncocytomas, and confirms clinical outcomes are excellent after a median follow-up of over 2 years. Active surveillance should be considered the 'gold standard' management of renal oncocytomas up to 7cm., (© 2021 The Authors BJU International published by John Wiley & Sons Ltd on behalf of BJU International.)

Purpose: Renal oncocytoma (RO) is the most commonly resected benign renal tumor because of misdiagnosis as renal cell carcinoma. This misdiagnosis is generally owing to overlapping imaging features. This study describes the building of a radiomics nomogram based on clinical data and radiomics signature for the preoperative differentiation of RO from clear cell renal cell carcinoma (ccRCC) on tri-phasic contrast-enhanced CT., Methods: A total of 122 patients (85 in training set and 37 in external validation set) with ROs (n = 46) or ccRCCs (n = 76) were enrolled. Patient characteristics and tri-phasic contrast-enhanced CT imaging features were evaluated to build a clinical factors model. A radiomics signature was constructed by extracting radiomics features from tri-phasic contrast-enhanced CT images and a radiomics score (Rad-score) was calculated. A radiomics nomogram was then built by incorporating the Rad-score and significant clinical factors according to a multivariate logistic regression analysis. The diagnostic performance of the above three models was evaluated in training and validation sets., Results: Central stellate area and perirenal fascia thickening were selected to build the clinical factors model. Eleven radiomics features were combined to construct the radiomics signature. The AUCs of the radiomics nomogram, which was based on the selected clinical factors and Rad-score, were 0.960 and 0.898 in the training and validation sets, respectively. The decision curves of the radiomics nomogram and radiomics signature in the validation set indicated an overall net benefit over the clinical factors model., Conclusion: Our radiomics nomogram can effectively predict the preoperative diagnosis of ROs and may therefore be of assistance in sparing unnecessary surgery and tailoring precise therapy. The ROC curves of the clinical model, the radiomics signature and the radiomics nomogram for the validation set. RO = Renal oncocytoma; ccRCC = Clear cell renal cell carcinoma., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: To evaluate the ability of inferior vena cava-lesion-attenuation-difference (ILAD) and lesion-cortex-attenuation-ratio (LCAR) to differentiate renal oncocytomas (RO) from chromophobe renal cell carcinomas (chRCC)., Methods: Retrospective study with analysis of 84 cases of chRCC and 30 cases of RO confirmed by surgical pathology. ILAD was calculated by measuring the difference in Hounsfield units (HU) between the inferior vena cava and the lesion of interest on the same image slice on preoperative CT scan. Calculating LCAR using the CT attenuation ratio of lesion to renal cortex at the same image slice. Receiver operating characteristic (ROC) curves were plotted to analyze the diagnostic values of ILAD and LCAR for disease activity., Results: There were no statistically significant differences in demographic and lesion characteristics between patients with chRCC and RO (p > 0.05). ILAD has significant statistical differences in the identification of RO and chRCC in the arterial (p = 0.031), venous (p = 0.047), and delayed phase (p = 0.002). And LCAR showed a statistically significant difference between two lesions during the arterial (p = 0.043), venous (p = 0.026), and delayed phase (p = 0.008). When all significant variables were used in combination to build a predicting model (Mix), the AUC was 0.871 (95% CI 0.759-0.984) with 67.9% sensitivity and 100% specificity., Conclusion: ILAD and LCAR at the arterial phase, venous phase and delayed phase were shown to be useful CT attenuation parameter in discriminating RO from chRCC when histologic evaluation on biopsy is indeterminate.

FOXI1 is a forkhead family transcription factor that plays a key role in differentiation and functional maintenance for the renal intercalated cell (IC). The diagnostic utility of FOXI1 is rarely studied thus far. Comparative analyses of FOXI1 mRNA expression in normal kidney tissue and different renal neoplasms including chromophobe renal cell carcinoma (chRCC), renal oncocytoma (RO), and other renal cell carcinomas were conducted using transcriptomic data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus, and single-cell RNA-seq datasets, in combination with integrative analyses using mutant data, karyotype data, and digital slides for cases with anomalous FOXI1 expression in TCGA. Formalin-fixed, paraffin-embedded whole-tissue slides of varied primary renal neoplasms (n = 367) were subjected to FOXI1 staining for validating FOXI1 transcription levels. We confirmed that FOXI1 was significantly upregulated at mRNA levels in ICs, chRCCs, and ROs compared with other renal tubule cell and renal cell carcinoma subtypes. Furthermore, most of the cases with FOXI1 expression outliers were misclassified in the TCGA kidney cancer project. An underlying novel entity with frequent mutations involved in the mTOR pathway was also found. FOXI1 immunoreactivity was consistently noted in ICs of the distal nephron. FOXI1 staining was positive in 85 of 93 chRCCs and 13 of 18 ROs, respectively. FOXI1 staining was not seen in renal neoplasms (n = 254) derived from non-ICs. In conclusion, FOXI1 expression in normal kidney tissue is restricted to ICs. This cell type-specific expression is retained during neoplastic transformation from ICs to chRCCs or ROs. FOXI1 is thereby a potential biomarker of IC-related tumors.

The histologic features of renal oncocytoma (RO) are similar to those for the more aggressive chromophobe renal cell carcinoma (ChRCC). To assess immunohistochemical markers of the two, the sensitivity and specificity of cytokeratin 7 (CK7) and C-kit, as well as hepatocyte nuclear factor-1β (HNF-1β), were analyzed. Typical cases of ChRCC and RO at Severance Hospital between July 2014 and July 2018 were selected retrospectively. Among 44 cases, 17 were unanimously compatible with ChRCC, 16 were RO, and 11 cases were indeterminate. Samples from all selected cases were used for immunostaining with antibodies against CK7, C-kit, HNF-1β, and CD10. Immunostaining demonstrated complete loss of HNF-1β expression in 11 out of 17 (64.7%) ChRCC cases and a partial, but significant loss in > 50% of tumor cells in the remaining 6 cases (35.3%). In contrast, HNF-1β expression was preserved in tumor cells of RO cases. Fourteen of 17 ChRCC cases (82.4%) were diffusely positive for CK7, whereas cases of RO were focal positive or negative. C-kit staining did not show a significant difference between ChRCC and RO. Two of five ChRCC cases showing diffuse immunoreactivity for CD10 had poor prognoses of local invasion, distant metastasis, or death. Loss of HNF-1β expression is a useful marker with which to diagnose ChRCC, especially in cases with confusing histologic findings or equivocal CK7 staining. Additionally, CD10 staining in high-grade ChRCC aids in diagnosis and prediction of the clinical prognosis.

Renal oncocytoma (RO) accounts for 5% of renal cancers and generally behaves as a benign tumor with favorable long-term prognosis. It is difficult to confidently distinguish between benign RO and other renal malignancies, particularly chromophobe renal cell carcinoma (chRCC). Therefore, RO is often managed aggressively with surgery. We sought to identify molecular biomarkers to distinguish RO from chRCC and other malignant renal cancer mimics. In a 44-patient discovery cohort, we identified a significant differential abundance of nine genes in RO relative to chRCC. These genes were used to train a classifier to distinguish RO from chRCC in an independent 57-patient cohort. The trained classifier was then validated in five independent cohorts comprising 89 total patients. This nine-gene classifier trained on the basis of differential gene expression showed 93% sensitivity and 98% specificity for distinguishing RO from chRCC across the pooled validation cohorts, with a c-statistic of 0.978. This tool may be a useful adjunct to other diagnostic modalities to decrease the diagnostic and management uncertainty associated with small renal masses and to enable clinicians to recommend more confidently less aggressive management for some tumors. PATIENT SUMMARY: Renal oncocytoma is generally a benign form of kidney cancer that does not necessarily require surgical removal. However, it is difficult to distinguish renal oncocytoma from other more aggressive forms of kidney cancer, so it is treated most commonly with surgery. We built a classification tool based on the RNA levels of nine genes that may help avoid these surgeries by reliably distinguishing renal oncocytoma from other forms of kidney cancer., (Copyright © 2020. Published by Elsevier B.V.)

Purpose: We investigate the use of ratio of lesion to cortex (L/C) attenuation and aorta-lesion attenuation difference (ALAD) on multiphase contrast-enhanced CT to help distinguish oncocytoma from clear cell RCC in small renal masses (diameter < 4 cm)., Methods: We retrospectively identified 76 patients that undergo CT before surgery for a suspicious small renal mass between January 2014 and December 2018 with pathological diagnosis of 21 oncocytomas (ROs), 25 clear cell RCCs, 7 chromophobe RCCs, 7 papillary RCCs, 7 multilocular cystic RCCs, 7 angiomyolipomas and 2 leiomyomas. CT attenuation values were obtained for the tumor, the normal renal cortex and the aorta, placing a circular region of interest (ROI) in the same slice by two radiologists, independently., Results: In the corticomedullary phase, ROs showed isodense enhancement to the renal cortex (ratio L/C 0.92 ± 0.12), while clear cell RCCs appeared hypodense to the renal cortex (ratio L/C 0.69 ± 0.20; p < 0.01) with an accuracy of 80% for diagnosing RO. In nephrographic phase, the ratio L/C attenuation was lower than the corticomedullary phase in ROs (0.78 ± 0.11) showing an early washout pattern, while the ratio L/C was similar to the corticomedullary phase in clear cell RCCs (0.69 ± 0.13; p = 0.025, with an accuracy of 65% for diagnosing RO). The ratio L/C attenuation showed considerable overlap between ROs and clear cell RCCs in the excretory phase (p = 0.27). Mean ALAD values in the nephrographic phase were 21.95 ± 16.24 for ROs and 36.96 ± 30.53 for clear cell RCCs (p = 0.049)., Conclusion: The ratio L/C attenuation in corticomedullary phase may be useful to differentiate RO from clear cell RCC.

Background: The present study aims to evaluate the diagnostic performance of contrast-enhanced ultrasound (CEUS) for discriminating between benign and malignant solid renal masses., Methods: 18 patients with histopathologically confirmed benign solid renal masses (11 oncocytomas, seven angiomyolipomas) as well as 96 patients with confirmed renal cell carcinoma (RCC) who underwent CEUS followed by radical or partial nephrectomy were included in this single-center study. CEUS examinations were performed by an experienced radiologist (EFSUMB Level 3) and included the application of a second-generation contrast agent., Results: Renal angiomyolipomas, oncocytomas, and renal cell carcinomas showed varying sonomorphological characteristics in CEUS. Angiomyolipomas showed heterogeneous echogenicity (57% hypo-, 43% hyperechoic), while all lesions showed rapid contrast-enhancement with two lesions also showing venous wash-out (29%). Notably, 9/11 oncocytomas could be detected in conventional ultrasound (64% hypo-, 9% hyper-, 9% isoechoic) and 2/11 only demarcated upon intravenous application of contrast agent (18%). All oncocytomas showed hyperenhancement in CEUS, venous wash-out was registered in 7/11 lesions (64%)., Conclusions: In line with the current state of knowledge, no specific sonomorphological characteristics allowing for accurate distinction between benign and malignant solid renal masses in CEUS could be detected in our study.

Background: While subtyping of the majority of malignant chromophobe renal cell carcinoma (cRCC) and benign renal oncocytoma (rO) is possible on morphology alone, additional histochemical, immunohistochemical or molecular investigations are required in a subset of cases. As currently used histochemical and immunohistological stains as well as genetic aberrations show considerable overlap in both tumors, additional techniques are required for differential diagnostics. Mass spectrometry imaging (MSI) combining the detection of multiple peptides with information about their localization in tissue may be a suitable technology to overcome this diagnostic challenge. Patients and Methods: Formalin-fixed paraffin embedded (FFPE) tissue specimens from cRCC (n=71) and rO (n=64) were analyzed by MSI. Data were classified by linear discriminant analysis (LDA), classification and regression trees (CART), k-nearest neighbors (KNN), support vector machine (SVM), and random forest (RF) algorithm with internal cross validation and visualized by t-distributed stochastic neighbor embedding (t-SNE). Most important variables for classification were identified and the classification algorithm was optimized. Results: Applying different machine learning algorithms on all m/z peaks, classification accuracy between cRCC and rO was 85%, 82%, 84%, 77% and 64% for RF, SVM, KNN, CART and LDA. Under the assumption that a reduction of m/z peaks would lead to improved classification accuracy, m/z peaks were ranked based on their variable importance. Reduction to six most important m/z peaks resulted in improved accuracy of 89%, 85%, 85% and 85% for RF, SVM, KNN, and LDA and remained at the level of 77% for CART. t-SNE showed clear separation of cRCC and rO after algorithm improvement. Conclusion: In summary, we acquired MSI data on FFPE tissue specimens of cRCC and rO, performed classification and detected most relevant biomarkers for the differential diagnosis of both diseases. MSI data might be a useful adjunct method in the differential diagnosis of cRCC and rO., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

Objective: Renal oncocytoma (RO) and chromophobe renal cell carcinoma (ChRCC) originate from the same cell origin, that is, the intercalated cells of the collecting duct. [1] In most cases, there are clear morphologic differences between RO and ChRCC; however, in some instances, overlapping features may be encountered and the differentiation between the two entities becomes difficult. [2] Several immunohistochemical markers with different expression patterns in ChRCC and RO have been described to rule out this dilemma., Materials and Methods: About 47 primary renal neoplasms that had been diagnosed as RO or ChRCC were submitted for immunohistochemical staining of amylase α-1A (AMY1A), MOC 31, and CD 82. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy have been analyzed., Results: AMY1A positivity was observed in all RO cases in our work with 91.7% sensitivity and 100% specificity in the diagnosis of RO. The PPV of its expression was (100%) and NPV (97.2%) with a diagnostic accuracy of 97.9%. A significant high expression of MOC 31 was observed in ChRCC compared to its expression in RO with a statistical significance (P < 0.001). In addition, we obtained 82.9% sensitivity and 91.7% specificity of MOC 31 expression in the diagnosis of ChRCC. The positive predictive value (PPV) was (96.7%), negative predictive value (NPV) (64.7%) with diagnostic accuracy (85.1%). In our studied cases, we detected positive immunoexpression of CD 82 in 10 cases (83.3%) of ChRCC. However, it was lost in all RO cases (100%). CD 82 sensitivity and specificity in differentiating ChRCC from RO were 100% and 83.3%, respectively., Conclusion: We propose MOC 31 and CD 82 as negative immunostains for RO, as these markers are commonly expressed in ChRCC. In conjunction with AMY1A strong immunopositivity in RO cases, we provide a triple panel of biomarkers (AMY1A, MOC 31, and CD 82) for the distinction between RO and ChRCC.

Tento p&#345;ehledový &#269;lánek stru&#269;n&#283; shrnuje mo&#382;nosti vyu&#382;ití imunohistochemie p&#345;i vy&#353;et&#345;ování p&#345;edev&#353;ím renálních karcinom&#367; a základní molekulárn&#283; genetické znaky vybraných neoplázií. &#268;lánek v&#353;ak v &#382;ádném p&#345;ípad&#283; nelze brát jako univerzální návod pro diagnostiku renálních tumor&#367;. Renální karcinomy doká&#382;ou mít velmi variabilní morfologický vzhled a to i v rámci jedné léze (nádorová heterogenita) a &#269;asto velmi nep&#345;edvídatelný a neuniformní imunohistochemický profil. N&#283;které renální neoplázie jsou diagnostikovány striktn&#283; na podklad&#283; molekulárn&#283;-genetických vlastností, bez ohledu na morfologický vzhled.

Objectives . Differentiating renal oncocytoma (RO) from chromophobe renal cell carcinoma (ChRCC) can occasionally be challenging. We evaluated the expression of RB1 and ERBB4 in RO and ChRCC, and compared the immunohistochemistry (IHC) results to RB1 and ERBB4 gene abnormalities detected by fluorescence in situ hybridization (FISH). Materials and Methods. Fifty-three kidney resections (ChRCC, n=28; RO, n=25) were stained for RB1 and ERBB4 IHC and FISH was performed to evaluate gene copy number analysis. Results. A loss of RB1 staining was identified in 64% (18/28) of ChRCCs, which was not found in any ROs (0/25; P <.001). FISH analysis revealed 36% (10/28) of ChRCCs contained a RB1 hemizygous deletion with a concordance of 56% (10/18) between the IHC and FISH findings. No RB1 gene copy number variations were detected in any of the ROs (0/25; P <.001) and retained expression of RB1 by IHC. ERBB4 showed cytoplasmic/membranous staining in all ROs and ChRCCs. However, 75% (21/28) of ChRCCs also contained nuclear positivity for ERBB4, which was uncommonly seen in ROs (3/25, 12%; P < .001). A hemizygous ERBB4 gene deletion was detected in 46% of ChRCCs (13/28), but none of the ROs (0/25; 0%). Loss of labeling by RB1 or nuclear staining for ERBB4 IHC identified 25 of 28 (89%) of ChRCCs. Conclusion. In summary, the loss of RB1 expression is a highly specific diagnostic biomarker in distinguishing ChRCC from RO. Nuclear ERBB4 expression also appears to be a sensitive diagnostic biomarker for ChRCC, albeit the mechanism is unknown.

Purpose: The aim of the present retrospective single-center study is to evaluate the diagnostic performance of contrast-enhanced ultrasound (CEUS) in the evaluation of renal oncocytoma. Method: Thirteen patients with histopathologically confirmed renal oncocytoma and 26 patients with histopathologically confirmed renal cell carcinoma were included in this retrospective single-center study on whom CEUS was performed between 2005 and 2015. The applied contrast agent was a second-generation blood pool agent. CEUS examinations were performed and interpreted by a single radiologist with more than 15 years of experience (EFSUMB Level 3). Results: CEUS examinations were successfully performed in all included patients without any adverse effects. Renal oncocytomas showed varying echogenicity (46% hypoechoic, 23% hyperechoic, 8% iso-/hyperechoic, 8% isoechoic). In two cases renal oncocytoma only demarcated upon i.v. application of contrast medium. In bilateral oncocytosis, lesions presented as hyperechoic. Only 23% of renal oncocytomas showed slight vascularization using Color Doppler. No oncocytoma-specific pattern of microperfusion could be elucidated: 85% of the oncocytomas presented hyperenhancing, of whom 50% also showed delayed venous wash-out; 8% of renal oncocytomas showed venous wash-out without early arterial hyperenhancement. Conclusions: Within the frame of the present study and in line with the recent state of knowledge, no specific sonomorphological feature - including CEUS - could be detected allowing for adequate discrimination between oncocytoma and renal cell carcinoma.

A novel analytical approach is proposed to discriminate between solid biopsies of chromophobe renal cell carcinoma (chRCC) and renal oncocytoma (RO). The method comprises the following steps: (i) ultrasonic extraction of proteins from solid biopsies, (ii) protein depletion with acetonitrile, (iii) ultrasonic assisted in-solution digestion using magnetic nanoparticle with immobilized trypsin, (iv) C18 tip-based preconcentration of peptides, (v) sequential extraction of the peptides with ACN, (vi) MALDI-snapshot of the extracts and (vii) investigation of the extract containing the most discriminating features using high resolution mass spectrometry. With this approach we have been able to differentially cluster renal oncocytoma and chromophobe renal cell carcinoma and identified 18 proteins specific to chromophobe and seven unique to renal oncocytoma. Chromophobes express proteins associated with ATP function (ATP5I & 5E; VATE1 & G2; ADT2), glycolysis (PGK1) and neuromedin whilst oncocytomas express ATP5H, ATPA, DEPD7 and TRIPB thyroid receptor interacting protein., (Copyright © 2019 Elsevier B.V. All rights reserved.)

The cytogenetic alterations in renal oncocytoma (RO) are poorly understood. We analyzed 130 consecutive RO for karyotypic alterations. Clonal chromosome abnormalities were identified in 63 (49%) cases, which could be categorized into three classes of mutually exclusive cytogenetic categories. Class 1 (N = 20) RO had diploid karyotypes with characteristic 11q13 rearrangement in balanced translocations with 10 or more different chromosome partners in all cases. We identified recurrent translocation partners at 5q35, 6p21, 9p24, 11p13-14, and 11q23, and confirmed that CCND1 gene rearrangement at 11q13 utilizing fluorescence in situ hybridization (FISH). Class 2 RO (N = 25) exhibited hypodiploid karyotypes with loss of chromosome 1 and/or losses of Y in males and X in females in all cases. The class 3 tumors comprising of 18 cases showed diverse types of abnormalities with the involvement of two or more chromosomes exclusive of abnormalities seen in classes 1 and 2 tumors. Furthermore, karyotypically uninformative cases were subjected to FISH analysis to identify classes 1 and 2 abnormalities. In this group, we found similar frequencies of CCND1 rearrangement, loss of chromosome 1 or Y as with karyotypically abnormal cases. We validated our results against 91 tumors from the Mitelman database. Correlation of clinical data with all the three classes of ROs showed no clear evidence of overall patient survival. Our findings support the hypothesis that RO exhibit three principal cytogenetic categories, which may have different roles in initiation and/or progression. These cytogenetic markers provide a key tool in the diagnostic evaluation of RO., (© 2019 Wiley Periodicals, Inc.)

Renal oncocytoma is a benign epithelial neoplasm typically composed of large cells with granular eosinophilic cytoplasm. Although rare, histologically worrisome features such as vascular and perinephric fat invasion have been reported. Of the 159 renal oncocytomas resected at our institution, 20 (12.6%) had vascular and/or perinephric fat invasion. Microscopically, 10 oncocytomas had perinephric fat invasion, 7 had vascular invasion and 3 had both vascular and perinephric fat invasion. Grossly, perinephric fat invasion was visible in three cases and tumour was identified within the branches of the renal vein in two cases. Tumours occurred in 14 men and 6 women (M:F = 2.3:1). The mean age at diagnosis was 64.5 years (range, 33-88 years). A total of 11 cases had radical nephrectomies while 9 cases had partial nephrectomies. There was no evidence of disease recurrence, metastasis or death due to tumour after a mean follow up of 25.6 months (range, 2-103 months). The presence of vascular and perinephric fat invasion in renal oncocytoma though worrisome, does not alter the benign course of the tumour., Competing Interests: Conflict of interest statement: The authors declare no conflicts of interest in preparing this article., (© The Author(s), 2019.)

An effective three-step proteomics workflow is proposed to overcome the pitfalls caused by polymers present in optimum cutting temperature (OCT)-embedded tissue during its preparation for mass spectrometry analysis. First, the OCT-embedded tissue biopsies are cleaned using ethanol and water in a sequential series of ultrasonic washes in an ultrasound bath (35 kHz ultrasonic frequency, 100% ultrasonic amplitude, 2 min of ultrasonic duty time). Second, a fast ultrasonic-assisted extraction of proteins is done using an ultrasonic probe (30 kHz ultrasonic frequency, 50% ultrasonic amplitude, 2 min of ultrasonic duty time, 1 mm diameter tip). Third, a rapid ultrasonic digestion of complex proteomes is performed using a microplate horn assembly device (20 kHz ultrasonic frequency, 25% ultrasonic amplitude, 4 min of ultrasonic duty time). As a proof of concept, the new workflow was applied to human normal and tumor kidney biopsies including chromophobe renal cell carcinomas (chRCCs) and renal oncocytomas (ROs). A successful cluster of proteomics profiles was obtained comprising 511 and 172 unique proteins found in chRCC and RO samples, respectively. The new method provides high sample throughput and comprehensive protein recovery from OCT samples.

Renal oncocytoma is generally regarded as a benign renal tumor. We herein report a case of large renal oncocytoma with renal venous tumor thrombus. The patient may need to be carefully followed up because hematogenous metastasis may occur.

Background/aim: Renal oncocytoma (RO) and chromophobe renal cell carcinoma (chRCC) are suggested to develop from α- and β-intercalated (IC) cells of the collecting duct expressing solute carrier family 4 member 1 (SLC4A1) and SLC26A4 under control of forkhead box 1 (FOXI1) transcription factor. The aim of this study was to clarify the possible cellular origin and of RO and chRCC., Materials and Methods: Immunohistochemistry for aquaporin 2 (AQP2), FOXI1, SLC4A1 and SLC16A4 was applied to distinct types of renal cell tumors., Results: Nuclear FOXI1 staining occurred in 96% of 83 ROs, in 3% of 90 chRCCs and none of the other tumor types. The α-IC cell marker SLC4A1 was seen in 60% of RO and 11% of chRCC, whereas staining for the β-IC cell marker SLC26A4 was negative in all but one tumor., Conclusion: Although the origin of RO remains unclear, our findings suggest that FOXI1 immunohistochemistry is useful in differential diagnosis of RO from chRCC with overlapping histology., (Copyright© 2019, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

Low-grade eosinophilic unclassified renal cell carcinoma is a rare kidney tumor recently described, not included in the WHO classification, which is very close to oncocytoma. It is unknown to most pathologists and clinicians. From a histopathological point of view, this tumor is composed of oncocytic cells arranged in a diffuse and solid pattern, without cell nests, that makes it possible to differentiate it from oncocytoma, and expresses cytokeratin 7 (CK7) heterogeneously. We report a case with a cranial vault metastasis, and present the features to differentiate this entity from oncocytoma. Furthemore, we discuss about unclassified renal cell carcinomas with oncocytic cells., (Copyright © 2018 Elsevier Masson SAS. All rights reserved.)

The increase in serendipitous detection of solid renal masses on imaging has not resulted in a reduction in mortality from renal cell carcinoma. Consequently, efforts for improved lesion characterization have been pursued and incorporated into management algorithms for distinguishing clinically significant tumors from those with favorable histology or benign conditions. Although diagnostic imaging strategies have evolved for optimized lesion detection, distinction between benign tumors and both indolent and aggressive malignant neoplasms remain an important diagnostic challenge. Recent advances in cross-sectional imaging have expanded the role of these tests in the noninvasive characterization of solid renal tumors., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Objective: To report on the contemporary UK experience of surgical management of renal oncocytomas., Patients and Methods: Descriptive analysis of practice and postoperative outcomes of patients with a final histological diagnosis of oncocytoma included in The British Association of Urological Surgeons (BAUS) nephrectomy registry from 01/01/2013 to 31/12/2016. Short-term outcomes were assessed over a follow-up of 60 days., Results: Over 4 years, 32 130 renal surgical cases were recorded in the UK, of which 1202 were oncocytomas (3.7%). Most patients were male (756; 62.9%), the median (interquartile range [IQR]) age was 66.8 (13) years. The median (IQR; range) lesion size was 4.1 (3; 1-25) cm, 43.5% were ≤4 cm and 30.3% were 4-7 cm lesions. In all, 35 patients (2.9%) had preoperative renal tumour biopsy. Most patients had minimally invasive surgery, either radical nephrectomy (683 patients; 56.8%), partial nephrectomy (483; 40.2%) or other procedures (36; 3%). One in five patients (243 patients; 20.2%) had in-hospital complications: 48 were Clavien-Dindo classification grade ≥III (4% of the total cohort), including three deaths. Two additional deaths occurred within 60 days of surgery. The analysis is limited by the study's observational nature, not capturing lesions on surveillance or ablated after biopsy, possible underreporting, short follow-up, and lack of central histology review., Conclusion: We report on the largest surgical series of renal oncocytomas. In the UK, the complication rate associated with surgical removal of a renal oncocytoma was not negligible. Centralisation of specialist services and increased utilisation of biopsy may inform management, reduce overtreatment, and change patient outcomes for this benign tumour., (© 2018 The Authors BJU International © 2018 BJU International Published by John Wiley & Sons Ltd.)

Background: Renal oncocytoma is the most common benign renal tumor, and papillary renal cell carcinoma is the second most common histologic subtype of renal cell carcinoma. Renal tumors containing different components such as papillary renal cell carcinoma and oncocytoma are extremely rare., Case Presentation: A renal mass was incidentally detected in a 52-year-old Korean woman, and a computed tomographic scan showed a 32-mm multicystic mass with some calcifications in the lower pole of the right kidney. She underwent laparoscopic partial nephrectomy without any perioperative complications. We found a papillary renal cell carcinoma and an oncocytoma in a tumor mass., Conclusions: The possibility of a mixed malignant tumor should be considered while treating benign tumors such as oncocytoma.

Renal cell carcinoma (RCC) constitutes an array of morphologically and genetically distinct tumors the most prevalent of which are clear cell, papillary, and chromophobe RCC. Accurate distinction between the typically benign-behaving renal oncocytoma and RCC subtypes is a frequent challenge for pathologists. This is critical for clinical decision making. Subtypes also have different survival outcomes and responses to therapy. We extracted RNA from ninety formalin-fixed paraffin-embedded (FFPE) tissues (27 clear cell, 29 papillary, 19 chromophobe, 4 unclassified RCC and 11 oncocytomas). We quantified the expression of six miRNAs (miR-221, miR-222, miR-126, miR-182, miR-200b and miR-200c) by qRT-PCR, and by in situ hybridization in an independent set of tumors. We developed a two-step classifier. In the first step, it uses expression of either miR-221 or miR-222 to distinguish the clear cell and papillary subtypes from chromophobe RCC and oncocytoma (miR-221 AUC: 0.96, 95% CI: 0.9132-1.014, p < 0.0001 and miR-222 AUC: 0.91, 95% CI: 0.8478-0.9772, p < 0.0001). In the second step, it uses miR-126 to discriminate clear cell from papillary RCC (AUC: 1, p < 0.0001) and miR-200b to discriminate chromophobe RCC from oncocytoma (AUC: 0.95, 95% CI: 0.8933-1.021, p < 0.0001). In situ hybridization showed a nuclear staining pattern. miR-126, miR-222 and miR-200b were significantly differentially expressed between the subtypes by in situ hybridization. miRNA expression could distinguish RCC subtypes and oncocytoma. miRNA expression assessed by either PCR or in situ hybridization can be a clinically useful diagnostic tool to complement morphologic renal tumor classification, improving diagnosis and patient management., Competing Interests: CONFLICTS OF INTEREST The authors have declared no conflicts of interest.

Objectives: To compare the performance of diffusion-weighted imaging (DWI) with that of contrast-enhanced MRI in differentiating renal oncocytomas from chromophobe renal cell carcinomas (RCCs)., Methods: We recruited 48 patients with histopathologically confirmed renal oncocytomas (n=16) and chromophobe RCCs (n=32). All patients underwent preoperative DWI and contrast-enhanced MRI. Apparent diffusion coefficient (ADC) and signal intensity were measured in each patient. ADC ratio and percentage of signal intensity change were calculated., Results: Mean ADC values for renal oncoctytomas were significantly higher than those for chromophobe RCCs (1.59±0.21 vs. 1.09±0.29× 10 -3 mm 2 /s, p < 0.001). Area under the ROC curve, sensitivity and specificity were 0.931, 87.5% and 84.4%, respectively, for ADC measurement of DW imaging; 0.825, 87.5% and 75%, respectively, for enhancement ratio (p > 0.05). Adding ADC values to the enhancement ratios in the ROC, analysis to differentiate renal oncocytoma from chromophobe RCCs increased specificity from 75 to 87.5% at 87.5% sensitivity without significantly increasing the AUC (0.930)., Conclusions: Both DWI and contrast-enhanced MRI may assist in differentiating renal oncocytomas from chromophobe RCCs, with DWI showing higher diagnostic value. The combination of the two parameters could potentially provide better performance in distinguishing these two tumours., Key Points: • ADC values can assist in differentiating renal oncocytomas from chromophobe RCCs. • DW imaging possesses better specificity than does contrast-enhanced MR imaging. • Combining the two parameters provides higher specificity regarding the differential diagnosis.

Renal oncocytomas are rare benign tumors of the kidney and characterized by a deficient complex I (CI) enzyme activity of the oxidative phosphorylation (OXPHOS) system caused by mitochondrial DNA (mtDNA) mutations. Yet, little is known about the underlying molecular mechanisms and alterations of metabolic pathways in this tumor. We compared renal oncocytomas with adjacent matched normal kidney tissues on a global scale by multi-omics approaches, including whole exome sequencing (WES), proteomics, metabolomics, and metabolic pathway simulation. The abundance of proteins localized to mitochondria increased more than 2-fold, the only exception was a strong decrease in the abundance for CI subunits that revealed several pathogenic heteroplasmic mtDNA mutations by WES. We also observed renal oncocytomas to dysregulate main metabolic pathways, shunting away from gluconeogenesis and lipid metabolism. Nevertheless, the abundance of energy carrier molecules such as NAD + , NADH, NADP, ATP, and ADP were significantly higher in renal oncocytomas. Finally, a substantial 5000-fold increase of the reactive oxygen species scavenger glutathione can be regarded as a new hallmark of renal oncocytoma. Our findings demonstrate that renal oncocytomas undergo a metabolic switch to eliminate ATP consuming processes to ensure a sufficient energy supply for the tumor., Competing Interests: CONFLICTS OF INTEREST No competing interests are declared.

Background Small renal masses (SRMs; ≤4 cm) represent a challenging issue. Computed tomography (CT) is widely used for investigating renal tumors even if its ability to differentiate among the different subtypes has not yet been definitively established. Purpose To assess the potential role of the morphological features and angiodynamic behavior on multiphasic CT in the preoperative evaluation of SRMs. Material and Methods The CT images of 80 patients with SRMs who underwent surgical resection at our institution were retrospectively reviewed. The morphological features, the pattern, and the quantitative analysis of enhancement were assessed for each lesion and were correlated with the histological subtypes. Results Overall, 81 SRMs were evaluated. Final pathological examination showed 30 (37%) oncocytomas, 22 (27.2%) clear cell renal cell carcinomas (ccRCCs), 16 (19.8%) papillary RCCs (pRCCs), and 13 (16%) chromophobe RCCs (chRCCs). Of the morphological features, only necrosis was significantly associated with ccRCC ( P = 0.047). The analysis of enhancement allowed the identification of two groups of lesions, based on arterial behavior: hypervascular (oncocytomas/ccRCC) and hypovascular (chRCC/pRCC) lesions. A significant difference between the two groups in terms of degree of enhancement on CT phases was found ( P < 0.05); this was also confirmed by the receiver operating characteristic (ROC) analysis. Conclusion Except for necrosis, the morphological features are not useful in making a correct diagnosis in the case of SRMs. The angiodynamic behavior on multiphasic CT showed high accuracy in differentiating between hypovascular and hypervascular tumors; this differentiation could be useful for deciding on the most appropriate clinical management of SRMs.