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.

The increasing evidence of oncocytic renal tumors positive in 99mTc 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 99mTc 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 99mTc 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 99mTc 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 99mTc 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 99mTc Sestamibi uptake was the most influential attribute in the combined model. This study highlights the potential of combining radiomics analysis with 99mTc Sestamibi SPECT/CT to improve the preoperative characterization of benign renal oncocytic neoplasms. The proposed SPECT/radiomics classifier outperformed the visual evaluation of 99mTc Sestamibii SPECT/CT and the radiomics-only model, demonstrating that the integration of 99mTc Sestamibi SPECT/CT and radiomics data provides improved diagnostic performance, with minimal false positive and false negative results.

Paraganglioma is a rare type of neuroendocrine tumor with variable clinical presentations, making diagnosis relatively challenging. In this report, we present a case of retroperitoneal paraganglioma in a patient who experienced intermittent episodes of dizziness and chest pain. Imaging studies conducted during the patient\'s hospitalization revealed the presence of a lesion in the upper region of the right kidney, as well as a mass in the left retroperitoneal area that was suspected to be a paraganglioma. Biochemical studies were collected, including 24-hour urine metanephrines, urine catecholamines, urine cortisol, plasma metanephrines, renin, and aldosterone. However, it took an extended period of time for these results to come back. Given high clinical suspicion, alpha-blockade was initiated without a definite diagnosis of paraganglioma. Ultimately, the patient underwent tumor resection and the final pathology confirmed paraganglioma. The pathology of the contralateral renal mass showed oncocytoma. This case serves as an illustration of the difficulties that can arise when diagnosing and treating undiagnosed paragangliomas within a community healthcare setting.

This is a case report about a patient which presents with two right renal tumors, one of them being an oncocytoma with typical histopathological features and renal vein extension. Recent studies show that despite renal vein thrombus being a histological sign of malignancy; when associated with renal oncocytoma, it should not alter the benign prognosis of oncocytoma, and a simple follow-up may be carried. Further explorations should be done when easily available, and when the histopathologic diagnosis of oncocytoma is uncertain, to rule out the differential diagnosis of a chromophobe renal cell carcinoma, oncocytic variant.

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.

Renal oncocytoma is usually detected incidentally. It can be considered as a renal cell carcinoma (RCC) on preoperative imaging. They usually present as small masses and usually look like benign tumors. Giant oncocytomas are rare. A 72-year-old male patient was seen in the outpatient department for left scrotal swelling. Ultrasound (US) showed a giant mass compatible with RCC in the right kidney which was incidentally detected. Abdominal computed tomography (CT) revealed a mass with an axial diameter of 167×146 mm, compatible with RCC, a heterogeneous mass of soft tissue density with central necrosis. There was no evidence of tumor thrombus in the right renal vein or inferior vena cava. Open radical nephrectomy was performed through an anterior subcostal incision. Pathological examination revealed a 17×15 cm renal oncocytoma. The patient was discharged on the sixth day postoperatively. Clinically or radiologically, renal oncocytoma and renal cell carcinoma usually cannot be distinguished, although oncocytoma may be suspected if a central scar with fibrous extensions is seen, the so-called \"spoke-wheel appearance\". The treatment decision should be made according to the clinical aspects. Radical/partial nephrectomy or thermal ablation can be considered as treatment options. In this article, we review the literature on the radiological and pathological features of renal oncocytoma.

To evaluate whether significant loss in ipsilateral renal parenchymal volume (IRPV) and renal function occurs during active surveillance (AS) of renal oncocytoma (RO) patients.
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 cm3. 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.
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 m2, P = 0.50; median change -3.0 ml/min/1.73 m2). Among patients (n = 17) with RO growth >+10 cm3 during AS (median growth +28.6 cm3, IQR +16.9- + 46.5 cm3), 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.
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.

UNASSIGNED: \"Other oncocytic renal tumors of the kidney\" is a new category constituted by 2022 WHO classification and different in the point of morphology and immunohistochemistory from typical oncocytic/eosinophilic renal tumors including chromophobe renal cell carcinoma and oncocytoma.
UNASSIGNED: The patient was an 84-year-old woman in whom a left renal tumor was incidentally discovered. She underwent left nephrectomy, and the pathological specimens showed a borderline eosinophilic renal tumor between chromophobe renal cell carcinoma and renal oncocytoma. After all recognized oncocytic tumors were excluded, we diagnosed the tumor as other oncocytic renal tumor of the kidney.
UNASSIGNED: Other oncocytic renal tumor of the kidney is a provisional category. Therefore, further research and accumulation of similar cases are necessary.

Renal oncocytoma is a benign tumor that arises from epithelial cells of the distal renal tubules. It is naturally presented with a small-sized mass, and giant oncocytoma is uncommon. Renal oncocytoma is frequently asymptomatic and challenging to distinguish preoperatively from renal cell carcinoma (RCC). We present a 40-year-old man who presented with intermittent abdominal pain in the last two years. Abdominal computed tomography (CT) scan showed a large, heterogenous left renal mass measured 15 x 16 x 19.5 cm and associated with central calcifications suspected of RCC. The patient underwent a left radical nephrectomy without complication. The histopathological study revealed typical oncocytoma features. There was no detected recurrence or distant metastasis on six months follow-up. In conclusion, it is challenging to distinguish renal oncocytoma from RCC via preoperative radiology images, especially when a giant mass is present. The only histopathology examination of the removed specimen can provide a definitive diagnosis.

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.