Towards Personalized Sampling in Clear Cell Renal Cell Carcinomas

Alpha-methyl CoA racemase (AMACR) reactivity across the spectrum of clear cell renal cell neoplasms

a-Methylacyl coenzyme A racemase (AMACR) is traditionally considered to be a marker of papillary renal cell carcinoma. However, AMACR expression can be seen in other renal tumors. The aim of this study was to investigate AMACR immunoreactivity within the spectrum of clear cell renal cell neoplasms. Fifty-three clear cell renal epithelial tumors were used in assembling the following four cohorts: low grade (LG) clear cell renal cell carcinoma (CCRCC), high grade (HG) CCRCC, CCRCC with cystic changes, and multilocular cystic renal neoplasm of low malignant potential (MCRNLMP). Representative blocks were stained for AMACR, using two different clones (SP52 and OV-TL12/30). There were at least some AMACR immunoreactivity in 77.8 % and 68.9 % of CCRCCs (using SP52 and OV-TL12/30 clone, respectively). Moderate to strong positivity, or positivity in more than one third of the tumor (even weak in intensity) was detected in 46.7 % of CCRCCs using SP52 and in 48.9 % of CCRCC using OV-TL12/30 clone. The highest AMACR reactivity was observed in HG CCRCC (60 % by SP52 and 66.7 % by OV-TL12/30). Strong and diffuse AMACR positivity was detected in 8.9 % of all CCRCCs. AMACR immunoreactivity in MCRNLMP was 37.5 % (SP52 clone) and 25 % (OV-TL12/30 clone). We demonstrated relatively high expression rate of AMACR in CCRCC, while very variable in intensity and distribution. This finding may have diagnostic implications especially in limited samples (i.e., core biopsies), as AMACR positivity does not exclude the diagnosis of CCRCC.

The Expression of Alamandine Receptor MrgD in Clear Cell Renal Cell Carcinoma Is Associated with a Worse Prognosis and Unfavorable Response to Antiangiogenic Therapy

Renal cell carcinoma (RCC) ranks among the most prevalent malignancies in Western countries, marked by its notable heterogeneity, which contributes to an unpredictable clinical trajectory. The insufficiency of dependable biomarkers adds complexity to assessing this tumor progression. Imbalances of several components of the intrarenal renin-angiotensin system (iRAS) significantly impact patient prognoses and responses to first-line immunotherapies. In this study, we analyzed the immunohistochemical expression of the Mas-related G-protein-coupled receptor D (MrgD), which recognizes the novel RAS peptide alamandine (ALA), in a series of 87 clear cell renal cell (CCRCCs), 19 papillary (PRCC), 7 chromophobe (ChRCC) renal cell carcinomas, and 11 renal oncocytomas (RO). MrgD was expressed in all the renal tumor subtypes, with a higher mean staining intensity in the PRCCs, ChRCCs, and ROs. A high expression of MrgD at the tumor center and at the infiltrative front of CCRCC tissues was significantly associated with a high histological grade, large tumor diameter, local invasion, and locoregional node and distant metastasis. Patients with worse 5-year cancer-specific survival and a poorer response to antiangiogenic tyrosine-kinase inhibitors (TKIs) showed higher MrgD expression at the center of their primary tumors. These findings suggest a possible role of MrgD in renal carcinogenetic processes. Further studies are necessary to unveil its potential as a novel biomarker for CCRCC prognosis and response to frontline therapies.

Improving CNNs classification with pathologist-based expertise: the renal cell carcinoma case study

The prognosis of renal cell carcinoma (RCC) malignant neoplasms deeply relies on an accurate determination of the histological subtype, which currently involves the light microscopy visual analysis of histological slides, considering notably tumor architecture and cytology. RCC subtyping is therefore a time-consuming and tedious process, sometimes requiring expert review, with great impact on diagnosis, prognosis and treatment of RCC neoplasms. In this study, we investigate the automatic RCC subtyping classification of 91 patients, diagnosed with clear cell RCC, papillary RCC, chromophobe RCC, or renal oncocytoma, through deep learning based methodologies. We show how the classification performance of several state-of-the-art Convolutional Neural Networks (CNNs) are perfectible among the different RCC subtypes. Thus, we introduce a new classification model leveraging a combination of supervised deep learning models (specifically CNNs) and pathologist's expertise, giving birth to a hybrid approach that we termed ExpertDeepTree (ExpertDT). Our findings prove ExpertDT's superior capability in the RCC subtyping task, with respect to traditional CNNs, and suggest that introducing some expert-based knowledge into deep learning models may be a valuable solution for complex classification cases.

Advances in Urological Cancer in 2022, from Basic Approaches to Clinical Management

This Special Issue includes 12 articles and 3 reviews dealing with several basic and clinical aspects of prostate, renal, and urinary tract cancer published during 2022 in Cancers, and intends to serve as a multidisciplinary chance to share the last advances in urological neoplasms [...].

Tumor-to-Tumor Metastases Involving Clear Cell Renal Cell Carcinomas: A Diagnostic Challenge for Pathologists Needing Clinical Correlation

Tumor-to-tumor metastasis is a rare event which it is specifically up to pathologists to bring to light correctly. The histological identification of such tumor-to-tumor cases is simple when the respective histologies are different but can be problematic if the case includes two carcinomas with similar cytoarchitecture viewed one inside the other under the microscope. We report four cases of this condition in which clear cell renal cell carcinoma is involved, either as a receptor or as a donor, and remark on the difficulties in recognizing some of them. Appropriate clinical-pathological correlation, including a review of the patient's antecedents and radiological exams, would be a great help in routinely identifying tumor-to-tumor metastases.

Pathology and the evolutionary dynamics of clear cell renal cell carcinoma

Cancer is an ecosystem whose intrinsic mechanisms do not show up under the microscope of pathologists. However, the information provided by pathologists is absolutely necessary for the correct implementation of personalized treatments. This short paper seeks to analyze this apparent paradox, i.e. static snapshots for making crucial decisions in essentially dynamic diseases, taking clear cell renal cell carcinoma as a paradigmatic example of tumor variability. We seek to call the attention of pathologists and other cancer-related medical specialists to extend knowledge of the evolutionary features of the disease to help obtain a better understanding of why cancer behaves as it does.