Real-world biomarker testing patterns: clinical-pathological portrait of early and late non-small cell lung cancer in hub and spoke North Italian centers.

Background: Lung cancer is still the main cause of cancer death. In the last decades, significant innovations were introduced in non-small cell lung cancer (NSCLC) treatment and management improving patient outcomes. The discovery of immune checkpoint inhibitors and the detection of an increasing list of actionable genetic alterations are enabling a tailored approach. Herein, we assessed in a pragmatic retrospective study the rate of biomarker tests within a large pulmonary pathology-based unit (PPU) network of the Veneto region (Northern Italy). Methods: Each PPU of 7 hubs and spoke centers implemented a biomarker database with pathologic and clinical data of patients with NSCLC diagnosis over 24 months. Results: Out of 1,817 NSCLC cases, 51% were advanced and 49% early stage, with 72% being adenocarcinomas. Programmed death ligand 1 expression and epidermal growth factor receptor mutations were available in most samples, 91% and 78%, respectively. Only 36% of advanced stages received all 5 biomarker tests with an increased rate over time. Co-occurring molecular alterations were detected in 42 cases (2%): the prevalence was (n=17) 41% and (n=25) 59% in early and late-stage adenocarcinomas, respectively. Conclusions: In this real-world study, while most patients received at least one biomarker test, less than 50% had all 5 biomarkers. The screening appeared to increase over time especially with the progressive use of next generation sequencing. Our results confirm the importance of systematic biomarker testing including all NSCLCs based on the evidence of several genomic alterations also in early-stage disease whose analysis may become relevant as neo-adjuvant targeted therapies are available. Keywords: Non-small cell lung cancer (NSCLC); biomarkers; actionable targets; lung cancer.

Comparison of Primary and Metastatic Fumarate Hydratase-Deficient Renal Cell Carcinomas Documents Morphologic Divergence and Potential Diagnostic Pitfall With Peritoneal Mesothelioma.

Fumarate hydratase (FH)-deficient renal cell carcinomas are rare neoplasms characterized by wide morphologic heterogeneity and pathogenetic mutations in the FH gene. They often show aggressive behavior with rapid diffusion to distant organs, so novel therapeutic scenarios have been explored, including EGFR inhibitors and PD-L1 expression for targeted immunotherapy. Herein, we investigated a series of 11 primary FH-deficient renal cell carcinomas and 7 distant metastases to evaluate tumor heterogeneity even in metastatic sites and estimate the specific spread rates to various organs. Furthermore, the tumors were tested for immunohistochemical PD-L1 expression and EGFR mutations. Most metastatic cases involved the abdominal lymph nodes (4/7; 57%), followed by the peritoneum (3/7; 42%), the liver (2/7; 29%), and the lungs (1/7; 14%). Six metastatic localizations were histologically documented, revealing a morphologic heterogeneous architecture often differing from that of the corresponding primary renal tumor. Peritoneal involvement morphologically resembled a benign reactive mesothelial process or primary peritoneal mesothelioma, thus advocating to perform an accurate immunohistochemical panel, including PAX8 and FH, to reach a proper diagnosis. A pure low-grade succinate dehydrogenase-looking primary FH-deficient renal cell carcinoma was also recorded. As for therapy, significant PD-L1 labeling was found in 60% of primary renal tumors, whereas none of them carried pathogenetic EGFR mutations. Our data show that FH-deficient renal cell carcinoma may be morphologically heterogeneous in metastases as well, which involve the lymph nodes, the liver, and the peritoneum more frequently than other renal tumors. Due to the high frequency of this latter (42%), pathologists should always be concerned about ruling out mesothelial-derived mimickers, and the occurrence of rarer, primary, low-grade-looking types. Finally, contrary to EGFR mutations, PD-L1 expression could be a possible predictive biomarker for the therapy of these tumors.

Benchmarking digital displays (monitors) for histological diagnoses: the nephropathology use case.

AIM: The digital transformation of the pathology laboratory is being continuously sustained by the introduction of innovative technologies promoting whole slide image (WSI)-based primary diagnosis. Here, we proposed a real-life benchmark of a pathology-dedicated medical monitor for the primary diagnosis of renal biopsies, evaluating the concordance between the 'traditional' microscope and commercial monitors using WSI from different scanners. METHODS: The College of American Pathologists WSI validation guidelines were used on 60 consecutive renal biopsies from three scanners (Aperio, 3DHISTECH and Hamamatsu) using pathology-dedicated medical grade (MG), professional grade (PG) and consumer-off-the-shelf (COTS) monitors, comparing results with the microscope diagnosis after a 2-week washout period. RESULTS: MG monitor was faster (1090 vs 1159 vs 1181 min, delta of 6-8%, p<0.01), with slightly better performances on the detection of concurrent diseases compared with COTS (κ=1 vs 0.96, 95% CI=0.87 to 1), but equal concordance to the commercial monitors on main diagnosis (κ=1). Minor discrepancies were noted on specific scores/classifications, with MG and PG monitors closer to the reference report (r=0.98, 95% CI=0.83 to 1 vs 0.98, 95% CI=0.83 to 1 vs 0.91, 95% CI=0.76 to 1, κ=0.93, 95% CI=077 to 1 vs 0.93, 95% CI=0.77 to 1 vs 0.86, 95% CI=0.64 to 1, κ=1 vs 0.50, 95% CI=0 to 1 vs 0.50, 95% CI=0 to 1, for IgA, antineutrophilic cytoplasmic antibody and lupus nephritis, respectively). Streamlined Pipeline for Amyloid detection through congo red fluorescence Digital Analysis detected amyloidosis on both monitors (4 of 30, 13% cases), allowing detection of minimal interstitial deposits with slight overestimation of the Amyloid Score (average 6 vs 7). CONCLUSIONS: The digital transformation needs careful assessment of the hardware component to support a smart and safe diagnostic process. Choosing the display for WSI is critical in the process and requires adequate planning.

Artificial intelligence-based algorithms for the diagnosis of prostate cancer: A systematic review.

OBJECTIVES: The high incidence of prostate cancer causes prostatic samples to significantly affect pathology laboratories workflow and turnaround times (TATs). Whole-slide imaging (WSI) and artificial intelligence (AI) have both gained approval for primary diagnosis in prostate pathology, providing physicians with novel tools for their daily routine. METHODS: A systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was carried out in electronic databases to gather the available evidence on the application of AI-based algorithms to prostate cancer. RESULTS: Of 6290 articles, 80 were included, mostly (59%) dealing with biopsy specimens. Glass slides were digitized to WSI in most studies (89%), roughly two-thirds of which (66%) exploited convolutional neural networks for computational analysis. The algorithms achieved good to excellent results about cancer detection and grading, along with significantly reduced TATs. Furthermore, several studies showed a relevant correlation between AI-identified histologic features and prognostic predictive variables such as biochemical recurrence, extraprostatic extension, perineural invasion, and disease-free survival. CONCLUSIONS: The published evidence suggests that AI can be reliably used for prostate cancer detection and grading, assisting pathologists in the time-consuming screening of slides. Further technologic improvement would help widening AI's adoption in prostate pathology, as well as expanding its prognostic predictive potential.

Discordance of Biomarker Expression Profile between Primary Breast Cancer and Synchronous Axillary Lymph Node Metastasis in Preoperative Core Needle Biopsy.

Background: Breast cancer (BC) is a heterogeneous disease made up of clones with different metastatic potential. Intratumoral heterogeneity may cause metastases to show divergent biomarker expression, potentially affecting chemotherapy response. Methods: We investigated the immunohistochemical (IHC) and FISH profile of estrogen receptors (ER), progesterone (PR) receptors, Ki67, and HER2 in a series of BC-matched primary tumors (PTs) and axillary lymph node (ALN) metastases in pre-operative core needle biopsies (CNBs). Phenotypical findings were correlated to morphological features and their clinical implications. Results: Divergent expression between PTs and ALNs was found in 10% of the tumors, often involving multiple biomarkers (12/31, 39%). Most (52%) displayed significant differences in ER and PR staining. HER2 divergences were observed in almost three-quarters of the cases (23/31, 74%), with five (16%) switching from negativity to overexpression/amplification in ALNs. Roughly 90% of disparities reflected significant morphological differences between PTs and ALN metastases. Less than half of the discrepancies (12/31, 39%) modified pre/post-operative treatment options. Conclusions: We observed relevant discrepancies in biomarker expression between PTs and metastatic ALNs in a noteworthy proportion (10%) of preoperative BC CNBs, which were often able to influence therapies. Hence, our data suggest routine preoperative assessment of biomarkers in both PTs and ALNs in cases showing significant morphological differences.

The Puzzle of Preimplantation Kidney Biopsy Decision-Making Process: The Pathologist Perspective.

Kidney transplantation is the best treatment for end-stage renal disease since it offers the greatest survival benefit compared to dialysis. The gap between the number of renal transplants performed and the number of patients awaiting renal transplants leads to a steadily increasing pressure on the scientific community. Kidney preimplantation biopsy is used as a component of the evaluation of organ quality before acceptance for transplantation. However, the reliability and predictive value of biopsy data are controversial. Most of the previously proposed predictive models were not associated with graft survival, but what has to be reaffirmed is that histologic examination of kidney tissue can provide an objective window on the state of the organ that cannot be deduced from clinical records and renal functional studies. The balance of evidence indicates that reliable decisions about donor suitability must be made based on the overall picture. This work discusses recent trends that can reduce diagnostic timing and variability among players in the decision-making process that lead to kidney transplants, from the pathologist's perspective.

mTOR eosinophilic renal cell carcinoma: a distinctive tumor characterized by mTOR mutation, loss of chromosome 1, cathepsin-K expression, and response to target therapy.

In the spectrum of oncocytic renal neoplasms, a subset of tumors with high-grade-appearing histologic features harboring pathogenic mutations in mammalian target of rapamycin (mTOR) and hitherto clinical indolent behavior has been described. Three cases (2F,1 M) with histologically documented metastases (lymph node, skull, and liver) were retrieved and extensively investigated by immunohistochemistry, FISH, and next-generation sequencing. Tumors were composed of eosinophilic cells with prominent nucleoli (G3 by ISUP/WHO) arranged in solid to nested architecture. Additionally, there were larger cells with perinuclear cytoplasmic shrinkage and sparse basophilic Nissl-like granules, superficially resembling the so-called spider cells of cardiac rhabdomyomas. The renal tumors, including the skull and liver metastases, showed immunoexpression PAX8, CK8-18, and cathepsin-K, and negativity for vimentin. NGS identified mTOR genetic alterations in the three cases, including the skull and liver metastases. One patient was then treated with Everolimus (mTOR inhibitors) with clinical response (metastatic tumor shrinkage). We present a distinct renal tumor characterized by high-grade eosinophilic cells, cathepsin-K immunohistochemical expression, and harboring mTOR gene mutations demonstrating a malignant potential and showing responsiveness to mTOR inhibitors.

Perspective of a Pathologist on Benchmark Strategies for Artificial Intelligence Development in Organ Transplantation.

Transplant pathology of donors is a highly specialized field comprising both the evaluation of organ donor biopsy for the oncological risk transmission and to guide the organ allocation. Timing is critical in transplant procurement since organs must be recovered as soon as possible to ensure the best possible outcome for the recipient. To all this is added the fact that the evaluation of a donor causes difficulties in many cases and the impact of these assessments is paramount, considering the possible recovery of organs that would have been erroneously discarded or, conversely, the possibly correct discarding of donors with unacceptable risk profiles. In transplant pathology histology is still the gold standard for diagnosis dictating the subsequent decisions and course of clinical care. Digital pathology has played an important role in accelerating healthcare progression and nowadays artificial intelligence powered computational pathology can effectively improve diagnostic needs, supporting the quality and safety of the process. Mapping the shape of the journey would suggest a progressive approach from supervised to semi/unsupervised models, which would involve training these models directly for clinical endpoints. In machine learning, this generally delivers better performance, compensating for a potential lack in interpretability. With planning and enough confidence in the performance of learning-based methods from digital pathology and artificial intelligence, there is great potential to augment the diagnostic quality and correlation with clinical endpoints. This may improve the donor pool and vastly reduce diagnostic and prognostic errors that are known but currently are unavoidable in transplant donor pathology.

Pre-Implantation Kidney Biopsies in Extended Criteria Donors: From On Call to Expert Pathologist, from Conventional Microscope to Digital Pathology.

The number of patients awaiting a kidney transplant is constantly rising but lack of organs leads kidneys from extended criteria donors (ECD) to be used to increase the donor pool. Pre-transplant biopsies are routinely evaluated through the Karpinski-Remuzzi score but consensus on its correlation with graft survival is controversial. This study aims to test a new diagnostic model relying on digital pathology to evaluate pre-transplant biopsies and to correlate it with graft outcomes. Pre-transplant biopsies from 78 ECD utilized as single kidney transplantation were scanned, converted to whole-slide images (WSIs), and reassessed by two expert nephropathologists using the Remuzzi-Karpinski score. The correlation between graft survival at 36 months median follow-up and parameters assigned by either WSI or glass slide score (GSL) by on-call pathologists was evaluated, as well as the agreement between the GSL and the WSIs score. No relation was found between the GSL assessed by on-call pathologists and graft survival (P = 0.413). Conversely, the WSI score assigned by the two nephropathologists strongly correlated with graft loss probability, as confirmed by the ROC curves analysis (DeLong test P = 0.046). Digital pathology allows to share expertise in the transplant urgent setting, ensuring higher accuracy and favoring standardization of the process. Its employment may significantly increase the predictive capability of the pre-transplant biopsy evaluation for ECD, improving the quality of allocation and patient safety.

Revolutionizing Cancer Research: The Impact of Artificial Intelligence in Digital Biobanking.

BACKGROUND: Biobanks are vital research infrastructures aiming to collect, process, store, and distribute biological specimens along with associated data in an organized and governed manner. Exploiting diverse datasets produced by the biobanks and the downstream research from various sources and integrating bioinformatics and "omics" data has proven instrumental in advancing research such as cancer research. Biobanks offer different types of biological samples matched with rich datasets comprising clinicopathologic information. As digital pathology and artificial intelligence (AI) have entered the precision medicine arena, biobanks are progressively transitioning from mere biorepositories to integrated computational databanks. Consequently, the application of AI and machine learning on these biobank datasets holds huge potential to profoundly impact cancer research. METHODS: In this paper, we explore how AI and machine learning can respond to the digital evolution of biobanks with flexibility, solutions, and effective services. We look at the different data that ranges from specimen-related data, including digital images, patient health records and downstream genetic/genomic data and resulting "Big Data" and the analytic approaches used for analysis. RESULTS: These cutting-edge technologies can address the challenges faced by translational and clinical research, enhancing their capabilities in data management, analysis, and interpretation. By leveraging AI, biobanks can unlock valuable insights from their vast repositories, enabling the identification of novel biomarkers, prediction of treatment responses, and ultimately facilitating the development of personalized cancer therapies. CONCLUSIONS: The integration of biobanking with AI has the potential not only to expand the current understanding of cancer biology but also to pave the way for more precise, patient-centric healthcare strategies.

Validation of real-time prostatic biopsies evaluation with fluorescence laser confocal microscopy.

BACKGROUND: Routine processing of prostate biopsies requires conventional steps that usually take a few days. The aim of this study was to validate the use of fluorescence laser confocal microscopy (FCM) for real-time diagnostics. METHODS: We prospectively tested images from prostate needle biopsies (75 images were evaluated by FCM and conventional slides). Two pathologists reviewed the images and assessed agreements between FCM versus conventional slides and between pathologists (κ-values). Interpretation was performed on digital images from the VivaScope 2500 confocal microscope (MAVIG GmbH, Munich, Germany; Caliber I.D., Rochester, NY, USA) placed in the urological operating room. Cancerous versus benign tissue was the primary focus, then the application of the grading system. RESULTS: Cancer was diagnosed in 24 conventional slides (on 75 images) in which agreement among pathologists was high for both conventional (κ=0.96) and FMC (κ=0.84). 1/24 (4%) was ISUP/WHO grade group I, 12/24 (50%) II, 8/24 (33%) III, 2/24 (8%) IV and 1/24 (4%) grade V. Near perfect agreement was obtained for grades I, IV and V (κ=0.85). Grade III values achieved a moderate agreement (κ=0.55). The mean time for laser scanning was 9 minutes. For the remaining non-tumor images, agreement was nearly perfect (κ=0.81). CONCLUSIONS: We validated the use of FCM for real-time cancer detection in prostate biopsies.

Digital Examination of LYmph node CYtopathology Using the Sydney system (DELYCYUS): An international, multi-institutional study.

BACKGROUND: After a series of standardized reporting systems in cytopathology, the Sydney system was recently introduced to address the need for reproducibility and standardization in lymph node cytopathology. Since then, the risk of malignancy for the categories of the Sydney system has been explored by several studies, but no studies have yet examined the interobserver reproducibility of the Sydney system. METHODS: The authors assessed interobserver reproducibility of the Sydney system on 85 lymph node fine-needle aspiration cytology cases reviewed by 15 cytopathologists from 12 institutions in eight different countries, resulting in 1275 diagnoses. In total, 186 slides stained with Diff-Quik, Papanicolaou, and immunocytochemistry were scanned. A subset of the cases included clinical data and results from ultrasound examinations, flow cytometry immunophenotyping, and fluorescence in situ hybridization analysis. The study participants assessed the cases digitally using whole-slide images. RESULTS: Overall, the authors observed an almost perfect agreement of cytopathologists with the ground truth (median weighted Cohen κ = 0.887; interquartile range, κ = 0.210) and moderate overall interobserver concordance (Fleiss κ = 0.476). There was substantial agreement for the inadequate and malignant categories (κ = 0.794 and κ = 0.729, respectively), moderate agreement for the benign category (κ = 0.490), and very slight agreement for the suspicious (κ = 0.104) and atypical (κ = 0.075) categories. CONCLUSIONS: The Sydney system for reporting lymph node cytopathology shows adequate interobserver concordance. Digital microscopy is an adequate means to assess lymph node cytopathology specimens.

Histology for nephrology, from pre-implantation to post-transplant kidney biopsy. Lesson learned from ReBIrth (Renal BIopsy for Kidney Transplantation Therapy).

A meeting entitled Renal BIopsy for Kidney Transplantation Therapy (ReBIrth) took place on May 31st, 2022 in Bologna, Italy. The meeting drew together nephrologists, surgeons, and pathologists and recognized as experts in the field of kidney transplantation in Italy. In this paper, we present our experience working with kidney transplants in the current era of immunosuppression therapy. The primary aim is to report the histopathological characteristics of failed kidney allografts after a consensus of experts reviewed the cases on a wholeslide imaging digital platform. Regardless of the cases discussed, digital pathology was reliable in identifying all the morphological and immunohistochemical features required to improve the correct use of immunosuppressive therapy to prevent graft failure and optimize patient management.

Value of Artificial Intelligence in Evaluating Lymph Node Metastases.

One of the most relevant prognostic factors in cancer staging is the presence of lymph node (LN) metastasis. Evaluating lymph nodes for the presence of metastatic cancerous cells can be a lengthy, monotonous, and error-prone process. Owing to digital pathology, artificial intelligence (AI) applied to whole slide images (WSIs) of lymph nodes can be exploited for the automatic detection of metastatic tissue. The aim of this study was to review the literature regarding the implementation of AI as a tool for the detection of metastases in LNs in WSIs. A systematic literature search was conducted in PubMed and Embase databases. Studies involving the application of AI techniques to automatically analyze LN status were included. Of 4584 retrieved articles, 23 were included. Relevant articles were labeled into three categories based upon the accuracy of AI in evaluating LNs. Published data overall indicate that the application of AI in detecting LN metastases is promising and can be proficiently employed in daily pathology practice.

STING is a prognostic factor related to tumor necrosis, sarcomatoid dedifferentiation, and distant metastasis in clear cell renal cell carcinoma.

STING is a molecule involved in immune reactions against double-stranded DNA fragments, released in infective and neoplastic diseases, whose role in the interactions between immune and neoplastic cells in clear cell renal cell carcinoma has not been studied yet. We investigated the immunohistochemical expression of STING in a series of 146 clear-cell renal cell carcinomas and correlated it with the main pathological prognostic factors. Furthermore, tumoral inflammatory infiltrate was evaluated and studied for the subpopulations of lymphocytes. Expression of STING was observed in 36% (53/146) of the samples, more frequently in high-grade (G3-G4) tumors (48%,43/90) and recurrent/metastatic ones (75%, 24/32) than in low grade (G1-G2) and indolent neoplasms (16%, 9/55). STING staining correlated with parameters of aggressive behavior, including coagulative granular necrosis (p = 0.001), stage (p < 0.001), and development of metastases (p < 0.001). Among prognostic parameters, STING immune expression reached an independent statistical significance (p = 0.029) in multivariable analysis, along with the stage and the presence of coagulative granular necrosis. About tumor immune-environment, no significant statistical association has been demonstrated between tumor-infiltrating lymphocytes and STING. Our results provide novel insights regarding the role of STING in aggressive clear cell renal cell carcinomas, suggesting its adoption as a prognostic marker and a potentially targetable molecule for specific immunotherapies.

Prognostic value of major pathological response following neoadjuvant therapy for non resectable pancreatic ductal adenocarcinoma.

BACKGROUND: The aim of this study is to evaluate the impact of major pathological response on overall survival (OS) in borderline resectable and locally advanced pancreatic ductal adenocarcinoma following neoadjuvant treatment, and to identify predictors of major pathological response. METHODS: Patients surgically resected following neoadjuvant treatment between 2010 and 2020 at the Pederzoli Hospital were retrospectively analyzed. Pathologic response was assessed using the College of American Pathologists (CAP) score, and major pathological response was defined as CAP 0-1. OS was estimated and compared using the Kaplan-Meier method and log-rank test. A logistic and Cox regression model were performed to identify predictors of major pathologic response and OS. RESULTS: Overall, 200 patients were included in the study. A major and complete pathological response were observed in 52(26.0%) and 15(7.3%) patients respectively. The 1-, 3-, 5-year OS was 92.7, 67.2, and 41.7%, and 71.0, 37.4, and 20.8% in patients with or without major pathologic response respectively (log-rank test p < 0.001). Major pathologic response was confirmed as independent predictor of OS (OR 0.50 95%CI 0.29-0.88, p = 0.01). Post-treatment CA19-9 normalization (OR 4.20 95%CI 1.14-10.35, p = 0.02) and radiological post-treatment tumor residual size<25 mm (OR 2.71 95%CI 1.27-5.79, p = 0.01) were found to be independent predictors of major pathologic response. CONCLUSION: Patients experienced a major pathological response after neoadjuvant treatment have an increased survival, and major pathologic response is an independent predictor of OS. A normal CA19-9 value and radiological tumor size at restaging are confirmed to be independent predictors of major pathologic response.

Effect of Radio-Chemotherapy on PD-L1 Immunohistochemical Expression in Head and Neck Squamous Cell Carcinoma.

BACKGROUND: Programmed death-ligand 1 (PD-L1) checkpoint inhibitors represent a mainstay of therapy in head and neck squamous cell cancer (HNSCC). However, little is known about the influence of combined therapy on PD-L1 expression. The study aims to gather evidence on this topic. METHODS: A systematic search was carried out in electronic databases Pubmed-MEDLINE and Embase to retrieve studies on the comparison of PD-L1 expression before and after conventional therapy. Data were extracted and a quantitative analysis with pooled odds ratios (ORs) was performed when applicable. RESULTS: Of 5688 items, 15 were finally included. Only a minority of studies assessed PD-L1 with the recommended combined positive score (CPS). The results are highly heterogeneous, with some studies reporting an increase in PD-L1 expression and others reporting a decrease. Three studies allowed for quantitative analysis and showed a pooled OR of 0.49 (CI 0.27-0.90). CONCLUSIONS: From the present evidence, a clear conclusion towards an increase or decrease in PD-L1 expression after combined therapy cannot be drawn, but even with few studies available, a trend towards an increase in expression in tumor cells at a cutoff of 1% can be noted in patients undergoing platinum-based therapy. Future studies will provide more robust data on the effect of combined therapy on PD-L1 expression.

Well-differentiated neuroendocrine tumor of the urinary bladder expressing GATA 3.

Neuroendocrine neoplasms of the urinary bladder are uncommon tumors represented by small-cell neuroendocrine carcinoma and by fewer cases of large-cell neuroendocrine carcinomas and well-differentiated neuroendocrine tumors. Less than 30 examples of this latter entity have been published so far and consisted of clinically indolent lesions mainly located in the bladder neck arranged in a pseudo-glandular architecture often associated with reactive urothelial changes like cystitis cystica/glandularis. Due to their infrequency, pathologists may face difficulty to recognize this proliferation considering it as part of cystitis cystica/glandularis or misinterpreting it as nested urothelial carcinoma, paraganglioma, or secondary bladder involvement by prostatic adenocarcinoma. Herein the case of a 51-year-old female diagnosed with a well-differentiated neuroendocrine tumor of the bladder immunohistochemically expressing GATA3 is reported, pointing out either the pitfall in the differential diagnosis with cystitis cystica/glandularis, nested urothelial carcinoma, and paraganglioma or its usefulness in the differential diagnosis with prostatic adenocarcinoma.

Hot topics in renal cancer pathology: implications for clinical management.

INTRODUCTION: The updated European Association of Urology (EAU) Guidelines issued a weak recommendation for adjuvant pembrolizumab for patients with high-risk operable clear cell Renal Cell Carcinoma (ccRCC). High risk of recurrence was defined, as per protocol-criteria, as T2 with nuclear grade 4 or sarcomatoid differentiation, T3 or higher, regional lymph node metastasis, or stage M1 with no evidence of disease. Considering the heterogeneous population included in the recommendation, it has been questioned if adjuvant pembrolizumab may lead to overtreatment of some patients as well as undertreatment of patients with worse prognosis. AREAS COVERED: In this review, we discuss the issues related to the assessment of pathological features required to identify those patients harboring a high-risk tumor, highlighting the issue related to interobserver variability and discuss the currently available prognostic scoring systems in ccRCC. EXPERT OPINION: PPathologist assessment of prognostic features suffers from interobserver variability which may depend on gross sampling and the pathologist's expertise. The presence of clear cell feature is not sufficient criteria by itself to define ccRCC since clear cell can be also found in other histotypes. Application of molecular biomarkers may be useful tools in the near future to help clinicians identify patients harboring tumors with worse prognosis.