Practical Applications of Immunohistochemistry in the Diagnosis of Genitourinary Tumors

Xiao, Xiuli; Hu, Rong; Deng, Fang; Shen, Steven S.; Yang, Ximing J.; Wu, Chin Lee

doi:10.5858/arpa.2016-0530-ra

Cited by 15 publications

(11 citation statements)

References 125 publications

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“…CK7 expression was observed in both healthy and neoplastic cells and CK7 staining has prognostic value in an IHC-based analysis of renal cell neoplasms (34, 35). In addition, both chromophobe RCC and clear cell papillary RCC are typically positive for CK7, while conventional ccRCC is usually not, which grants it pivotal importance in the differential diagnosis among clear cell renal neoplasms (36). In 2018, Gonzalez et al suggested that CK7 immunoreactivity in ccRCC is variable and the extent of staining depends on the clinical-histopathological parameters including grade and architectural growth patterns of the tumors (37).…”

Section: Discussionmentioning

confidence: 99%

An Integrated Score and Nomogram Combining Clinical and Immunohistochemistry Factors to Predict High ISUP Grade Clear Cell Renal Cell Carcinoma

et al. 2018

Front. Oncol.

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Objective: The International Society of Urological Pathology (ISUP) has proposed a grading system to classify renal cell carcinoma (RCC). However, classification using biopsy specimens remains problematic and, consequently, the accuracy of a biopsy-based diagnosis is relatively poor. This study aims to combine clinical and immunohistochemical (IHC) factors for the prediction of high ISUP grade clear cell RCC (ccRCC) in an attempt to complement and improve the accuracy of a biopsy-based diagnosis.Methods: A total of 362 ccRCC patients were enrolled in this study and used for the training set. We performed IHC analysis of 18 protein markers on standard tissue sections using an automated stainer. Multivariate logistic regression models were developed to evaluate independent predictors for high ISUP grade. We evaluated different prediction models using receiver operating characteristic (ROC) curves and area under the ROC curve (AUC) analysis. A nomogram for the derivation of an integrated score for predicting high ISUP grade ccRCC and a calibration curve were also plotted. Finally, an internal validation cohort was examined to evaluate the performance of our integrated scoring system and nomogram.Results: Multivariate logistic analyses revealed seven credible candidates for predicting high grade ISUP. These were age, tumor diameter, surgery, and CK7, Ki-67, PTEN, and MTOR protein expression. The ROC curves for the clinical, IHC and integrated models were compared in the training set, and the AUC for each was 0.731, 0.744, and 0.801, respectively. DeLong's test showed that the integrated model was significantly better at predicting high ISUP grade, when compared with the other models. Internal validation confirmed the good performance of the integrated score in predicting ISUP grade.Conclusion: We have developed a nomogram integrating clinical and immunohistochemical parameters to predict high ISUP grade for M0 ccRCC patients. This nomogram may offer potentially useful information during preoperative individualized patient risk assessment, and consequently may help urologists when planning personalized management regimens.

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Section: Discussionmentioning

confidence: 99%

An Integrated Score and Nomogram Combining Clinical and Immunohistochemistry Factors to Predict High ISUP Grade Clear Cell Renal Cell Carcinoma

et al. 2018

Front. Oncol.

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“…These RCC subtypes include clear-cell tumors, such as clear-cell carcinoma (ccRCC), chromophobe RCC (ChRCC), clear-cell papillary RCC (CCPRCC), and microphthalmos translocation family RCC (MiT RCC). Alternatively, eosinophilic tumors can be seen in papillary RCC (PRCC), CCRCC, ChRCC, eosinophilic variants, renal oncocytoma (RO), and acquired cystic disease RCC (ACD-RCC) [1][2][3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Immunoprofiles of Renal Cell Carcinoma Subtypes

Kim

Joo

Lee

et al. 2020

Cancers

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In recent years, renal epithelial tumors have been among the fastest reclassifying tumors, requiring updates to the tumor classification system. Nonetheless, immunohistochemistry (IHC) remains the most widely used tool for renal epithelial tumors. In this proposal, we aimed to create the most efficient IHC panel for categorizing the diverse subtypes of renal tumors, and to find out more specific immunohistochemical results in each subtype or each antibody. A total of 214 renal tumors were analyzed using 10 possible IHC markers to differentiate subtypes, including three major renal cell carcinoma (RCC) subtypes, clear-cell type (50 cases), papillary type (50 cases), and chromophobe type (20 cases), and minor subtypes (MiT RCC, 13 cases; collecting duct carcinoma, 5 cases; and oncocytoma, 10 cases). A triple immunomarker (cytokeratin 7 (CK7)-carbonic anhydrase IX (CAIX)- alpha-methylacyl-CoA racemase (AMACR)) panel is useful in particular high-grade clear-cell tumors. If IHC remains ambiguous, the use of an adjunctive panel can be suggested, including CD10, epithelial membrane antigen, cathepsin K, c-kit, hepatocyte nuclear factor 1-β, and E-cadherin. For an efficient immunohistochemical strategy for subtyping of RCC, we conclude that the CK7-CAIX-AMACR panel is the best primary choice for screening subtyping.

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“…The 4 most common types of RCC are clear cell RCC, papillary RCC, chromophobe RCC, and recently recognized clear cell papillary RCC. Immunohistochemical workup of renal cell neoplasms has been thoroughly reviewed previously 31 ; however, new entities have emerged in recent years. 32,33 These new tumors are rare and can be difficult to diagnose without special immunohistochemical and/or molecular studies.…”

Section: Kidneymentioning

confidence: 99%

Application and Pitfalls of Immunohistochemistry in Diagnosis of Challenging Genitourinary Cases

Ross

Yang

2020

Archives of Pathology &Amp; Laboratory Medicine

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Context.— Immunohistochemistry (IHC) has become increasingly important in the evaluation of pathologic conditions in the genitourinary (GU) organs. In addition to careful evaluation of hematoxylin-eosin sections and generation of a differential diagnosis, choosing the optimal panel of IHC markers becomes even more important when the biopsy material is very limited. The following summary of our experience supplemented with relevant literature review exemplifies how to use IHC to facilitate pathologic diagnosis in the GU system. Objective.— To describe our experience with the most common immunohistochemical markers used in GU pathology. Data Sources.— Institutional experience and literature search comprise our data sources. Conclusions.— Application of IHC provides enormous benefits to the interpretation of GU pathologic conditions, including benign and malignant lesions. However, both insufficient and excessive types of use of IHC, as well as incorrect interpretations in common and rare GU conditions, could present pitfalls in diagnosis.

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Practical Applications of Immunohistochemistry in the Diagnosis of Genitourinary Tumors

Cited by 15 publications

References 125 publications

An Integrated Score and Nomogram Combining Clinical and Immunohistochemistry Factors to Predict High ISUP Grade Clear Cell Renal Cell Carcinoma

An Integrated Score and Nomogram Combining Clinical and Immunohistochemistry Factors to Predict High ISUP Grade Clear Cell Renal Cell Carcinoma

Comprehensive Immunoprofiles of Renal Cell Carcinoma Subtypes

Application and Pitfalls of Immunohistochemistry in Diagnosis of Challenging Genitourinary Cases

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