Application and Pitfalls of Immunohistochemistry in Diagnosis of Challenging Genitourinary Cases

Immunohistochemical Staining Characteristics of Low-Grade Invasive Ductal Carcinoma Using the ADH5 Cocktail (CK5/14, P63, and CK7/18): A Potential Interpretative Pitfall

Background: In our practice, the antibody cocktail ADH5 (CK5/14, p63, and CK7/18) helps with diagnostic challenges, such as identifying microinvasion and foci of invasive carcinoma, differentiating atypical ductal hyperplasia from hyperplasia of the usual type, and distinguishing basal phenotypes in triple-negative carcinomas. However, the ADH5 cocktail does have pitfalls and caveats. Methods: We describe our experience with the ADH5 cocktail of antibodies in breast pathology. Institutional knowledge and a literature search form our data sources. Results: We analyzed 44 cases. Four out of a total of 44 cases (9.1%)-two tubular carcinomas and two low-grade invasive breast carcinomas of no special type (ductal) with tubular features-showed an expected pattern of staining for ADH5 with a loss of brown (P63, CK5/14) staining around invasive glands and diffuse red (CK7/18) expression. Forty out of 44 (90.9%) cases showed an unexpected staining pattern (mixture of cytoplasmic brown and red). All 44 cases (100%) showed negative myoepithelial staining around invasive foci when separately stained for P63 and SMMH (Smooth Muscle Myosin Heavy). Conclusions: The unexpected staining pattern of ADH5 in low-grade invasive ductal carcinomas can be challenging to interpret in these lesions with low-grade cytology. The occurrence can cause confusion among users who employ multiplex stains, and it is important for users to be aware of this potential pitfall.

Computer-assisted tumor grading, validation of PD-L1 scoring, and quantification of CD8-positive immune cell density in urothelial carcinoma, a visual guide for pathologists using QuPath

Background

Advances in digital imaging in pathology and the new capacity to scan high-quality images have change the way to practice and research in surgical pathology. QuPath is an open-source pathology software that offers a reproducible way to analyze quantified variables. We aimed to present the functionality of biomarker scoring using QuPath and provide a guide for the validation of pathologic grading using a series of cases of urothelial carcinomas.

Methods

Tissue microarrays of urothelial carcinomas were constructed and scanned. The images stained with HE, CD8 and PD-L1 immunohistochemistry were imported into QuPath and dearrayed. Training images were used to build a grade classifier and applied to all cases. Quantification of CD8 and PD-L1 was undertaken for each core using cytoplasmic and membrane color segmentation and output measurement and compared with pathologists semi-quantitative assessments.

Results

There was a good correlation between tumor grade by the pathologist and by QuPath software (Kappa agreement 0.73). For low-grade carcinomas (by the report and pathologist), the concordance was not as high. Of the 32 low-grade tumors, 22 were correctly classified as low-grade, but 11 (34%) were diagnosed as high-grade, with the high-grade to the low-grade ratio in these misclassified cases ranging from 0.41 to 0.58. The median ratio for bona fide high-grade carcinomas was 0.59. Some of the reasons the authors list as potential mimickers for high-grade cases are fulguration artifact, nuclear hyperchromasia, folded tissues, and inconsistency in staining. The correlation analysis between the software and the pathologist showed that the CD8 marker showed a moderate (r = 0.595) and statistically significant (p < 0.001) correlation. The internal consistency of this parameter showed an index of 0.470. The correlation analysis between the software and the pathologist showed that the PDL1 marker showed a robust (r = 0.834) and significant (p < 0.001) correlation. The internal consistency of this parameter showed a CCI of 0.851.

Conclusions

We were able to demonstrate the utility of QuPath in identifying and scoring tumor cells and IHC quantification of two biomarkers. The protocol we present uses a free open-source platform to help researchers deal with imaging and data processing in the surgical pathology field.