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Demonstrating the interference of tissue processing in the evaluation oftissue biomarkers: The case of PD-L1


Ana Caramelo, Antonio Polonia, Joao Vale, Monica Curado, Sofia Campelos, Vanessa Nascimento, Mariana Barros, Diana Ferreira, Tania Pereira, Beatriz Neves, Catarina Eloy


Pathology - Research and Practice


DESCRIPTION

The immunohistochemical (IHC) expression of PD-L1 in cancer models is used as a predictive biomarker of response to immunotherapy. We aimed to evaluate the impact of the usage of 3 different tissue processors in the IHC expression of PD-L1 antibody clones: 22C3 and SP142.

Three different topographies of samples (n = 73) were selected at the macroscopy room: 39 uterine leiomyomas, 17 placentas and 17 palatine tonsils.

Three fragments were collected from each sample and were inked with a specific color that represented their separate processing in a different tissue processor (A, B or C).

During embedding, the 3 fragments with distinct processing were ensemble in the same cassette for sectioning of 3 slides/each: hematoxylin-eosin, 22C3 PDL1 IHC staining and SP142 PD-L1 IHC staining, that were blindly observed by 2 pathologists under digital environment.
All but one set of 3 fragments were considered adequate for observation even in the presence of artifacts associated with processing issues that were recorded as high as 50.7 % for processor C.
The occurrence of background non-specific staining and the presence of false positive results appear to be unrelated with the PD-L1 clone or the type of tissue processing.
22C3 PD-L1 was more frequently considered adequate for evaluation than SP142 PD-L1 that, in 29.2 % of WSIs (after tissue processor C) were considered not adequate for observation due to lack of the typical pattern of expression.

Similarly, the intensity of PD-L1 staining was significantly decreased in fragments processed by C (both PD-L1 clones) in tonsil and placenta specimens, and by A (both clones) in comparison with those processed by B.
This study demonstrates the need to standardize the tissue processing in pathology to cope with the growing needs of precision medicine quantifications and the production of high-quality material necessary for computational pathology usage.


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