Abstract

Deficiencies in Mismatch Repair (MMR) proteins are one of the major pathways in the development of colorectal cancer (CRC). MMR status evaluation is recommended in every new CRC patient. However, this is not fully implemented due to high costs. Tissue microarray (TMA) enables allocating tissue cores from few specimens to a single paraffin block. The primary objective of this study was to evaluate the accuracy of TMA MMR immunohistochemistry (IHC) compared to whole slide. The secondary objective was to evaluate and validate automatic digital image analysis software in differentiating pathological and normal TMA cores. Pathological cores were defined if at least one MMR protein was unstained. Tumoral and normal tissue of 11 CRC patients with known MMR status was used to obtain 623 TMA cores. The MMR staining of each core was evaluated by a pathologist and compared to the whole slide result. Digital analysis software by 3DHistech Ltd. was used to identify cell nucleus and quantify nuclear staining in 323 tissue cores. To identifying pathological tissue, cores the cohort was divided into a test (N = 146 cores) and validation sets (N = 177 cores). A staining intensity score (SIS) was developed, and its performance compared to the pathologist review of each core and to the whole slide result. Compared to the whole slide, the pathologist's assessment had 100% sensitivity (n/N = 112/112) and 100% specificity (n/N = 278/278) with 95% lower limit of 97 and 99% respectively. The area under the receiver operating characteristic (ROC) curve of SIS was 77%. A cutoff of 55 was obtained from the ROC curve. By implementing the cutoff in the validation dataset, the SIS had sensitivity and specificity of 98.2% [90.1-100%] and 58.5% [49.3-67.4%] respectively. The MMR status of CRC can be evaluated in TMA tissue cores thus potentially reducing MMR testing costs. The SIS can be used as triage indicator during pathologic review. Institutional ethical approval was granted for the performance of this study (Emek Medical Center Ethics ID: EMC-19-0179).

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