Elevated Microsatellite Alterations at Selected Tetranucleotides (EMAST) Is Not Attributed to MSH3 Loss in Stage I-III Colon cancer: An Automated, Digitalized Assessment by Immunohistochemistry of Whole Slides and Hot Spots

Martin M Watson, Dordi Lea, Hanne R Hagland, Kjetil Søreide, Martin M Watson, Dordi Lea, Hanne R Hagland, Kjetil Søreide

Abstract

Introduction: EMAST is a poorly understood form of microsatellite instability (MSI) in colorectal cancer (CRC) for which loss of MSH3 has been proposed as the underlying mechanism, based on experimental studies. We aimed to evaluate whether MSH3 loss is associated with EMAST in CRC.

Methods: A consecutive cohort of patients with stage I-III CRC. Digital image analysis using heatmap-derived hot spots investigated MSH3 expression by immunohistochemistry. Fragment analysis of multiplex PCR was used to assess MSI and EMAST, and results cross-examined with MSH3 protein expression.

Results: Of 152 patients, EMAST was found in 50 (33%) and exclusively in the colon. Most EMAST-positive cancers had instability at all 5 markers, and EMAST overlapped with MSI-H in 42/50 cases (84%). The most frequently altered tetranucleotide markers were D8S321 (38.2% of tumors) and D20S82 (34.4%). Subjective evaluation of MSH3 expression by IHC in tumor found ≤10% negative tumor cells in all samples, most being ≤5% negative. Digital analysis improved the detection but showed a similar spread of MSH3 loss (range 0.1-15.7%, mean 2.2%). Hotspot MSH3 negativity ranged between 0.1 to 95.0%, (mean 8.6%) with significant correlation with the whole slide analysis (Spearman's rho=0.677 P<.001). Loss of MSH3 expression did not correlate with EMAST.

Conclusions: In a well-defined cohort of patients with CRC, loss of MSH3 was not associated with EMAST. Further investigation into the mechanisms leading to EMAST in CRC is needed.

Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.

Figures

Figure 1
Figure 1
MSH3 immunohistochemistry virtual image analysis process. (A-C) An initial gross exclusion of stroma, tissue folds and normal tissue is carried out, selecting a “work area” where an app-based algorithm is then run to specifically mark tumor cells and exclude stroma. This results in a highlighted region of interest (ROI, marked in blue); (D) A second app-based algorithm classifies cells on the basis of their positivity (green) or negativity (blue) for the MSH3 protein; (E-F) A heatmap is created to highlight areas on the whole slide where the highest concentration of negative cells are located; (G) Based on the heatmap created in (E), a 0.8 mm2 round ROI (hotspot, light blue circle) is placed and becomes the focus of the analysis; (H) Fully classified, hotspot-derived ROI.
Figure 2
Figure 2
EMAST analysis. Electropherograms of multiplex PCR fragment analysis are shown for (A) an EMAST-negative and (B) an EMAST-positive patient. Arrows indicate extra PCR products at +/− 4n bp in unstable markers. (C) Stacked bar population graph showing frequency of instability (red) at each EMAST marker, in EMAST-positive and EMAST-negative populations. (D) bar chart showing proportions of patients grouped by total number of unstable EMAST markers. For patients bearing only 1 marker mutated (not EMAST, according to our thresholds) the bar is stacked to specify each marker's abundance.
Figure 3
Figure 3
Digitalized evaluation of MSH3 expression. (A) The entire cohort was scored by an experienced pathologist as >90% positive for MSH3 (majority >95%). (B) With the help of digitalized hotspot analysis, small areas where a higher proportion of negative cells were found in all the slides. (C) Within most MSH3-positive cells, some nuclei exhibited heterogeneous staining.

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Source: PubMed

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