TY - JOUR
T1 - Computer-Aided Diagnostics Helps Accurately Determine Different Expression Levels of Claudin-18.2 in Gastric Cancer
AU - Köfler, Sabina
AU - Mühlberger, Katharina
AU - Girkinger, Verena
AU - Liu, Drolaiz H W
AU - Dislich, Bastian
AU - Gloor, Beat
AU - Langer, Rupert
PY - 2025/4/23
Y1 - 2025/4/23
N2 - INTRODUCTION: Determination of claudin-18.2 expression by immunohistochemistry (IHC) is a prerequisite for targeted treatment of gastric cancers (GCs) with zolbetuximab. Precise assessment of IHC expression categories, however, may be challenging and prone to interobserver variability. Computer-aided diagnosis has a high potential of improving diagnostic accuracy and reproducibility. We established a computer-aided analysis tool for claudin-18.2 positivity scoring. METHODS: Analysis steps included the identification of tumour tissue on haematoxylin-3,3'-diaminobenzidine-stained tissue microarray (TMA) slides, cell segmentation, and membranous staining intensity estimation of claudin-18.2 (clone 43-14A). We analysed 2,248 cores from 417 primary resected GCs with detailed pathological data available. RESULTS: In 51.6% (1,159/2,248) of TMA cores, no stained tumour cells were detected. Among cases with claudin-18.2 expression, predominantly 1+ and 2+ cells, a minority of 3+ stained cells were found, and 2+ to 3+ staining was unevenly distributed. Utilizing the SPOTLIGHT claudin-18.2 positivity threshold, we identified 12% (187/1,555) positive cores corresponding to 2.5% (9/365) positive cases. Lower staining intensities in tumour centre cores point to intratumoural heterogeneity. CONCLUSION: Computer-aided diagnostics helps accurately measure claudin-18.2 expression levels, allowing to precisely determine claudin-18.2 status in GC patients. Previously uncaptured categorization of staining intensities may enhance the understanding of claudin-18.2 threshold for patient stratification.
AB - INTRODUCTION: Determination of claudin-18.2 expression by immunohistochemistry (IHC) is a prerequisite for targeted treatment of gastric cancers (GCs) with zolbetuximab. Precise assessment of IHC expression categories, however, may be challenging and prone to interobserver variability. Computer-aided diagnosis has a high potential of improving diagnostic accuracy and reproducibility. We established a computer-aided analysis tool for claudin-18.2 positivity scoring. METHODS: Analysis steps included the identification of tumour tissue on haematoxylin-3,3'-diaminobenzidine-stained tissue microarray (TMA) slides, cell segmentation, and membranous staining intensity estimation of claudin-18.2 (clone 43-14A). We analysed 2,248 cores from 417 primary resected GCs with detailed pathological data available. RESULTS: In 51.6% (1,159/2,248) of TMA cores, no stained tumour cells were detected. Among cases with claudin-18.2 expression, predominantly 1+ and 2+ cells, a minority of 3+ stained cells were found, and 2+ to 3+ staining was unevenly distributed. Utilizing the SPOTLIGHT claudin-18.2 positivity threshold, we identified 12% (187/1,555) positive cores corresponding to 2.5% (9/365) positive cases. Lower staining intensities in tumour centre cores point to intratumoural heterogeneity. CONCLUSION: Computer-aided diagnostics helps accurately measure claudin-18.2 expression levels, allowing to precisely determine claudin-18.2 status in GC patients. Previously uncaptured categorization of staining intensities may enhance the understanding of claudin-18.2 threshold for patient stratification.
KW - Claudin-18.2 assessment
KW - Computer-aided diagnostics
KW - Digital pathology
KW - Gastric cancer
U2 - 10.1159/000545769
DO - 10.1159/000545769
M3 - Article
SN - 1015-2008
SP - 1
EP - 11
JO - Pathobiology
JF - Pathobiology
ER -