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Pretzsch, Elise; Boesch, Florian; Todorova, Rumyana; Niess, Hanno; Jacob, Sven; Guba, Markus; Kirchner, Thomas; Werner, Jens; Klauschen, Frederick; Angele, Martin K. and Neumann, Jens (2022): Molecular subtyping of gastric cancer according to ACRG using immunohistochemistry - Correlation with clinical parameters. In: Pathology, Research and Practice, Vol. 231, 153797

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Background: Gastric cancer (GC) is a very heterogenous disease necessitating further stratification for prognostic and therapeutic aspects. Based on the recommendation of The Asisan Cancer Research Group (ACRG) recently established four molecular subtypes (MSI, MSS/EMT, MSS/TP53+, MSS/TP53-) which require molecular expression analysis. The technology required for comprehensive molecular analysis is expensive and not applicable for routine diagnostics. Thus, in this study we established a classification system utilizing immunohistochemistry and morphology-based analyses as surrogate markers in order to reproduce the ACRG molecular subtypes of gastric cancer. To clarify the clinical relevance of the novel classification system, we performed a correlation with established clinical parameters. Methods: The study cohort consisted of 189 patients with GC (UICC III and IV). Using immunohistochemistry, the following markers were analysed: MLH1, MSH2, MSH6, PMS2 (as a surrogate for microsatellite status), p53, SOX9. We assessed tumor budding as a surrogate for EMT to distinguish between MSS/EMT and MSS/non-EMT groups. Results: Immunohistochemical and morphologic subtyping classified cases as follows: 10% MSI, 35% MSS/EMT, 16% MSS/TP53 + and 39% MSS/TP53-. Subtypes significantly correlated with the Lauren classification, tumor stage, venous invasion and SOX9 expression (p < .05). There was no significant correlation between molecular subtype and lymph node growth pattern. Conclusion: We propose a simple algorithm for molecular subtyping of GC using universally available immunohistochemistry, which correlates with clinical parameters and is cost-effective and applicable in diagnostic routine. This classification might prospectively help to determine patient prognosis, optimize patient care and homogenize patient cohorts for clinical trials.

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