Immunohistochemistry-based molecular classification using TCGA and ACRG Algorithm in locally advanced and metastatic gastric cancer

Background Gastric cancer is a heterogeneous disease with varying clinical outcomes and treatment responses, so the present study aimed to classify gastric cancer using immunohistochemistry based molecular subtyping aligned with the cancer genome atlas (TCGA) and Asian cancer research group (ACRG) algorithm. IHC offers a cost-effective and widely accessible alternative to next-generation sequencing Methods A retrospective analysis of 191 GC patients assessed for EBV, MSI, p53, E-cadherin, and PI3K by IHC based Molecular classification (TCGA and ACRG) and correlated with clinic pathological features and survival. Results A total of 191 patients were included with EBV positivity (18.3%), MSI (17.3%), p53 aberration (13.1%), and E-cadherin loss (29.3%) were observed. p53 aberration was associated with higher age (> 60 yrs), E- cadherin negative with diffuse histology and antro-pyloric region as predominant site. MSI with intestinal histology and antro-pyloric region as predominant site with MSI. TCGA classification revealed EBV (18%), MSI (15%), GS (25%), and CIN (42%) subtypes. CIN correlated with age > 40 years ( p  = 0.04), while GS associated with diffuse histology ( p  < 0.0001). ACRG subtypes included MSI (17%), MSS/EMT (26.7%), MSS/p53 normal (47.6%), and MSS/p53 aberrant (8.4%), with MSS/EMT linked to diffuse histology. PI3K overexpression was higher in CIN (TCGA) and MSI (ACRG) subtypes. MSI demonstrated superior median overall survival (35 vs. 32 months, p  < 0.0001) in both classifications. Conclusion TCGA and ACRG classifications effectively stratified GC, correlating with clinical outcomes. PIK3CA as an additional marker may be further explored to be included in the classification system. These findings support IHC-based molecular classification for prognostic stratification in regional cohorts.