Abstract
BACKGROUND: Anti-PD1/PD-L1 antibody plus human epidermal growth factor receptor 2 (HER2) antibody and chemotherapy have become the new first-line therapy for HER2 overexpression-positive advanced gastric cancers (GC), suggesting that HER2 and PD-L1 play a vital role in guiding systemic treatment for patients with GC. This study aimed to depict the genomic and immune landscapes of Chinese patients with GC and investigate their correlations with HER2 amplification and PD-L1 expression. PATIENTS AND METHODS: Next-generation targeted sequencing and PD-L1 immunohistochemistry were performed on tumor samples from 735 patients with pathologically diagnosed GC. The genomic and immune landscapes and their correlations with HER2 amplification and PD-L1 expression were analyzed. RESULTS: The most commonly mutated genes in Chinese GC were TP53 (64%), CDH1 (20%), ARID1A (18%), HMCN1 (15%), KMT2D (11%), and PIK3CA (11%). Seventy-six (10%) patients were HER2 amplification, and 291 (40%) had positive PD-L1 expression. Classifying the total population based on HER2 amplification and PD-L1 expression level, 735 patients were divided into four subgroups: HER2+/PD-L1+ (4.5%), HER2+/PD-L1- (5.9%), HER2-/PD-L1+ (35.1%), and HER2-/PD-L1- (54.5%). The HER2+/PD-L1- and HER2+/PD-L1+ subgroups exhibited dramatically higher rate of TP53 mutations, CCNE1 and VEGF amplifications. The HER2+/PD-L1- subgroup also had a markedly higher rate of MYC amplification and KRAS mutations. The HER2-/PD-L1+ subgroup had significantly higher rate of PIK3CA mutations. HER2+/PD-L1- subgroup had the highest TMB level and HER2-/PD-L1+ subgroup had the highest proportion of patients with microsatellite instability-high than other subgroups. Furthermore, we observed that different HER2 amplification levels had distinct impacts on the correlations between PD-L1 expression and therapeutic genomic alterations, but no impact on the prognosis. CONCLUSION: The combination of HER2 amplification and PD-L1 expression in Chinese patients with GC could stratify the total populations into several subgroups with distinctive genomic and immune landscapes, which should be considered when making personalized treatment decisions.