IDDF2024-ABS-0404 Patient-derived xenograft (PDX) models with varying levels of HER2 expression are utilized for the preclinical evaluation of HER2-targeted therapies

Background Overexpression of human epidermal growth factor receptor 2 (HER2) is increasingly recognized as a common molecular abnormality in gastric and gastroesophageal cancer. Drugs targeting the HER2 protein have shown promise in treating these cancers. Additionally, there is evidence to suggest that DS-8201a, a HER2-targeted ADC drug, may be effective and safe in treating patients with heterogeneous or low HER2 expression. To aid in the design of personalized or precise drug treatment strategies for HER2-targeted drugs in clinical trials, Gempharmatech offers suitable patient-derived xenograft (PDX) gastric cancer models. Methods Gastric Cancer (GC) Patient-Derived Xenograft (PDX) models were meticulously established by engrafting patient tumor fragments into NCG mice. FFPE slides of GC PDX models were prepared using standard histology procedures. The standard IHC staining protocol was performed with an anti-human ErbB2/HER2 Antibody. The fresh fourth-generation tumors were then transplanted into female NOD-SCID mice (6-8 weeks old). When the average tumor volume reached 80mm3, the mice were randomly grouped into three groups (n=5/group). Each group was respectively treated with PBS, trastuzumab, and DS8201a. Results Gastric cancer samples with varying levels of HER2 expression were identified using an IHC assay. Interestingly, high heterogeneity in HER2 expression was observed among different tumor-bearing mice in one sample. These models were then utilized to evaluate the efficacy of HER2 therapy. All HER2-targeted drugs, including Trastuzumab (Herceptin), Margetuximab, and DS-8201a, inhibited tumor growth in the model with HER2-positive expression. Notably, only DS-8201a continued to significantly inhibit tumor growth in the model with heterogeneous HER2 expression. Conclusions Therefore, Gempharmatech utilized PDX gastric cancer models to present detailed and realistic assessments of drug effects and assist in predicting phase I and II clinical efficacy as well as response rates for new drugs.