315. PATIENT-DERIVED ESOPHAGEAL ADENOCARCINOMA ORGANOIDS TREATED WITH CHEMOTHERAPEUTIC AGENTS MAY PREDICT TUMOR RESPONSE IN VIVO

Abstract

Abstract The current management of locally-advanced esophageal adenocarcinoma (EAC) includes neoadjuvant therapy; however, there are no robust markers that predict treatment response. While 25% of patients will have a complete pathological response, up to 40% will have little or no response. Identification of this non-responsive subgroup prior to treatment could allow personalization of induction regimens. This study aims to determine the feasibility of using patient-derived organoids (PDOs) generated from EAC to predict induction treatment response. PDOs were generated from endoscopic biopsies taken pre-treatment in patients with locally advanced (LA) or metastatic (M) esophageal cancer. For those with LA disease, samples were also taken post-resection. PDOs were established, passaged, then treated with a drug panel of platinum-based drugs, taxane-based drugs, topoisomerase inhibitors and 5-flurouracil. Treatment response curves and growth metrics were mapped back to treatment response, based on pathological tumor regression grade in the LA group and clinical response based on cross-sectional imaging in the M group. 19 organoids from 7 LA tumors and 10 organoids from 8 M tumors were treated. For LA PDOs, there were significant correlations between cisplatin IC50 (p = 0.007), EC50 (p = 0.002) and TRG. There was a correlation between paclitaxel AUC and TRG (p = 0.02). There were no correlations with irinotecan or 5-FU drug metrics and TRG. For M PDOs, there was a correlation between cisplatin and clinical response for AUC (p = 0.04), and a trend for IC50 (p = 0.07). There were also correlations between paclitaxel and clinical response for IC50 (p = 0.04) and AUC (p = 0.01). There were no correlations with irinotecan or 5-FU. Treatment responses of EAC PDOs treated in vitro with standard chemotherapeutic agents may predict clinical response in the corresponding patient’s tumor. A PDO model may form the basis for screening therapeutic agents in the neoadjuvant window, allowing the development of truly personalized neoadjuvant strategies.