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Abstract Background and aims This study sought to determine the value of patient-derived organoids (PDOs) from esophago-gastric adenocarcinoma (EGC) for response prediction to neoadjuvant chemotherapy (neoCTx). Methods Endoscopic biopsies of patients with locally advanced EGC (n = 120) were taken into culture and PDOs expanded. PDOs' response towards the single substances of the FLOT regimen and the combination treatment were correlated to patients' pathological response using tumor regression grading. A classifier based on FLOT response of PDOs was established in an exploratory cohort (n = 13) and subsequently confirmed in an independent validation cohort (n = 13). Results EGC PDOs reflected patients' diverse responses to single chemotherapeutics and the combination regimen FLOT. In the exploratory cohort, PDOs response to single 5-FU and FLOT combination treatment correlated with the patients' pathological response (5-FU: Kendall's τ = 0.411, P = 0.001; FLOT: Kendall's τ = 0.694, P = 2.541e-08). For FLOT testing, a high diagnostic precision in receiver operating characteristic (ROC) analysis was reached with an AUCROC of 0.994 (CI 0.980 to 1.000). The discriminative ability of PDO-based FLOT testing allowed the definition of a threshold, which classified in an independent validation cohort FLOT responders from non-responders with high sensitivity (90%), specificity (100%) and accuracy (92%). Conclusion In vitro drug testing of EGC PDOs has a high predictive accuracy in classifying patients' histological response to neoadjuvant FLOT treatment. Taking into account the high rate of successful PDO expansion from biopsies, the definition of a threshold that allows treatment stratification paves the way for an interventional trial exploring PDO-guided treatment of EGC patients.

Abstract Gastric cancer ranks the fifth most common and third leading cause of cancer‐related deaths worldwide. Alterations in the RTK/MAPK, WNT, cell adhesion, TP53, TGFβ, NOTCH, and NFκB signaling pathways could be identified as main oncogenic drivers. A combination of altered pathways can be associated with molecular subtypes of gastric cancer. In order to generate model systems to study the impact of different pathway alterations in a defined genetic background, we generated three murine organoid models: a RAS‐activated (KrasG12D, Tp53R172H), a WNT‐activated (Apcfl/fl, Tp53R172H), and a diffuse (Cdh1fl/fl, Apcfl/fl) model. These organoid models were morphologically and phenotypically diverse, differed in proteome expression signatures and possessed individual drug sensitivities. A differential vulnerability to RTK/MAPK pathway interference based on the different mitogenic drivers and according to the level of dependence on the pathway could be uncovered. Furthermore, an association between RTK/MAPK pathway activity and susceptibility to HDAC inhibition was observed. This finding was further validated in patient‐derived organoids from gastric adenocarcinoma, thus identifying a novel treatment approach for RTK/MAPK pathway altered gastric cancer patients.

Background. Organoid cultures of human pancreatic ductal adenocarcinoma (PDAC) have become a promising tool for tumor subtyping and individualized chemosensitivity testing. PDACs have recently been grouped into different molecular subtypes with clinical impact based on cytokeratin-81 (KRT81) and hepatocyte nuclear factor 1A (HNF1A). However, a suitable antibody for HNF1A is currently unavailable. The present study is aimed at establishing subtyping in PDAC organoids using an alternative marker. Methods. A PDAC organoid biobank was generated from human primary tumor samples containing 22 lines. Immunofluorescence staining was established and done for 10 organoid lines for cystic fibrosis transmembrane conductance regulator (CFTR) and KRT81. Quantitative real-time PCR (qPCR) was performed for CFTR and HNF1A. A chemotherapeutic drug response analysis was done using gemcitabine, 5-FU, oxaliplatin, and irinotecan. Results. A biobank of patient-derived PDAC organoids was established. The efficiency was 71% (22/31) with 68% for surgical resections and 83% for fine needle aspirations. Organoids could be categorized into the established quasimesenchymal, exocrine-like, and classical subtypes based on KRT81 and CFTR immunoreactivity. CFTR protein expression was confirmed on the transcript level. CFTR and HNF1A transcript expression levels positively correlated (n=10; r=0.927; p=0.001). PDAC subtypes of the primary tumors and the corresponding organoid lines were identical for most of the cases analyzed (6/7). Treatment with chemotherapeutic drugs revealed tendencies but no significant differences regarding drug responses. Conclusions. Human PDAC organoids can be classified into known subtypes based on KRT81 and CFTR immunoreactivity. CFTR and HNF1A mRNA levels correlated well. Furthermore, subtype-specific immunoreactivity matched well between PDAC organoids and the respective primary tumor tissue. Subtyping of human PDACs using CFTR might constitute an alternative to HNF1A and should be further investigated.