Human Organoids Share Structural and Genetic Features with Primary Pancreatic Adenocarcinoma Tumors

人类类器官与原发性胰腺腺癌肿瘤具有相同的结构和遗传特征

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作者:Isabel Romero-Calvo, Christopher R Weber, Mohana Ray, Miguel Brown, Kori Kirby, Rajib K Nandi, Tiha M Long, Samantha M Sparrow, Andrey Ugolkov, Wenan Qiang, Yilin Zhang, Tonya Brunetti, Hedy Kindler, Jeremy P Segal, Andrey Rzhetsky, Andrew P Mazar, Mary M Buschmann, Ralph Weichselbaum, Kevin Roggin,

Abstract

Patient-derived pancreatic ductal adenocarcinoma (PDAC) organoid systems show great promise for understanding the biological underpinnings of disease and advancing therapeutic precision medicine. Despite the increased use of organoids, the fidelity of molecular features, genetic heterogeneity, and drug response to the tumor of origin remain important unanswered questions limiting their utility. To address this gap in knowledge, primary tumor- and patient-derived xenograft (PDX)-derived organoids, and 2D cultures for in-depth genomic and histopathologic comparisons with the primary tumor were created. Histopathologic features and PDAC representative protein markers (e.g., claudin 4 and CA19-9) showed strong concordance. DNA- and RNA-sequencing (RNAseq) of single organoids revealed patient-specific genomic and transcriptomic consistency. Single-cell RNAseq demonstrated that organoids are primarily a clonal population. In drug response assays, organoids displayed patient-specific sensitivities. In addition, the in vivo PDX response to FOLFIRINOX and gemcitabine/abraxane treatments were examined, which was recapitulated in vitro with organoids. This study has demonstrated that organoids are potentially invaluable for precision medicine as well as preclinical drug treatment studies because they maintain distinct patient phenotypes and respond differently to drug combinations and dosage. IMPLICATIONS: The patient-specific molecular and histopathologic fidelity of organoids indicate that they can be used to understand the etiology of the patient's tumor and the differential response to therapies and suggests utility for predicting drug responses.

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