Patient-derived pancreatic ductal adenocarcinoma organoid model systems show great promise for understanding the biological underpinnings of disease and advancing therapeutic precision medicine programs.
More...Patient-derived pancreatic ductal adenocarcinoma organoid model systems show great promise for understanding the biological underpinnings of disease and advancing therapeutic precision medicine programs. These models are exciting because they exhibit disease-specific characteristics, they can be rapidly generated, and they can be easily maintained. Despite the increased of use of organoid models, the fidelity of molecular features, genetic heterogeneity, and drug response to the tumor of origin remain important unanswered questions that limit their utility. We created primary tumor-derived and PDX-derived organoid models, and 2D cultures, and performed in-depth genomic and histopathological comparisons to the primary tumor. Microscopic features, including glandular architecture, cellular stratification, and cytological atypia were highly correlated between primary tumors and corresponding models. Similarly, cytokeratins 7, 19, and 20, p53, CA19-9, and claudin-4 PDAC markers showed strong concordance. DNA and RNA sequencing of single organoids revealed patient-specific genomic and transcriptomic consistency. Single-cell RNAseq revealed organoids are primarily a clonal population, but also contain distinct subpopulations with stem cell and EGF signatures. In drug response assays, organoid models displayed patient-specific sensitivities. Additionally, for one case, we examined the in vivo PDX response to FOLFIRINOX and Gemcitabine/Abraxane treatments, which was recapitulated by in vitro organoid models. The patient-specific genetic and histopathological fidelity of organoids indicates that organoid models can be used to understand the etiology of the patient’s tumor biology and potentially drug responses.
Less...| Accession | PRJNA471134 |
| Data Type | Raw sequence reads |
| Scope | Multispecies |
| Submission | Registration date: 12-May-2018 University of Chicago |
| Relevance | Medical |
Project Data:
| Resource Name | Number of Links |
|---|
| BioSample | 67 |
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