{'fraction_non_alphanumeric': 0.03188662533215235, 'fraction_numerical': 0.009152642456451136, 'mean_word_length': 5.8582995951417, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Abstract PR02: Matched metastatic pancreatic ductal adenocarcinoma biopsies and organoid models reveal tumor cell transcriptional plasticity and subtype-specific microenvironmental crosstalk

The majority of patients with pancreatic ductal adenocarcinoma (PDAC) present with metastatic disease at diagnosis and have median survival times of less than 12 months. Recent studies have demonstrated that PDAC tumors with distinct transcriptional signatures are associated with different clinical outcomes, and that the tumor microenvironment may contribute to PDAC pathogenesis. In parallel, there are ongoing efforts to understand if patient-derived organoid models can be used as functional surrogates for an individual patient’s disease. However, it remains unclear if patient transcriptional phenotypes are preserved in their matched organoid models. Here, we describe a pipeline that permits both direct characterization of the PDAC liver metastatic niche via single-cell RNA-sequencing and functional assessment of PDAC tumor biology in patient-matched organoid models. Starting from core needle biopsies of metastatic PDAC lesions containing 50-100k viable cells, we simultaneously perform (1) low-input single-cell RNA-sequencing using Seq-Well and (2) three-dimensional organoid culture generation. We have applied this approach to profile 21 patients and their matched early passage organoid models. Our pipeline yields high-quality single-cell measurements across diverse cell types—both tumor and nontumor stromal—enabling a principled dissection of tumor intrinsic and extrinsic factors. Evaluation of clinically relevant transcriptional signatures (e.g., basal-like vs. classical) revealed extensive heterogeneity at the single-cell level and identified new, hybrid expression states. We also observed evidence of significant subtype-specific crosstalk between immune populations and tumor cells—specifically between T cells and tumor cells originating from basal-like tumors. Serial sampling at different stages of treatment revealed transcriptional shifts in tumor cells suggestive of significant plasticity. We similarly found that organoids derived from basal-like tumors exhibited considerable plasticity in vitro and had decreased fitness in standard organoid culture conditions, suggesting the need for distinct environments to support specific transcriptional subtypes. Overall, our approach provides actionable insights into the heterogeneity and plasticity of human PDAC, as well as a pipeline and framework for the analysis of PDAC and other cancers. This abstract is also being presented as Poster A50. Citation Format: Peter S. Winter, Srivatsan Raghavan, Andrew W. Navia, Hannah Williams, Jennyfer Galvez-Reyes, Radha Kalekar, Ashir Borah, Alan DenAdel, Manisha Raghavan, Kristen Lowder, Nolawit Mulugeta, Junning Wang, Emma Reilly, Lauren Brais, Lorin Crawford, James McFarland, James M. Cleary, Jonathan Nowak, Brian M. Wolpin, Andrew J. Aguirre, William C. Hahn, Alex K. Shalek. Matched metastatic pancreatic ductal adenocarcinoma biopsies and organoid models reveal tumor cell transcriptional plasticity and subtype-specific microenvironmental crosstalk [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr PR02.