Targeted transcriptomic analysis of pancreatic adenocarcinoma in EUS-FNA samples by NanoString technology

Background: Integration of transcriptomic testing into EUS-FNA samples is a growing need for precision oncology in pancreatic ductal adenocarcinoma (PDAC). The NanoString platform is suitable for transcriptome profiling in low yield RNA samples. Methods: Inclusion of patients that underwent EUS-FNA...

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Bibliographic Details
Authors: Pedrosa, Leire, Araujo, Isis Karina, Cuatrecasas Freixas, Miriam, Soy, Guillem, López, S., Maurel Santasusana, Joan, Sánchez Montes, Cristina, Montironi, Carla, Saurí, Tamara, Sendino, Oriol, Pérez, F.M., Ausania, Fabio, Fernández Esparrach, Glòria, Espósito, F.M., Vaquero, Eva C., Ginès i Gibert, M. Àngels
Format: article
Status:Published version
Publication Date:2023
Country:España
Institution:Universidad de Barcelona
Repository:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/219891
Online Access:https://hdl.handle.net/2445/219891
Access Level:Open access
Keyword:Tècniques citològiques
Marcadors bioquímics
Càncer de pàncrees
RNA
Cytological techniques
Biochemical markers
Pancreas cancer
Description
Summary:Background: Integration of transcriptomic testing into EUS-FNA samples is a growing need for precision oncology in pancreatic ductal adenocarcinoma (PDAC). The NanoString platform is suitable for transcriptome profiling in low yield RNA samples. Methods: Inclusion of patients that underwent EUS-FNA cytological diagnosis of pancreatic ductal adenocarcinoma using 19G and/or 22G needles and subsequent surgical resection. Formalin-fixed, paraffin-embedded (FFPE) cytological and surgical samples underwent RNA extraction and transcriptomic analysis using a custom 52-gene NanoString panel of stromal PDAC features. Cell type abundance was quantified in FFPE specimens and correlated. Results: 18 PDAC patients were included. Mean EUS-FNA passes was 2 + 0.7. All FFPE passed the RNA quality control for genomic analysis. Hierarchical clustering on the global gene expression data showed that genes were differentially expressed between EUS and surgical samples. A more enriched cancer-associated fibroblasts and epithelial-mesenchymal transition transcriptomic profile was observed across surgical specimens whereas immunological biomarkers were more represented in EUS-FNA samples. Cytological examination confirmed a scanty representation of CAF and more immunological cell abundance in cytological samples in comparison to surgical specimens. Conclusion: Targeted transcriptomic NanoString profiling of PDAC samples obtained by EUS-FNA is a feasible approach for pre-surgical molecular analysis although stromal CAF/EMT mRNA biomarkers are underrepresented.

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