di Pietro, M. | bioRxiv Science

bioRxiv2026

Polyclonal and single clonal patient-derived organoid models of Barrett oesophagus and oesophageal adenocarcinoma establish a platform for the analysis of heterogeneity in disease progression and therapy response

SUMMARY/ABSTRACTOesophageal adenocarcinoma (OAC) is a major cause of morbidity and mortality. OAC and its precursor, Barrett oesophagus (BO), are defined by substantial early heterogeneity, complicating prevention and treatment of OAC and remaining poorly recapitulated by current in vitro and animal model systems. We have generated 116 patient- and healthy donor-derived organoids (PDOs) spanning normal oesophagogastric tissue, BO and OAC. These PDOs capture population diversity and recapitulate phenotypic, genomic and transcriptomic features of their respective disease stages. We develop a single cell-derived clonal organoid approach and show that this enables us to capture the heterogeneity and isolate high-risk, subclonal populations that are difficult to discern and maintain in bulk PDO cultures. Using this platform, we demonstrate functional importance of this biobank across the pre-malignant to invasive disease spectrum, including a role for BO in shaping fibroblast phenotype within assembloids, and diverse responses of OAC to chemotherapy, radiotherapy and targeted CDK4/6 inhibition. HIGHLIGHTSO_LIPatient- and healthy donor-derived organoids (PDOs) provide a functional platform of disease progression and heterogeneity across normal gastric, non-dysplastic and dysplastic Barrett oesophagus (BO) and oesophageal adenocarcinoma (OAC). C_LIO_LIWe provide a quantitative phenotypic and molecular framework to assess the provenance and fidelity of each PDO model given the heterogeneity of this disease. C_LIO_LIPDOs recapitulate key features of non-dysplastic and dysplastic BO, as well as invasive OAC. C_LIO_LISingle cell-derived clonal organoids (sc-organoids) isolate and maintain high-risk subclonal populations. C_LIO_LIOAC PDOs mirror known population level variation in response to systemic anti-cancer therapies. C_LI

cancer biology↗

bioRxiv2023

Dual-modality imaging of immunofluorescence and imaging mass cytometry for whole slide imaging with accurate single-cell segmentation

Imaging mass cytometry (IMC) is a powerful multiplexed tissue imaging technology that allows simultaneous detection of more than 30 makers on a single slide. It has been increasingly used for singlecell-based spatial phenotyping in a wide range of samples. However, it only acquires a small, rectangle field of view (FOV) with a low image resolution that hinders downstream analysis. Here, we reported a highly practical dual-modality imaging method that combines high-resolution immunofluorescence (IF) and high-dimensional IMC on the same tissue slide. Our computational pipeline uses the whole slide image (WSI) of IF as a spatial reference and integrates small FOVs IMC into a WSI of IMC. The high-resolution IF images enable accurate single-cell segmentation to extract robust high-dimensional IMC features for downstream analysis. We applied this method in esophageal adenocarcinoma of different stages, identified the single-cell pathology landscape via reconstruction of WSI IMC images, and demonstrated the advantage of the dual-modality imaging strategy. MotivationHighly multiplexed tissue imaging allows visualization of the spatially resolved expression of multiple proteins at the single-cell level. Although imaging mass cytometry (IMC) using metal isotope-conjugated antibodies has a significant advantage of low background signal and absence of autofluorescence or batch effect, it has a low resolution that hampers accurate cell segmentation and results in inaccurate feature extraction. In addition, IMC only acquires mm2-sized rectangle regions, which limits its application and efficiency when studying larger clinical samples with non-rectangle shapes. To maximize the research output of IMC, we developed the dual-modality imaging method based on a highly practical and technical improvement requiring no extra specialized equipment or agents and proposed a comprehensive computational pipeline that combines IF and IMC. The proposed method greatly improves the accuracy of cell segmentation and downstream analysis and is able to obtain whole slide image IMC to capture the comprehensive cellular landscape of large tissue sections.

bioinformatics↗