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An Automated Organoid Platform with Inter-organoid Homogeneity and Inter-patient Heterogeneity.

ABSTRACT: Current organoid technologies require intensive manual manipulation and lack uniformity in organoid size and cell composition. We present here an automated organoid platform that generates uniform organoid precursors in high-throughput. This is achieved by templating from monodisperse Matrigel droplets and sequentially delivering them into wells using a synchronized microfluidic droplet printer. Each droplet encapsulates a certain number of cells (e.g., 1,500 cells), which statistically represent the heterogeneous cell population in a tumor section. The system produces >400-μm organoids within 1 week with both inter-organoid homogeneity and inter-patient heterogeneity. This enables automated organoid printing to obtain one organoid per well. The organoids recapitulate 97% gene mutations in the parental tumor and reflect the patient-to-patient variation in drug response and sensitivity, from which we obtained more than 80% accuracy among the 21 patients investigated. This organoid platform is anticipated to fulfill the personalized medicine goal of 1-week high-throughput screening for cancer patients.

SUBMITTER: Jiang S

PROVIDER: S-EPMC7762778 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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An Automated Organoid Platform with Inter-organoid Homogeneity and Inter-patient Heterogeneity.

Jiang Shengwei S Zhao Haoran H Zhang Weijie W Wang Jiaqi J Liu Yuhong Y Cao Yuanxiong Y Zheng Honghui H Hu Zhiwei Z Wang Shubin S Zhu Yu Y Wang Wei W Cui Shuzhong S Lobie Peter E PE Huang Laiqiang L Ma Shaohua S

Cell reports. Medicine 20201222 9

Current organoid technologies require intensive manual manipulation and lack uniformity in organoid size and cell composition. We present here an automated organoid platform that generates uniform organoid precursors in high-throughput. This is achieved by templating from monodisperse Matrigel droplets and sequentially delivering them into wells using a synchronized microfluidic droplet printer. Each droplet encapsulates a certain number of cells (e.g., 1,500 cells), which statistically represen ...[more]

PMID: 33377132

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Project description:Background & aimsPatient-derived organoid cancer models are generated from epithelial tumor cells and reflect tumor characteristics. However, they lack the complexity of the tumor microenvironment, which is a key driver of tumorigenesis and therapy response. Here, we developed a colorectal cancer organoid model that incorporates matched epithelial cells and stromal fibroblasts.MethodsPrimary fibroblasts and tumor cells were isolated from colorectal cancer specimens. Fibroblasts were characterized for their proteome, secretome, and gene expression signatures. Fibroblast/organoid co-cultures were analyzed by immunohistochemistry and compared with their tissue of origin, as well as on gene expression levels compared with standard organoid models. Bioinformatics deconvolution was used to calculate cellular proportions of cell subsets in organoids based on single-cell RNA sequencing data.ResultsNormal primary fibroblasts, isolated from tumor adjacent tissue, and cancer associated fibroblasts retained their molecular characteristics in vitro, including higher motility of cancer associated compared with normal fibroblasts. Importantly, both cancer-associated fibroblasts and normal fibroblasts supported cancer cell proliferation in 3D co-cultures, without the addition of classical niche factors. Organoids grown together with fibroblasts displayed a larger cellular heterogeneity of tumor cells compared with mono-cultures and closely resembled the in vivo tumor morphology. Additionally, we observed a mutual crosstalk between tumor cells and fibroblasts in the co-cultures. This was manifested by considerably deregulated pathways such as cell-cell communication and extracellular matrix remodeling in the organoids. Thrombospondin-1 was identified as a critical factor for fibroblast invasiveness.ConclusionWe developed a physiological tumor/stroma model, which will be vital as a personalized tumor model to study disease mechanisms and therapy response in colorectal cancer.

Project description:BackgroundAddition of oxaliplatin to adjuvant 5-FU has significantly improved the disease-free survival and served as the first line adjuvant chemotherapy in advanced colorectal cancer (CRC) patients. However, a fraction of patients remains refractory to oxaliplatin-based treatment. It is urgent to establish a preclinical platform to predict the responsiveness toward oxaliplatin in CRC patients as well as to improve the efficacy in the resistant patients.MethodsA living biobank of organoid lines were established from advanced CRC patients. Oxaliplatin sensitivity was assessed in patient-derived tumor organoids (PDOs) in vitro and in PDO-xenografted tumors in mice. Based on in vitro oxaliplatin IC50 values, PDOs were classified into either oxaliplatin-resistant (OR) or oxaliplatin-sensitive (OS) PDOs. The outcomes of patients undergone oxaliplatin-based treatment was followed. RNA-sequencing and bioinformatics tools were performed for molecular profiling of OR and OS PDOs. Oxaliplatin response signatures were submitted to Connectivity Map algorithm to identify perturbagens that may antagonize oxaliplatin resistance.ResultsOxaliplatin sensitivity in PDOs was shown to correlate to oxaliplatin-mediated inhibition on PDO xenograft tumors in mice, and parallelled clinical outcomes of CRC patients who received FOLFOX treatment. Molecular profiling of transcriptomes revealed oxaliplatin-resistant and -sensitive PDOs as two separate entities, each being characterized with distinct hallmarks and gene sets. Using Leave-One-Out Cross Validation algorithm and Logistic Regression model, 18 gene signatures were identified as predictive biomarkers for oxaliplatin response. Candidate drugs identified by oxaliplatin response signature-based strategies, including inhibitors targeting c-ABL and Notch pathway, DNA/RNA synthesis inhibitors, and HDAC inhibitors, were demonstrated to potently and effectively increase oxaliplatin sensitivity in the resistant PDOs.ConclusionsPDOs are useful in informing decision-making on oxaliplatin-based chemotherapy and in designing personalized chemotherapy in CRC patients.

Dataset Information

An Automated Organoid Platform with Inter-organoid Homogeneity and Inter-patient Heterogeneity.

Publications

An Automated Organoid Platform with Inter-organoid Homogeneity and Inter-patient Heterogeneity.

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