Automated brightfield morphometry of 3D organoid populations by OrganoSeg

Borten, Michael A.; Bajikar, Sameer S.; Sasaki, Nobuo; Clevers, Hans; Janes, Kevin A.

doi:10.1038/s41598-017-18815-8

Cited by 109 publications

(89 citation statements)

References 33 publications

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“…However, depending on the microscope objectives on hand, multiple fields may need to be collected and tiled in order to obtain a whole-well image. Some labs have described measuring area from a single z-plane 12 , but to capture all organoids in focus, it is recommended to collect and stack multiple planes into a single EDF-image 13 . In some cases, a meniscus in the matrix gel may cause vignetting in the image, and background correction methods may need to be applied using image analysis software.…”

Section: Discussionmentioning

confidence: 99%

Handling and Assessment of Human Primary Prostate Organoid Culture

McCray

Richards

Marsili

et al. 2019

JoVE

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This paper describes a detailed protocol for three-dimensional (3D) culturing, handling, and evaluation of human primary prostate organoids. The process involves seeding of epithelial cells sparsely in a 3D matrix gel on a 96-well microplate with media changes to cultivate expansion into organoids. Morphology is then assessed by whole-well capturing of z-stack images. Compression of z-stacks creates a single in-focus image from which organoids are measured to quantify a variety of outputs, including circularity, roundness, and area.DNA, RNA, and protein can be collected from organoids recovered from the matrix gel. Cell populations of interest can be assessed by organoid dissociation and flow cytometry. Formalin-fixation-paraffin-embedding (FFPE) followed by sectioning is used for the histological assessment and antibody staining. Whole-mount immunofluorescent staining preserves organoid morphology and facilitates observation of protein localization in organoids in situ. Commercial assays that are traditionally used for 2D monolayer cells can be modified for 3D organoids. Used together, the techniques in this protocol provide a robust toolbox to quantify prostate organoid growth, morphologic characteristics, and expression of differentiation markers.

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Section: Discussionmentioning

confidence: 99%

Handling and Assessment of Human Primary Prostate Organoid Culture

McCray

Richards

Marsili

et al. 2019

JoVE

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“…Brightfield 3D images were acquired on an Olympus CKX41 inverted microscope with a 4´ Plan objective (four fields per chamber) and a qColor3 camera (Qimaging). Images were segmented using OrganoSeg (111) to produce morphometric measures for each segmented spheroid. 'Rounded' spheres were classified as having circularity greater than 0.9 (Fig.…”

Section: Brightfield Imaging and Quantification Of Spheroid Phenotypesmentioning

confidence: 99%

Sporadic activation of an oxidative stress-dependent NRF2–p53 signaling network in breast epithelial spheroids and premalignancies

Pereira

Burns

Lee

et al. 2019

Preprint

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ABSTRACTBreast–mammary epithelial cells experience different local environments during tissue development and tumorigenesis. Microenvironmental heterogeneity gives rise to distinct cell-regulatory states whose identity and importance are just beginning to be appreciated. Cellular states diversify when clonal 3D spheroids are cultured in basement membrane, and prior transcriptomic analyses identified a state associated with stress tolerance and poor response to anticancer therapeutics. Here, we examined the regulation of this state and found that it is jointly coordinated by the NRF2 and p53 pathways, which are co-stabilized by spontaneous oxidative stress within the 3D cultures. Inhibition of NRF2 or p53 individually disrupts some of the transcripts defining the regulatory state but does not yield a notable phenotype in nontransformed breast epithelial cells. In contrast, combined perturbation prevents 3D growth in an oxidative stress-dependent manner. By integrating systems models of NRF2 and p53 signaling together as a single oxidative-stress network, we recapitulate these observations and make predictions about oxidative stress profiles during 3D growth. Similar coordination of NRF2 and p53 signaling is observed in normal breast epithelial tissue and hormone-negative ductal carcinoma in situ lesions. However, the pathways are uncoupled in triple-negative breast cancer, a subtype in which p53 is usually mutated. Using the integrated model, we reconcile the different NRF2-knockdown phenotypes of triple-negative cancer lines with their inferred handling of oxidative stress. Our results point to an oxidative stress-tolerance network that is important for single cells during glandular development and the early stages of breast cancer.One Sentence SummaryReactive oxygen species co-stabilize a non-oncogene and a tumor suppressor for triple-negative breast cancer when cells are surrounded by basement-membrane ECM.

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“…At day 10, organoids from Panc014 were cystic and had smooth edges while Panc030 and Panc281 were solid coinciding with lower level of genomic alterations observed in Panc014 (Fig.S1A). To better understand differences in other morphometric parameters, we used OrganoSeg, a segmentation and analysis platform that can extract multiple parameters from spheroid and organoid cultures (13). As shown in Fig.S1B, individual organoids were identified and highlighted based on their phase contrast intensity profiles to create a mask and measure the area (as index for organoid sizes) and eccentricity (as index for organoid circularity).…”

Section: Tumor Organoids Recapitulate Genomic Profiles Of Matched Pdxmentioning

confidence: 99%

“…About 200 images were obtained for each line. The images were analyzed for changes using the organoseg software program (13). Briefly, raw images were segmented and analyzed using inbuilt parameters such as area, perimeter and eccentricity.…”

Section: Morphological and Histological Analysismentioning

confidence: 99%

Pancreatic tumor organoids for modeling in vivo drug response and discovering clinically-actionable biomarkers

Huang

Bockorny

Paul

et al. 2019

Preprint

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Patient-derived models are transforming translational cancer research. It is not clear if the emergence of patientderived organoid (PDO) models can extend the utility of the widely used patient-derived xenograft (PDX). In addition, the utility of PDO models for serum biomarker discovery is not known. Here, we demonstrate that PDO models recapitulate the genomics, cell biology, glycomics and drug responses observed in PDX models. Furthermore, we demonstrate the applicability of PDO models for identification of N-glycans that are enriched in the glycome of pancreatic ductal adenocarcinoma (PDAC). Surprisingly, among all the glycans observed in PDX and PDOs, a core set of 57 N-glycans represent 50-94% of the relative abundance of all N-glycans detected, suggesting that only a subset of glycans dominate the cell surface landscape in PDAC. In addition, we outline a tumor organoid-based pipeline to identify surface proteins in extracellular vesicles (EV) from media supernatant of PDO cultures. When combined with the affinity-based validation platform, the EV surface proteins discovered in PDOs are effective in differentiating patients with PDAC from those with benign pancreatitis in the clinic, identifying PDO as powerful discovery platform for serum biomarkers. Thus, PDOs extend the utility of the archival collections of PDX models for translational research and function as a powerful platform for identification of clinically-actionable biomarkers in patients blood. Significance statement:Tumor organoids extend the utility of PDX models as platforms for investigating drug response, glycosylation changes and function as new platforms for discovering blood-based biomarkers

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Automated brightfield morphometry of 3D organoid populations by OrganoSeg

Cited by 109 publications

References 33 publications

Handling and Assessment of Human Primary Prostate Organoid Culture

Handling and Assessment of Human Primary Prostate Organoid Culture

Sporadic activation of an oxidative stress-dependent NRF2–p53 signaling network in breast epithelial spheroids and premalignancies

Pancreatic tumor organoids for modeling in vivo drug response and discovering clinically-actionable biomarkers

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