Organoid models through the lens of metabolomics: a systematic review of experimental applications and analytical approaches.

Organoid engineering with microfluidics and biomaterials for liver, lung disease, and cancer modeling

Three-dimensional (3D) stem cell differentiation cultures recently emerged as a novel model system for investigating human embryonic development and disease progression in vitro, complementing existing animal and two-dimensional (2D) cell culture models. Organoids, the 3D self-organizing structures derived from pluripotent or somatic stem cells, can recapitulate many aspects of structural organization and functionality of their in vivo organ counterparts, thus holding great promise for biomedical research and translational applications. Importantly, faithful recapitulation of disease and development processes relies on the ability to modify the genomic contents in organoid cells. The revolutionary genome engineering technologies, CRISPR/Cas9 in particular, enable investigators to generate various reporter cell lines for prompt validation of specific cell lineages as well as to introduce disease-associated mutations for disease modeling. In this review, we provide historical overviews, and discuss technical considerations, and potential future applications of genome engineering in 3D organoid models.

BACKGROUND Pediatric high-grade gliomas (pHGGs) are diffusely invasive and rapidly growing brain malignancies and are among the leading causes of cancer-related deaths in children. However, current treatments for pHGGs are largely ineffective. Thus, alternative therapeutic approaches are urgently needed. Genetic mutations observed in these gliomas include H3 oncohistone mutations and alterations in receptor tyrosine kinases (RTKs), including amplification, mutation, and gene fusions. However, directly targeting RTK variants with tyrosine kinase inhibitors (TKIs) has shown only partial responses in patients, due in part to the molecular and cellular heterogeneity within these tumors. Therefore, we sought to develop new experimental model systems that recapitulate inter- and intra-tumor heterogeneity to enable therapeutic discovery. METHODS To explore new therapeutic approaches, we created human brain organoid-tumor models of pHGG, in which patient-derived tumor cells are engrafted into ex vivo human cortical brain organoids that mimic the neonatal human brain. These organoid models provide an improved system for examining how the neural CNS microenvironment shapes cellular and molecular heterogeneity among tumor cells over time. We tested these models for responses to small molecule inhibitors and targeted therapies, including approaches that target a range of developmental and oncogenic effector pathways downstream of RTKs. Candidate targets included the YAP and TAZ transcription factors, which cooperate with TEAD co-factors to promote target gene expression, orchestrate stem cell fate decisions, and drive proliferation during embryonic neural development. We examined responses in both tumor and non-tumor cells in the neural microenvironment following YAP/TAZ pharmacologic and genetic inhibition, using single-cell RNA sequencing and immunofluorescence to visualize cellular responses. RESULTS We observed that YAP-TEAD function is required for the growth and progression of pHGGs with oncogenic RTK mutations and H3 oncohistone mutations. Depletion of YAP reduced proliferation, inhibited pHGG stem cell self-renewal, and induced apoptosis in pHGG cells. Treatment with small molecule inhibitors targeting YAP/TAZ and TEAD mimicked the effects of genetic YAP inhibition. Further preclinical work in primary tumor cell cultures and mouse genetic models of pHGG correlated with our findings from organoid models, supporting the potential therapeutic relevance of YAP/TAZ-TEAD inhibition for pHGG treatment. CONCLUSIONS Our results show that YAP/TAZ-TEAD inhibition may represent a promising therapeutic avenue for pHGGs.

BackgroundPatients with colorectal metastatic disease have a poor prognosis, limited therapeutic options, and frequent development of resistance. Strategies based on tumor-derived organoids are a powerful tool to assess drug sensitivity at an individual level and to suggest new treatment options or re-challenge. Here, we evaluated the method’s feasibility and clinical outcome as applied to patients with no satisfactory treatment options.MethodsIn this phase 2, single-center, open-label, non-comparative study (ClinicalTrials.gov, register NCT03251612), we enrolled 90 patients with metastatic colorectal cancer following progression on or after standard therapy. Participants were 18 years or older with an Eastern Cooperative Oncology Group performance status of 0–2, adequate organ function, and metastasis available for biopsy. Biopsies from the metastatic site were cultured using organoids model. Sensitivity testing was performed with a panel of drugs with proven activity in phase II or III trials. At the discretion of the investigator considering toxicity, the drug with the highest relative activity was offered. The primary endpoint was the proportion of patients alive without disease progression at two months per local assessment.ResultsBiopsies available from 82 to 90 patients were processed for cell culture, of which 44 successfully generated organoids with at least one treatment suggested. The precision cohort of 34 patients started treatment and the primary endpoint, progression-free survival (PFS) at two months was met in 17 patients (50%, 95% CI 32–68), exceeding the pre-defined level (14 of 45; 31%). The median PFS was 67 days (95% CI 51–108), and the median overall survival was 189 days (95% CI 103–277).ConclusionsPatient-derived organoids and in-vitro sensitivity testing were feasible in a cohort of metastatic colorectal cancer. The primary endpoint was met, as half of the patients were without progression at two months. Cancer patients may benefit from functional testing using tumor-derived organoids.Trial registrationClinicalTrials.gov, register NCT03251612.

Research on cancer therapies has benefited from predictive tools capable of simulating treatment response and other disease characteristics in a personalized manner, in particular three-dimensional cell culture models. Such models include tumor-derived spheroids, multicellular spheroids including organotypic multicellular spheroids, and tumor-derived organoids. Additionally, organoids can be grown from various cancer cell types, such as pluripotent stem cells and induced pluripotent stem cells, progenitor cells, and adult stem cells. Although patient-derived xenografts and genetically engineered mouse models replicate human disease in vivo, organoids are less expensive, less labor intensive, and less time-consuming, all-important aspects in high-throughput settings. Like in vivo models, organoids mimic the three-dimensional structure, cellular heterogeneity, and functions of primary tissues, with the advantage of representing the normal oxygen conditions of patient organs. In this review, we summarize the use of organoids in disease modeling, drug discovery, toxicity testing, and precision oncology. We also summarize the current clinical trials using organoids.

Volatilomics, an emerging field in the study of noninvasive biomarkers, holds significant promise for identifying esophageal cancer (EC) through the detection of volatile organic compounds (VOCs). This study investigates common characteristic VOCs of EC cells by analyzing VOCs from three-dimensional organoid and spheroid models as well as two-dimensional monolayer cultures. The VOC profiles were measured by using solid-phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS) in an untargeted approach. In the organoid, spheroid, and monolayer culture models, 21, 9, and 8 metabolically differential VOCs were identified between EC and normal esophageal (NE) cells, respectively. Correlation analysis across these three models revealed a shared characteristic VOC of EC: ethyl 2-methylbutyrate. This VOC was markedly increased in EC, demonstrating excellent diagnostic potential with an area under the curve (AUC) ranging from 0.93 to 0.99. Furthermore, transcriptomic data analysis of EC and NE tissues revealed the upregulation of protein degradation and absorption in EC tissues, supporting the hypothesis that ethyl 2-methylbutyrate arises from abnormalities within this metabolic pathway. This study not only supplies potential VOC biomarkers for EC identification but also provides a scientific basis for further elucidating the biochemical mechanisms underlying EC metabolic disturbances, potentially facilitating the gaseous biopsy technique development for EC diagnosis.

Chronic respiratory diseases such as idiopathic pulmonary fibrosis, chronic obstructive pulmonary disease, and respiratory infections injure the alveoli; the damage evoked is mostly irreversible and occasionally leads to death. Achieving a detailed understanding of the pathogenesis of these fatal respiratory diseases has been hampered by limited access to human alveolar tissue and the differences between mice and humans. Thus, the development of human alveolar organoid (AO) models that mimic in vivo physiology and pathophysiology has gained tremendous attention over the last decade. In recent years, human pluripotent stem cells (hPSCs) have been successfully employed to generate several types of organoids representing different respiratory compartments, including alveolar regions. However, despite continued advances in three-dimensional culture techniques and single-cell genomics, there is still a profound need to improve the cellular heterogeneity and maturity of AOs to recapitulate the key histological and functional features of in vivo alveolar tissue. In particular, the incorporation of immune cells such as macrophages into hPSC-AO systems is crucial for disease modeling and subsequent drug screening. In this review, we summarize current methods for differentiating alveolar epithelial cells from hPSCs followed by AO generation and their applications in disease modeling, drug testing, and toxicity evaluation. In addition, we review how current hPSC-AOs closely resemble in vivo alveoli in terms of phenotype, cellular heterogeneity, and maturity.

Gastric Organoids: Progress and Remaining Challenges.

We are experiencing a revolution in regenerative medicine. Recent developments in organoid technology have provided unique opportunities for studying human biology and diseases. Indeed, organoid models have revolutionized the in vitro culture tools for biomedical research by creating robust three-dimensional (3D) architecture to recapitulate the primary tissues' cellular heterogeneity, structure, and functions. Such organoid technology enables researchers to re-create human organs and diseases model in a culture dish. It thus holds excellent promises for many translational applications such as regenerative medicine, drug discovery, and precision medicine. This review summarizes the current knowledge on the progression and promotion of organoid models, particularly with the heart disease approach. We discuss the usefulness of clinical applications of cardiac organoids and ultimately highlight the currently advanced therapeutic strategies in vitro model of organoids aimed at personalizing heart disease treatment.

A key challenge in the clinical management and cause of treatment failure of prostate cancer (PCa) is its molecular, cellular and clinical heterogeneity. Modelling systems that fully recapitulate clinical diversity and resistant phenotypes are urgently required for the development of successful personalised PCa therapies. The advent of the three-dimensional (3D) organoid model has revolutionised preclinical cancer research through reflecting heterogeneity and offering genomic and environmental manipulation that has opened up unparalleled opportunities for applications in disease modelling, high-throughput drug screening and precision medicine. Despite these remarkable achievements of organoid technology, several shortcomings in emulating the complex tumor microenvironment and dynamic process of metastasis as well as the epigenome profile limit organoids achieving true in vivo functionality. Technological advances in tissue engineering have enabled the development of innovative tools to facilitate the design of improved 3D cancer models. In this review, we highlight the current in vitro 3D PCa models with a special focus on organoids and discuss engineering approaches to create more physiologically relevant PCa organoid models and maximise their translational relevance that ultimately will help to realise the transformational power of precision medicine.

Exposures to cyanobacterial harmful algal bloom (CHAB) toxins are of increasing concern to human and animal health, including livestock, pets, and wildlife. Climate change and eutrophication of streams, small lakes and ponds has led to an increase in the production of harmful algal blooms worldwide in recent years, and particularly in the Midwest section of the United States. Common toxins produced by CHABs are microcystins, anatoxin (a), and cylindrospermopsin. Several analytical methods are available to identify CHAB toxins and characterize their concentrations in human drinking water and waters used for human recreation. The purpose of the thesis is to develop and validate an analytical method for the determination of microcystin LR, RR, YR, and LA, anatoxin (a) and cylindrospermopsin concentrations in water consumed by livestock, companion animals and mammalian and avian wildlife. While analysis of water for human exposure requires an analytical method that can quantify CHAB toxins at sub ng/mL concentrations, analysis of water for veterinary diagnostic purposes does not need to reach these low levels of quantification. The main purpose of veterinary diagnoses is to determine if the concentrations of CHAB toxins in a water source are safe for animal consumption or at levels that would likely be acutely lethal. The secondary purpose of veterinary diagnoses is to determine if concentrations of CHAB toxins are at levels that would negatively affect livestock due to chromic exposure. Chronic exposure to CHAB toxins include poor weight gain, liver damage, and death. For veterinary diagnoses, the level of quantification is 1ng/mL for anantoxin (a), cylindrospermopsin, microcystin RR, microcystin LA, and 2ng/mL for microcystin LR and microcystin YR. To develop and validate a novel analytical method for the detection and quantification of CHAB toxins at aqueous concentrations of concern, several methodological issues were addressed. Since CHAB toxins are present in the water as well as in the cyanobacteria cells, an accurate assessment of the total CHAB toxin exposure requires cyanobacteria cells be lysed prior to analysis. Several cell lysis techniques were investigated to determine the most effective and efficient approach. Water samples known to contain CHABs were used to evaluate cell lysis techniques. Water samples from streams and ponds in in and around the Ames, Iowa were analyzed to determine matrix effects and selectivity. The analytical method was validated for limit of quantification (LOQ), accuracy, precision, and linearity of dilution using two liquid chromatography mass spectrometry (LC-MS) platforms: triple quadrupole mass spectrometry and high resolution accurate mass (HRAM) orbitrap mass spectrometry. Validation parameters included LOQ, accuracy, precision, linearity of dilution, re-injection reproducibility, and blinded sample analysis. All parameters were analyzed on both mass spectrometry platforms. To more fully assess the exposure to CHAB toxins an untargeted analytical approach was investigated using a LC-MS HRAM quadrupole orbitrap instrument. Understanding the complete CHAB toxin composition of water samples provides important diagnostic information to veterinarians in cases where animals have known exposure to contaminated water sources. A targeted quantitative method is limited by the number of CHAB toxins analytical standards that can be purchased through commercially available suppliers. While the analytical method includes anatoxin (a), CYN, MC LA, MC LR, MC RR, and MC YR, there are many other know CHAB toxins that could be present in a waters sample. An untargeted approach was also develop in order to identify CHAB toxins in a sample. This approach matches CHAB toxins to a library mass spectrum regardless of whether a standard for the toxin(s) is available. The mass spectral library used is mzCloud which is curated by Thermo Fisher Scientific and contains a mass spectrum for an additional eight microcystins and homo-anatoxin. Although the initial trials for untargeted analysis were not able to match CHAB toxins known to be present in water samples analyzed, future improvements to the methodology are described to advance a diagnostic tool to determine total CHAB toxin exposure.

Organoids are three-dimensional cell cultures that mimic organ functions and structures. The organoid model has been developed as a versatile in vitro platform for stem cell biology and diseases modeling. Tumor organoids are shown to share ~ 90% of genetic mutations with biopsies from same patients. However, it's not clear whether tumor organoids recapitulate the cellular heterogeneity observed in patient tumors. Here, we used single-cell RNA-Seq to investigate the transcriptomics of tumor organoids derived from human colorectal tumors, and applied machine learning methods to unbiasedly cluster subtypes in tumor organoids. Computational analysis reveals cancer heterogeneity sustained in tumor organoids, and the subtypes in organoids displayed high diversity. Furthermore, we treated the tumor organoids with a first-line cancer drug, Oxaliplatin, and investigated drug response in single-cell scale. Diversity of tumor cell populations in organoids were significantly perturbed by drug treatment. Single-cell analysis detected the depletion of chemosensitive subgroups and emergence of new drug tolerant subgroups after drug treatment. Our study suggests that the organoid model is capable of recapitulating clinical heterogeneity and its evolution in response to chemotherapy.

The Lipidyzer platform was recently updated on a SCIEX QTRAP 6500+ mass spectrometer and offers a targeted lipidomics assay including 1150 different lipids. We evaluated this targeted approach using human plasma samples and compared the results against a global untargeted lipidomics method using a high-resolution Q Exactive HF Orbitrap mass spectrometer. Lipids from human plasma samples (N = 5) were extracted using a modified Bligh-Dyer approach. A global untargeted analysis was performed using a Thermo Orbitrap Q Exactive HF mass spectrometer, followed by data analysis using Progenesis QI software. Multiple reaction monitoring (MRM)-based targeted analysis was performed using a QTRAP 6500+ mass spectrometer, followed by data analysis using SCIEX OS software. The samples were injected on three separate days to assess reproducibility for both approaches. Overall, 465 lipids were identified from 11 lipid classes in both approaches, of which 159 were similar between the methods, 168 lipids were unique to the MRM approach, and 138 lipids were unique to the untargeted approach. Phosphatidylcholine and phosphatidylethanolamine species were the most commonly identified using the untargeted approach, while triacylglycerol species were the most commonly identified using the targeted MRM approach. The targeted MRM approach had more consistent relative abundances across the three days than the untargeted approach. Overall, the coefficient of variation for inter-day comparisons across all lipid classes was ∼ 23% for the untargeted approach and ∼ 9% for the targeted MRM approach. The targeted MRM approach identified similar numbers of lipids to a conventional untargeted approach, but had better representation of 11 lipid classes commonly identified by both approaches. Based on the separation methods employed, the conventional untargeted approach could better detect phosphatidylcholine and sphingomyelin lipid classes. The targeted MRM approach had lower inter-day variability than the untargeted approach when tested using a small group of plasma samples. These studies highlight the advantages in using targeted MRM approaches for human plasma lipidomics analysis.

This study develops an efficient and accurate pipeline for classifying tumor-derived organoid candidates as benign or malignant, addressing challenges posed by organoid culture and advancing personalized medicine applications. Background: Tumor-derived organoids replicate tumor architecture and molecular features, providing controlled environments to study tumor behavior and therapeutic responses. A key challenge in using organoid models is classifying cellular aggregates as benign or malignant. Benign cells in a tumor source can sometimes outcompete malignant tumor cells in culture, misrepresenting the tumor's characteristics. Also, histological characterization of organoids is challenging due to the absence of histologic clues from tissue organization. Current approaches, such as genomic sequencing, effectively resolve such uncertainties but are costly and time-intensive. Hypothesis: We hypothesized that a deep learning (DL) based computational image analysis classification pipeline could improve the accuracy and efficiency of distinguishing organoids as benign or malignant. Methods: We developed a novel pipeline to enhance organoid classification methods using ML. Our pipeline was developed and validated on H&E-stained slides obtained from organoids derived from 17 colorectal cancer patients (26 slides: 11 tumor, 15 normal) with various degrees of differentiation and paired normal controls. Ground truth data were established using a comprehensive genomic profiling panel to confirm that tumor organoids matched primary tumor features and, for tumors with high microsatellite instability, mismatch repair protein status. We first trained a segmentation model using a Human-in-the-Loop approach for precise identification of regions of interest. We extracted non overlapping 256x256 tiles at 20x magnification. We used the UNI foundation model to extract (k=1024) relevant features from each tile. We fitted Linear Discriminant Analysis (LDA) models on the UNI feature vectors using leave-one-patient-out cross validation according to patients. Each slide's final classification score was determined by averaging the LDA scores across all tiles from that slide. Results: The LDA classifier achieved 92.3% accuracy and AUROC of 0.964 (0.907-1.000), matching gastrointestinal pathologist performance. Additionally, we visualized the UNI feature vectors through UMAP plots. Plot evaluation demonstrates distinct clustering of unsupervised features into tumor and normal groups. Conclusions: These findings demonstrate the feasibility of coupling organoids with DL methods to facilitate organoid classification. Our approach offers an efficient new strategy for studying organoid morphology and advancing organoid models. Adaptations of this model are expected to be valuable in understanding organoid responses to various therapies, paving the way for improved personalized cancer care. Citation Format: Adi Orlyanchik, Matteo Sacco, James Dolezal, Joseph Kainov, Piao Zhao, Mohammed Aziz Khan, Marina Garassino, Marc Bissonnette, Le Shen, Alexander T. Pearson, Christopher Weber. Digital pathology foundation models enable accurate tumor organoid classification [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 39.

Glioblastoma stem cell (GSC) cultures are initiated from glioblastoma (GBM) surgical resection tissue. When grown appropriately they can capture and propagate key GBM molecular and cellular features. We have characterized cellular, genomic and proteomic features of four isocitrate dehydrogenase (IDH)-expressing (IDH +) GSC cultures as cellular models for ~ 90% of adult GBMs. We demonstrate that GSC cultures can be continuously propagated in defined, serum-free media and 5% oxygen without specialized growth substrates; have culture-specific genomic and mtDNA variants together with gene/protein expression profiles; and display reproducible dose-survival curves for the GBM standard-of-care therapies ionizing radiation (IR) and temozolomide (TMZ). In order to better define GSC culture cellular heterogeneity and dynamics, we used lentiviral DNA barcoding, mtDNA variants and single cell gene expression profiling over 40 days after IR treatment. GSC cultures are versatile in their ability to support many in vitro protocols including high throughput screens as well as xenograft, organoid and other disease modeling protocols. They provide a simple cellular disease model for better understanding GBM biology, and for identifying new, potentially more effective GBM therapies and treatment regimens.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-33082-8.