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As 3D culture technology advances, new avenues have opened for the development of physiological human cancer models. These preclinical models provide efficient ways to translate basic cancer research into clinical tumor therapies. Recently, cancer organoids have emerged as a model to dissect the more complex tumor microenvironment. Incorporating cancer organoids into preclinical programs have the potential to increase the success rate of oncology drug development and recapitulate the most efficacious treatment regimens for cancer patients. In this review, four main types of cancer organoids are introduced, their applications, advantages, limitations, and prospects are discussed, as well as the recent application of single-cell RNA-sequencing (scRNA-seq) in exploring cancer organoids to advance this field.

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In vitro models coupled with multimodal approaches are needed to dissect the dynamic response of local tumor immune microenvironment (TIME) to immunotherapy. Here the patient-derived primary lung cancer organoids (pLCOs) are generated by isolating tumor cell clusters, including the infiltrated immune cells. A function-associated single-cell RNA sequencing (FascRNA-seq) platform allowing both phenotypic evaluation and scRNA-seq at single-organoid level is developed to dissect the TIME of individual pLCOs. The analysis of 171 individual pLCOs derived from seven patients reveals that pLCOs retain the TIME heterogeneity in the parenchyma of parental tumor tissues, providing models with identical genetic background but various TIME. Linking the scRNA-seq data of individual pLCOs with their responses to anti-PD-1 (αPD-1) immune checkpoint blockade (ICB) allows to confirm the central role of CD8+ T cells in anti-tumor immunity, to identify potential tumor-reactive T cells with a set of 10 genes, and to unravel the factors regulating T cell activity, including CD99 gene. In summary, the study constructs a joint phenotypic and transcriptomic FascRNA-seq platform to dissect the dynamic response of local TIME under ICB treatment, providing a promising approach to evaluate novel immunotherapies and to understand the underlying molecular mechanisms.

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BACKGROUND: Within the last decade, poly(ADP-ribose) polymerase inhibitors (PARPi) have emerged in the clinic as an effective treatment for numerous malignancies. Preclinical data have demonstrated powerful combination effects of PARPi paired with photodynamic therapy (PDT), which involves light-activation of specialized dyes (photosensitizers) to stimulate cancer cell death through reactive oxygen species generation. RESULTS: In this report, the most potent clinical PARP inhibitor, talazoparib, is loaded into the core of a polymeric nanoparticle (NP-Tal), which is interfaced with antibody-photosensitizer conjugates (photoimmunoconjugates, PICs) to form PIC-NP-Tal. In parallel, a new 3D fluorescent coculture model is developed using the parental OVCAR-8-DsRed2 and the chemo-resistant subline, NCI/ADR-RES-EGFP. This model enables quantification of trends in the evolutionary dynamics of acquired chemoresistance in response to various treatment regimes. Results reveal that at a low dosage (0.01 µM), NP-Tal kills the parental cells while sparing the chemo-resistant subline, thereby driving chemoresistance. Next, PIC-NP-Tal and relevant controls are evaluated in the 3D coculture model at multiple irradiation doses to characterize effects on total spheroid ablation and relative changes in parental and subline cell population dynamics. Total spheroid ablation data shows potent combination effects when PIC and NP-Tal are co-administered, but decreased efficacy with the conjugated formulation (PIC-NP-Tal). Analysis of cell population dynamics reveals that PIC, BPD + NP-Tal, PIC + NP-Tal, and PIC-NP-Tal demonstrate selection pressures towards chemoresistance. CONCLUSIONS: This study provides key insights into manufacturing parameters for PARPi-loaded nanoparticles, as well as the potential role of PDT-based combination therapies in the context of acquired drug resistance.

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INTRODUCTION: Hypoxia-inducible factor 1 (HIF-1) is a transcriptional activator mediating adaptive responses to hypoxia. It is up-regulated in the tumor microenvironment and recognized as an effective anticancer drug target. Previously, we discovered that the natural compound moracin-O and its synthetic derivative MO-460 inhibited HIF-1α via hnRNPA2B1. OBJECTIVES: This study aimed to develop novel HIF-1 inhibitors for cancer chemotherapy by harnessing the potential of the natural products moracins-O and P. METHODS: In an ongoing search for novel HIF-1 inhibitors, a series of nature-inspired benzofurans with modifications on the chiral rings of moracins-O and P were synthesized. They showed improved chemical tractability and were evaluated for their inhibitory activity on HIF-1α accumulation under hypoxic conditions in HeLa CCL2 cells. The most potent derivative's chemical-based toxicities, binding affinities, and in vivo anti-tumorigenic effects were evaluated. Further, we examined whether our compound, MO-2097, exhibited anticancer effects in three-dimensional cultured organoids. RESULTS: Herein, we identified a novel synthetic chiral-free compound, MO-2097, with reduced structural complexity and increased efficiency. MO-2097 exhibited inhibitory effects on hypoxia-induced HIF-1α accumulation in HeLa CCL2 cells via inhibition of hnRNPA2B1 protein, whose binding affinities were confirmed by isothermal titration calorimetry analysis. In addition, MO-2097 demonstrated in vivo efficacy and biocompatibility in a BALB/c mice xenograft model. The immunohistochemistry staining of MO-2097-treated tissues showed decreased expression of HIF-1α and increased levels of apoptosis marker cleaved caspase 3, confirming in vivo efficacy. Furthermore, we confirmed that MO-2097 works effectively in cancer patient-based organoid models. CONCLUSION: MO-2097 represents a promising new generation of chemotherapeutic agents targeting HIF-1α inhibition via hnRNPA2B1, requiring further investigation.

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BACKGROUND: Recently, cancer organoid-based drug sensitivity tests have been studied to predict patient responses to anticancer drugs. The area under curve (AUC) or IC50 value of the dose-response curve (DRC) is used to differentiate between sensitive and resistant patient's groups. This study proposes a multi-parameter analysis method (cancer organoid-based diagnosis reactivity prediction, CODRP) that considers the cancer stage and cancer cell growth rate, which represent the severity of cancer patients, in the sensitivity test. METHODS: On the CODRP platform, patient-derived organoids (PDOs) that recapitulate patients with lung cancer were implemented by applying a mechanical dissociation method capable of high yields and proliferation rates. A disposable nozzle-type cell spotter with efficient high-throughput screening (HTS) has also been developed to dispense a very small number of cells due to limited patient cells. A drug sensitivity test was performed using PDO from the patient tissue and the primary cancer characteristics of PDOs were confirmed by pathological comparision with tissue slides. RESULTS: The conventional index of drug sensitivity is the AUC of the DRC. In this study, the CODRP index for drug sensitivity test was proposed through multi-parameter analyses considering cancer cell proliferation rate, the cancer diagnosis stage, and AUC values. We tested PDOs from eight patients with lung cancer to verify the CODRP index. According to the anaplastic lymphoma kinase (ALK) rearrangement status, the conventional AUC index for the three ALK-targeted drugs (crizotinib, alectinib, and brigatinib) did not classify into sensitive and resistant groups. The proposed CODRP index-based drug sensitivity test classified ALK-targeted drug responses according to ALK rearrangement status and was verified to be consistent with the clinical drug treatment response. CONCLUSIONS: Therefore, the PDO-based HTS and CODRP index drug sensitivity tests described in this paper may be useful for predicting and analyzing promising anticancer drug efficacy for patients with lung cancer and can be applied to a precision medicine platform.

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Introduction: Lung tumor organoids (LTOs) have attracted attention as in vitro preclinical models; however, their clinical and experimental applications have not been fully established. Methods: We attempted to establish LTOs from resected specimens of patients with lung cancer who underwent lung resection. Clinicopathologic characteristics related to the establishment of LTOs were evaluated. Histologic assessment and genetic analysis were conducted for both LTOs and their parental tumors. Organoid-derived xenografts were generated in immunocompetent mice. Drug sensitivity was assessed using cell proliferation assays. Results: We established 53 LTOs from 79 lung cancer samples, including 10 long-term culture models. The establishment rate was significantly lower in squamous cell carcinomas than in other histologic types (48% versus 75%, p = 0.034). Histologic similarities were confirmed among LTOs, the parental tumors, and organoid-derived xenografts. Seven mutations, including two EGFR L858R and one EGFR exon 20 H773delinsYNPY mutations, were detected in both LTO and parental tumors; the other four mutations were detected in either LTO or parental tumors. The extensive culture ability of LTO (passaged >10 times) correlated with poor patient prognosis. LTO9 cells harboring EGFR H773delinsYNPY were sensitive to osimertinib. The parental patient, who had new metastatic lesions, was treated with osimertinib and exhibited a remarkable response. Conclusions: The establishment and growth rates of LTOs were associated with the histologic subtype and tumor size. LTOs derived from resected specimens have become preclinical models that can be used to predict drug responses and accelerate the development of treatment strategies for patients with rare mutations.

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So far, ovarian cancer has still been the most lethal gynecological malignancy. The chemotherapy and targeted medication are the mainstay for the recurrent ovarian cancer treatment. About 70% of the advanced-stage cases will relapse. Ascites-derived organoid is a pre-clinical model for the precise prediction of the therapeutic effectiveness for the ovarian cancer: it can be used to assess the drug sensitivity, to guide individualized precise treatment, and to improve advanced stage as well as recurrent ovarian cancer patient' survival and prognosis. Until now, there has been no report concerning the establishment of the organoid out of the patient's ascites and the concurrent usage of drug sensitivity test to guide the individualized precise treatment for the ovarian cancer. Here, we report a case of recurrent ovarian cancer of a 59-year-old female patient whose CA125 at its peak increased to 4523.4 U/mL. Then, patient's own ovarian cancer organoid was constructed from the ascites by the abdominocentesis; concurrently, medication sensitivity test was performed on the organoid to guide individualized precise treatment. After the treatment, CA125 decreased to 33.7 U/mL, and the patient's condition relieved effectively. This is the first published case report using ascites-derived organoid and the drug sensitivity test thereof to guide the precise treatment of recurrent ovarian cancer.

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Ovarian cancer (OC), particularly high-grade serous cancer (HGSC), is the leading cause of mortality among gynecological cancers owing to the treatment difficulty and high recurrence probability. As therapeutic drugs approved for OC, poly ADP-ribose polymerase inhibitors (PARPi) lead to synthetic lethality by inhibiting single-strand DNA repair, particularly in homologous recombination-deficient cancers. However, even PARPi have distinct efficacies and are prone to have drug resistance, the molecular mechanisms underlying the PARPi resistance in OC remain unclear. A patient-derived organoid platform was generated and treated with a PARPi to understand the factors associated with PARPi resistance. PARPi significantly inhibits organoid growth. After 72 h of treatment, both the size of organoids and the numbers of adherent cells decreased. Moreover, immunofluorescence results showed that the proportion of Ki67 positive cells significantly reduced. When the PARPi concentration reached 200 nM, the percentage of Ki67+/4',6-diamidino-2-phenylindole (DAPI) cells decreased approximately 50%. PARPi treatment also affected the expression of genes involved in base excision repair and cell cycle. Functional assays revealed that PARPi inhibits cell growth by upregulating early apoptosis. The expression levels of several key genes were validated. In addition to previously reported genes, some promising genes FEN1 and POLA2, were also be founded. The results demonstrate the complex effects of PARPi treatment on changes in potential genes relevant to PARPi resistance, and provide perspectives for further research on the PARPi resistance mechanisms.

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Krukovine (KV) is an alkaloid isolated from the bark of Abuta grandifolia (Mart.) Sandw. (Menispermaceae) with anticancer potential in some cancers with KRAS mutations. In this study, we explored the anticancer efficacy and mechanism of KV in oxaliplatin-resistant pancreatic cancer cells and patient-derived pancreatic cancer organoids (PDPCOs) with KRAS mutation. After treatment with KV, mRNA and protein levels were determined by RNA-seq and Western blotting, respectively. Cell proliferation, migration, and invasion were measured by MTT, scratch wound healing assay, and transwell analysis, respectively. Patient-derived pancreatic cancer organoids (PDPCOs) with KRAS mutations were treated with KV, oxaliplatin (OXA), and a combination of KV and OXA. KV suppresses tumor progression via the downregulation of the Erk-RPS6K-TMEM139 and PI3K-Akt-mTOR pathways in oxaliplatin-resistant AsPC-1 cells. Furthermore, KV showed an antiproliferative effect in PDPCOs, and the combination of OXA and KV inhibited PDPCO growth more effectively than either drug alone.

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Pancreatic cancer (PC) is a fatal malignancy in the human abdominal cavity that prefers to invade the surrounding nerve/nerve plexus and even the spine, causing devastating and unbearable pain. The limitation of available in vitro models restricts revealing the molecular mechanism of pain and screening pain-relieving strategies to improve the quality of life of end-stage PC patients. Here, we report a PC nerve invasion model that merged human brain organoids (hBrO) with mouse PC organoids (mPCO). After merging hBrOs with mPCOs, we monitored the structural crosstalk, growth patterns, and mutual interaction dynamics of hBrO with mPCOs for 7 days. After 7 days, we also analyzed the pathophysiological statuses, including proliferation, apoptosis and inflammation. The results showed that mPCOs tend to approximate and intrude into the hBrOs, merge entirely into the hBrOs, and induce the retraction/shrinking of neuronal projections that protrude from the margin of the hBrOs. The approximating of mPCOs to hBrOs accelerated the proliferation of neuronal progenitor cells, intensified the apoptosis of neurons in the hBrOs, and increased the expression of inflammatory molecules in hBrOs, including NLRP3, IL-8, and IL-1ß. Our system pathophysiologically replicated the nerve invasions in mouse GEMM (genetically engineered mouse model) primary and human PCs and might have the potential to be applied to reveal the molecular mechanism of nerve invasion and screen therapeutic strategies in PCs.

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Microphysiological systems (MPSs) with three-dimensional (3D) cultured models have attracted considerable interest because of their potential to mimic human health and disease conditions. Recent MPSs have shown significant advancements in engineering perfusable vascular networks integrated with 3D culture models, realizing a more physiological environment in vitro; however, a sensing system that can monitor their activity under biomimetic vascular flow is lacking. We designed an open-top microfluidic device with sensor capabilities and demonstrated its application in analyzing oxygen metabolism in vascularized 3D tissue models. We first validated the platform by using human lung fibroblast (hLF) spheroids. Then, we applied the platform to a patient-derived cancer organoid and evaluated the changes in oxygen metabolism during drug administration through the vascular network. We found that the platform could integrate a perfusable vascular network with 3D cultured cells, and the electrochemical sensor could detect the change in oxygen metabolism in a quantitative, non-invasive, and real-time manner. This platform would become a monitoring system for 3D cultured cells integrated with a perfusable vascular network.

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Intensive efforts to develop anti-cancer agents have been made for over 60 years. However, cancer is still considered a lethal disease. To study the best anti-cancer agents for improving the survival rates of cancer patients, many researchers have focused on establishing advanced experimental applications reflecting on the biomimetics of cancer patients involving the heterogeneity of cancer cells. The heterogeneity of cancer cells, which are derived from various clones and affected by different environments, presents different genetic backgrounds and molecular characteristics attributed to the differential responses to cancer therapies, and these are responsible for the resistance to cancer therapies, as well as for recurrence following cancer treatments. Therefore, the development of advanced applications for the cancer patient is expected to help the development of more effective anti-cancer agents. The present review evaluates recently developed cancer models encompassing the heterogeneity of cancer cells, which present similar morphological architecture, genetic backgrounds, and molecular characteristics to corresponding patient tumor tissues.

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The data presented in this article is related to a rapid communication entitled "ß-arrestin 2 suppresses the activation of YAP by promoting LATS kinase activity". This article describes the correlation of ß-arrestin 2 and YAP phosphorylation in patient-derived organoid models. Here, we analyzed 45 colon cancer organoids (CCOs) selected in the related research article to investigate the role of ß-arrestin 2 in YAP phosphorylation. Hematoxylin and eosin (H&E) staining and immunohistochemistry data showed that the CCOs maintained tissue architecture and histological features of their original cancer tissues. Moreover, mutation data detected from RNA-seq (RNA-sequencing) analysis showed that these CCOs retained the genetic features of their original colon cancer tissues as well. We also confirmed at the protein level that organoids expressing ß-arrestin 2 showed high expression of phosphorylated YAP. These organoid model studies strongly support the related research article that ß-arrestin 2 suppresses the activation of YAP in colon cancer.

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Background: Pancreatic ductal adenocarcinoma (PDAC), which commonly relapses due to chemotherapy resistance, has a poor 5-year survival rate (< 10%). The ability of PDAC to dynamically switch between cancer-initiating cell (CIC) and non-CIC states, which is influenced by both internal and external events, has been suggested as a reason for the low drug efficacy. However, cancer cell plasticity using patient-derived PDAC organoids remains poorly understood. Methods: First, we successfully differentiated CICs, which were the main components of PDAC organoids, toward epithelial ductal carcinomas. We further established PDAC assembloids of organoid-derived differentiated ductal cancer cells with endothelial cells (ECs) and autologous immune cells. To investigate the mechanism for PDAC plasticity, we performed single-cell RNA sequencing analysis after culturing the assembloids for 7 days. Results: In the PDAC assembloids, the ECs and immune cells acted as tumor-supporting cells and induced plasticity in the differentiated ductal carcinomas. We also observed that the transcriptome dynamics during PDAC re-programming were related to the WNT/beta-catenin pathway and apoptotic process. Interestingly, we found that WNT5B in the ECs was highly expressed by trans interaction with a JAG1. Furthermore, JAG1 was highly expressed on PDAC during differentiation, and NOTCH1/NOTCH2 were expressed on the ECs at the same time. The WNT5B expression level correlated positively with those of JAG1, NOTCH1, and NOTCH2, and high JAG1 expression correlated with poor survival. Additionally, we experimentally demonstrated that neutralizing JAG1 inhibited cancer cell plasticity. Conclusions: Our results indicate that JAG1 on PDAC plays a critical role in cancer cell plasticity and maintenance of tumor heterogeneity.

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Organoid culture technique has been taking center stage as a next-generation ex-vivo model due to advancement of stem cell research techniques. The importance of the laboratory-based ex vivo model has increasingly been recognized for recapitulating histological, and physioglocal conditions of in vivo microenviorment. Accordingly, the use of this technique has also broadened the understanding of intratumoral heterogeneity which is closely associated with varied drug responses observed in patients. Likewise, studies on heterogeneity within a single tumor tissue have drawn much attention. Here, we isolated 15 single clones from 4 tumor organoid lines from 1 patient at a primary passage from one patient. Each organoid line showed variable alterations in both genotype and phenotype. Furthermore, our methodological approach on drug test employing a high-throughput screening system enabled us to pinpoint the optimal time frame for anti-cancer drugs within a single tumor. We propose that our method can effectively reveal the heterogeneity of time-point in drug response, and the most optimal therapeutic strategies for individual patient.

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The cancer burden is rapidly increasing in most countries, and thus, new anticancer drugs for effective cancer therapy must be developed. Cancer model systems that recapitulate the biological processes of human cancers are one of the cores of the drug development process. PDCO has emerged as a unique model that preserves the genetic, physiological, and histologic characteristics of original cancer, including inter- and intratumoral heterogeneities. Due to these advantages, the PCDO model is increasingly investigated for anticancer drug screening and efficacy testing, preclinical patient stratification, and precision medicine for selecting the most effective anticancer therapy for patients. Here, we review the prospects and limitations of PDCO compared to the conventional cancer models. With advances in culture success rates, co-culture systems with the tumor microenvironment, organoid-on-a-chip technology, and automation technology, PDCO will become the most promising model to develop anticancer drugs and precision medicine.

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Organoids are self-organized three-dimensional in vitro cell cultures derived from stem cells. They can recapitulate organ development, tissue regeneration, and disease progression and, hence, have broad applications in drug discovery. However, the lack of effective graphic algorithms for organoid growth analysis has slowed the development of organoid-based drug screening. In this study, we take advantage of a bladder cancer organoid system and develop a deep learning model, the res-double dynamic conv attention U-Net (RDAU-Net) model, to improve the efficiency and accuracy of organoid-based drug screenings. In this RDAU-Net model, the dynamic convolution and attention modules are integrated. The feature-extracting capability of the encoder and the utilization of multi-scale information are substantially enhanced, and the semantic gap caused by skip connections has been filled, which substantially improved its anti-interference ability. A total of 200 images of bladder cancer organoids on culture days 1, 3, 5, and 7, with or without drug treatment, were employed for training and testing. Compared with the other variations of the U-Net model, the segmentation indicators, such as Intersection over Union and dice similarity coefficient, in the RDAU-Net model have been improved. In addition, this algorithm effectively prevented false identification and missing identification, while maintaining a smooth edge contour of segmentation results. In summary, we proposed a novel method based on a deep learning model which could significantly improve the efficiency and accuracy of high-throughput drug screening and evaluation using organoids.

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Using STAT3 inhibitors as a potential strategy in cancer therapy have attracted much attention. Recently, celastrol has been reported that it could directly bind to and suppress the activity of STAT3 in the cardiac dysfunction model. To explore more effective STAT3 inhibiting anti-tumour drug candidates, we synthesised a series of celastrol derivatives and biologically evaluated them with several human cancer cell lines. The western blotting analysis showed that compound 4 m, the most active derivative, could suppress the STAT3's phosphorylation as well as its downstream genes. SPR analysis, molecular docking and dynamics simulations' results indicated that the 4m could bind with STAT3 protein more tightly than celastrol. Then we found that the 4m could block cell-cycle and induce apoptosis on HCT-116 cells. Furthermore, the anti-tumour effect of 4m was verified on colorectal cancer organoid. This is the first research that discovered effective STAT3 inhibitors as potent anti-tumour agents from celastrol derivatives.

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As the importance of organoids increases, the need to develop organoid culture systems suitable for basic biological and clinical applications is being emphasized. However, there is still an unmet need to produce functionally complex and scalable uniform organoids. Here, we demonstrate a scalable organoid production platform with 8 well strips and a total of 8 × 9 microwells per strip using organoids derived from colorectal cancer tissue. The new culture platform is a format in which single cells are self-organized into organoids in culture medium supplemented with 2% Matrigel. It is functionally compatible with existing 96 well plates and Matrigel based conventional organoid culture methods. The consistency, uniformity and reproducibility of organoid produced on the new platform have been significantly improved compared to those of conventional plates. Importantly, Hydro-organoids are functionally identical to conventional Matrigel organoids, but show better consistency in drug screening. Our results show the possibility that Hydro-organoids can be used in high-throughput assays and incorporated into drug screening models to predict clinical outcomes.

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SIGNIFICANCE: Accessible tools are needed for rapid, non-destructive imaging of patient-derived cancer organoid (PCO) treatment response to accelerate drug discovery and streamline treatment planning for individual patients. AIM: To segment and track individual PCOs with wide-field one-photon redox imaging to extract morphological and metabolic variables of treatment response. APPROACH: Redox imaging of the endogenous fluorophores, nicotinamide dinucleotide (NADH), nicotinamide dinucleotide phosphate (NADPH), and flavin adenine dinucleotide (FAD), was used to monitor the metabolic state and morphology of PCOs. Redox imaging was performed on a wide-field one-photon epifluorescence microscope to evaluate drug response in two colorectal PCO lines. An automated image analysis framework was developed to track PCOs across multiple time points over 48 h. Variables quantified for each PCO captured metabolic and morphological response to drug treatment, including the optical redox ratio (ORR) and organoid area. RESULTS: The ORR (NAD(P)H/(FAD + NAD(P)H)) was independent of PCO morphology pretreatment. Drugs that induced cell death decreased the ORR and growth rate compared to control. Multivariate analysis of redox and morphology variables identified distinct PCO subpopulations. Single-organoid tracking improved sensitivity to drug treatment compared to pooled organoid analysis. CONCLUSIONS: Wide-field one-photon redox imaging can monitor metabolic and morphological changes on a single organoid-level, providing an accessible, non-destructive tool to screen drugs in patient-matched samples.

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