U-Shape Pillar Strip for 3D Cell-Lumped Organoid Model (3D-COM) Mimicking Lung Cancer Hypoxia Conditions in High-Throughput Screening (HTS).

Hypoxia is a representative tumor characteristic associated with malignant progression in clinical patients. Engineered in vitro models have led to significant advances in cancer research, allowing for the investigation of cells in physiological environments and the study of disease mechanisms and processes with enhanced relevance. In this study, we propose a U-shape pillar strip for a 3D cell-lumped organoid model (3D-COM) to study the effects of hypoxia on lung cancer in a high-throughput manner. We developed a U-pillar strip that facilitates the aggregation of PDCs mixed with an extracellular matrix to make the 3D-COM in 384-plate array form. The response to three hypoxia-activated prodrugs was higher in the 3D-COM than in the 2D culture model. The protein expression of hypoxia-inducible factor 1 alpha (HIF-1α) and HIF-2α, which are markers of hypoxia, was also higher in the 3D-COM than in the 2D culture. The results show that 3D-COM better recapitulated the hypoxic conditions of lung cancer tumors than the 2D culture. Therefore, the U-shape pillar strip for 3D-COM is a good tool to study the effects of hypoxia on lung cancer in a high-throughput manner, which can efficiently develop new drugs targeting hypoxic tumors.

An Automated High-Throughput Screening (HTS) Spotter for 3D Tumor Spheroid Formation.

Three-dimensional (3D) culture platforms have been adopted in a high-throughput screening (HTS) system to mimic in vivo physiological microenvironments. The automated dispenser has been established commercially to enable spotting or distributing non-viscous or viscous biomaterials onto microplates. However, there are still challenges to the precise and accurate dispensation of cells embedded in hydrogels such as Alginate- and Matrigel-extracellular matrices. We developed and improved an automated contact-free dispensing machine, the ASFA SPOTTER (V5 and V6), which is compatible with 96- and 384-pillar/well plates and 330- and 532-micropillar/well chips for the support of 3D spheroid/organoid models using bioprinting techniques. This enables the distribution of non-viscous and viscous biosamples, including chemical drugs and cancer cells, for large-scale drug screening at high speed and small volumes (20 to 4000 nanoliters) with no damage to cells. The ASFA SPOTTER (V5 and V6) utilizes a contact-free method that minimizes cross-contamination for the dispensation of encapsulated tissue cells with highly viscous scaffolds (over 70%). In particular, the SPOTTER V6 does not require a washing process and offers the advantage of almost no dead volume (defined as additional required sample volume, including a pre-shot and flushing shot for dispensing). It can be successfully applied for the achievement of an organoid culture in automation, with rapid and easy operation, as well as miniaturization for high-throughput screening. In this study, we report the advantages of the ASFA SPOTTER, which distributes standard-sized cell spots with hydrogels onto a 384-pillar/well plate with a fast dispensing speed, small-scale volume, accuracy, and precision.

Cell Proliferation Receptor-Enhanced 3D High-Throughput Screening Model for Optimized Drug Efficacy Evaluation in Breast Cancer Cells.

A higher correlation of epidermal growth factor receptor (EGFR)-targeting drugs has been reported with the use of the cell proliferation receptor-enhanced three-dimensional high-throughput screening model (CPRE 3D-HTS model) compared with two-dimensional (2D) cell-based HTS. A greater expression of differential human EGFR 2 (HER2) protein between HER2-positive and HER2-negative cell lines was observed in breast cancer (BC) cell lines cultured using the CPRE 3D-HTS model compared with 2D-cultured cells. When using 2D-cultured cells, properties such as the expression of the cell proliferation receptor are lost as the cells attach to the bottom of the well plate. In an effort to solve this problem, the CPRE 3D-HTS model expressing high cell proliferation receptors was optimized by the selection of alginate as the extracellular matrix. Results from the use of the CPRE 3D-HTS model showed higher drug resistance with increased expression of drug resistance-related proteins. Of particular interest, a higher correlation of HER2-targeted drugs was observed with the use of the CPRE 3D-HTS model. In order to validate this higher correlation of target drugs observed in the CPRE 3D-HTS model, the results of Western blot analysis and high content imaging analysis were analyzed, which confirmed that 3D-cultured BC cell lines showed a greater difference in the expression of HER2-positive and HER2-negative BC cell lines than 2D-cultured cells. Thus, the use of CPRE 3D-HTS using a 384-pillar plate resulted in increased accuracy when screening HER2-targeted drugs in BC, and it is a very useful platform for analyzing the efficacy of targeted drugs by enhancing the expression of HER2.

Patient-Derived Tumor Organoids for Guidance of Personalized Drug Therapies in Recurrent Glioblastoma.

An obstacle to effective uniform treatment of glioblastoma, especially at recurrence, is genetic and cellular intertumoral heterogeneity. Hence, personalized strategies are necessary, as are means to stratify potential targeted therapies in a clinically relevant timeframe. Functional profiling of drug candidates against patient-derived glioblastoma organoids (PD-GBO) holds promise as an empirical method to preclinically discover potentially effective treatments of individual tumors. Here, we describe our establishment of a PD-GBO-based functional profiling platform and the results of its application to four patient tumors. We show that our PD-GBO model system preserves key features of individual patient glioblastomas in vivo. As proof of concept, we tested a panel of 41 FDA-approved drugs and were able to identify potential treatment options for three out of four patients; the turnaround from tumor resection to discovery of treatment option was 13, 14, and 15 days, respectively. These results demonstrate that this approach is a complement and, potentially, an alternative to current molecular profiling efforts in the pursuit of effective personalized treatment discovery in a clinically relevant time period. Furthermore, these results warrant the use of PD-GBO platforms for preclinical identification of new drugs against defined morphological glioblastoma features.

Inhibition of SARS-CoV-2 Virus Entry by the Crude Polysaccharides of Seaweeds and Abalone Viscera In Vitro.

Much attention is being devoted to the potential of marine sulfated polysaccharides as antiviral agents in preventing COVID-19. In this study, sulfated fucoidan and crude polysaccharides, extracted from six seaweed species (Undaria pinnatifida sporophyll, Laminaria japonica, Hizikia fusiforme, Sargassum horneri, Codium fragile, Porphyra tenera) and Haliotis discus hannai (abalone viscera), were screened for their inhibitory activity against SARS-CoV-2 virus entry. Most of them showed significant antiviral activities at an IC50 of 12~289 µg/mL against SARS-CoV-2 pseudovirus in HEK293/ACE2, except for P. tenera (IC50 > 1000 µg/mL). The crude polysaccharide of S. horneri showed the strongest antiviral activity, with an IC50 of 12 µg/mL, to prevent COVID-19 entry, and abalone viscera and H. fusiforme could also inhibit SARS-CoV-2 infection with an IC50 of 33 µg/mL and 47 µg/mL, respectively. The common properties of these crude polysaccharides, which have strong antiviral activity, are high molecular weight (>800 kDa), high total carbohydrate (62.7~99.1%), high fucose content (37.3~66.2%), and highly branched polysaccharides. These results indicated that the crude polysaccharides from seaweeds and abalone viscera can effectively inhibit SARS-CoV-2 entry.

Antiviral Activity of Two Marine Carotenoids against SARS-CoV-2 Virus Entry In Silico and In Vitro.

The marine carotenoids fucoxanthin and siphonaxanthin are powerful antioxidants that are attracting focused attention to identify a variety of health benefits and industry applications. In this study, the binding energy of these carotenoids with the SARS-CoV-2 Spike-glycoprotein was predicted by molecular docking simulation, and their inhibitory activity was confirmed with SARS-CoV-2 pseudovirus on HEK293 cells overexpressing angiotensin-converting enzyme 2 (ACE2). Siphonaxanthin from Codium fragile showed significant antiviral activity with an IC50 of 87.4 µM against SARS-CoV-2 pseudovirus entry, while fucoxanthin from Undaria pinnatifida sporophyll did not. The acute toxicities were predicted to be relatively low, and pharmacokinetic predictions indicate GI absorption. Although further studies are needed to elucidate the inhibition of viral infection by siphonaxanthin, these results provide useful information in the application of these marine carotenoids for the treatment and prevention of COVID-19.

Three-Dimensional Aggregated Spheroid Model of Hepatocellular Carcinoma Using a 96-Pillar/Well Plate.

A common method of three-dimensional (3D) cell cultures is embedding single cells in Matrigel. Separated cells in Matrigel migrate or grow to form spheroids but lack cell-to-cell interaction, which causes difficulty or delay in forming mature spheroids. To address this issue, we proposed a 3D aggregated spheroid model (ASM) to create large single spheroids by aggregating cells in Matrigel attached to the surface of 96-pillar plates. Before gelling the Matrigel, we placed the pillar inserts into blank wells where gravity allowed the cells to gather at the curved end. In a drug screening assay, the ASM with Hepatocellular carcinoma (HCC) cell lines showed higher drug resistance compared to both a conventional spheroid model (CSM) and a two-dimensional (2D) cell culture model. With protein expression, cytokine activation, and penetration analysis, the ASM showed higher expression of cancer markers associated with proliferation (p-AKT, p-Erk), tight junction formation (Fibronectin, ZO-1, Occludin), and epithelial cell identity (E-cadherin) in HCC cells. Furthermore, cytokine factors were increased, which were associated with immune cell recruitment/activation (MIF-3α), extracellular matrix regulation (TIMP-2), cancer interaction (IL-8, TGF-ß2), and angiogenesis regulation (VEGF-A). Compared to CSM, the ASM also showed limited drug penetration in doxorubicin, which appears in tissues in vivo. Thus, the proposed ASM better recapitulated the tumor microenvironment and can provide for more instructive data during in vitro drug screening assays of tumor cells and improved prediction of efficacious drugs in HCC patients.

Prediction of metabolism-induced hepatotoxicity on three-dimensional hepatic cell culture and enzyme microarrays.

Human liver contains various oxidative and conjugative enzymes that can convert nontoxic parent compounds to toxic metabolites or, conversely, toxic parent compounds to nontoxic metabolites. Unlike primary hepatocytes, which contain myriad drug-metabolizing enzymes (DMEs), but are difficult to culture and maintain physiological levels of DMEs, immortalized hepatic cell lines used in predictive toxicity assays are easy to culture, but lack the ability to metabolize compounds. To address this limitation and predict metabolism-induced hepatotoxicity in high-throughput, we developed an advanced miniaturized three-dimensional (3D) cell culture array (DataChip 2.0) and an advanced metabolizing enzyme microarray (MetaChip 2.0). The DataChip is a functionalized micropillar chip that supports the Hep3B human hepatoma cell line in a 3D microarray format. The MetaChip is a microwell chip containing immobilized DMEs found in the human liver. As a proof of concept for generating compound metabolites in situ on the chip and rapidly assessing their toxicity, 22 model compounds were dispensed into the MetaChip and sandwiched with the DataChip. The IC50 values obtained from the chip platform were correlated with rat LD50 values, human C max values, and drug-induced liver injury categories to predict adverse drug reactions in vivo. As a result, the platform had 100% sensitivity, 86% specificity, and 93% overall predictivity at optimum cutoffs of IC50 and C max values. Therefore, the DataChip/MetaChip platform could be used as a high-throughput, early stage, microscale alternative to conventional in vitro multi-well plate platforms and provide a rapid and inexpensive assessment of metabolism-induced toxicity at early phases of drug development.

High-throughput screening (HTS) of anticancer drug efficacy on a micropillar/microwell chip platform.

Contemporary cancer therapy refers to treatment based on genetic abnormalities found in patient's tumor. However, this approach is faced with numerous challenges, including tumor heterogeneity and molecular evolution, insufficient tumor samples available along with genetic information linking to clinical outcomes, lack of therapeutic drugs containing pharmacogenomic information, and technical limitations of rapid drug efficacy tests with insufficient quantities of primary cancer cells from patients. To address these problems and improve clinical outcomes of current personalized gene-targeted cancer therapy, we have developed a micropillar/microwell chip platform, which is ideally suited for encapsulating primary cancer cells in nanoscale spots of hydrogels on the chip, generating efficacy data with various drugs, eventually allowing for a comparison of the in vitro data obtained from the chip with clinical data as well as gene expression data. As a proof of concept in this study, we have encapsulated a U251 brain cancer cell line and three primary brain cancer cells from patients (448T, 464T, and 775T) in 30 nL droplets of alginate and then tested the therapeutic efficacy of 24 anticancer drugs by measuring their dose responses. As a result, the IC50 values of 24 anticancer drugs obtained from the brain cancer cells clearly showed patient cell-specific efficacy, some of which were well-correlated with their oncogene overexpression (c-Met and FGFR1) as well as the in vivo previous results of the mouse xenograft model with the three primary brain cancer cells.

High-throughput, miniaturized clonogenic analysis of a limiting dilution assay on a micropillar/microwell chip with brain tumor cells.

The limiting dilution assay (LDA) is a clonogenic drug efficacy test designed to determine a value for drug efficacy based on an all-or-none (positive or negative) response within replicates. It also attempts to calculate minimum cell numbers for cells to form colony in each drugged conditions, wherein a large value implies high drug efficacy (as a large number of extant cells are required to start a colony). However, traditional LDAs are time-consuming to set up, often requiring many replicates for statistical analysis, and manual colony identification under a microscope to determine a positive or negative response is tedious and is susceptible to human error. To address these issues, a high-throughput miniaturized LDA assay is developed using a micropillar/microwell chip platform using an automatic colony identification method. Three glioblastoma multiforme (GBM) brain tumor isolates (448T, 464T, and 775T) are used to test this new assay, using the c-Met kinase inhibitors SU11274 and PHA665752 as the target drugs. The results show that the minimum cell number of 775T is larger than that of the other two cell types (SU11274 and PHA665752) in both the sampled drugs, a result that is in good agreement with the results of previous conventional experiments using 96 well plates.

Application of the DataChip/MetaChip technology for the evaluation of ajoene toxicity in vitro.

The DataChip is a universal platform for three-dimensional (3D) cell cultures on a micropillar chip, which can be applicable to a variety of human cells to simulate organ-specific toxicity. In addition, the MetaChip is developed for various combinations of drug metabolizing enzymes that can be spotted into the microwell chip and incubated with 3D human cells to simulate systematic compound metabolism in the human liver on a microscale format. Ajoenes have been known for various therapeutics activities, including anticancer effects, but there was limited information available in regard to their metabolism and cytotoxicity. In the present work, the metabolism-mediated toxicity of ajoenes was evaluated on a DataChip/MetaChip platform. In detail, we tested cytotoxicity of E- and Z-ajoene on 3D cultured Hep3B human hepatoma cells coupled with mixtures of drug metabolizing enzymes. Metabolic profiles of ajoenes were assessed with 23 representative drug metabolizing enzymes on the MetaChip. As a result, cytotoxicity of E-ajoene was significantly augmented in the presence of cytochrome P450 (CYP) isoforms, such as CYP2E1 and CYP3A5. Both E- and Z-ajoene were drastically detoxified in the presence of Phase II enzymes, including major UGTs, SULTs, NATs, and GSTs. Interestingly, All Mix, an artificial human liver microsome containing representative P450 mixture and phase II enzyme mixture, attenuated P450-induced cytotoxicity of ajoenes. Conclusively, we were able to confirm the metabolism-medicated toxicity of ajoenes on the chip.

Two-dimensional segmentation fusion tool: an extensible, free-to-use, user-friendly tool for combining different bidimensional segmentations.

Introduction: In several fields, the process of fusing multiple two-dimensional (2D) closed lines is an important step. For instance, this is fundamental in histology and oncology in general. The treatment of a tumor consists of numerous steps and activities. Among them, segmenting the cancer area, that is, the correct identification of its spatial location by the segmentation technique, is one of the most important and at the same time complex and delicate steps. The difficulty in deriving reliable segmentations stems from the lack of a standard for identifying the edges and surrounding tissues of the tumor area. For this reason, the entire process is affected by considerable subjectivity. Given a tumor image, different practitioners can associate different segmentations with it, and the diagnoses produced may differ. Moreover, experimental data show that the analysis of the same area by the same physician at two separate timepoints may result in different lines being produced. Accordingly, it is challenging to establish which contour line is the ground truth. Methods: Starting from multiple segmentations related to the same tumor, statistical metrics and computational procedures could be exploited to combine them for determining the most reliable contour line. In particular, numerous algorithms have been developed over time for this procedure, but none of them is validated yet. Accordingly, in this field, there is no ground truth, and research is still active. Results: In this work, we developed the Two-Dimensional Segmentation Fusion Tool (TDSFT), a user-friendly tool distributed as a free-to-use standalone application for MAC, Linux, and Windows, which offers a simple and extensible interface where numerous algorithms are proposed to "compute the mean" (i.e., the process to fuse, combine, and "average") multiple 2D lines. Conclusions: The TDSFT can support medical specialists, but it can also be used in other fields where it is required to combine 2D close lines. In addition, the TDSFT is designed to be easily extended with new algorithms thanks to a dedicated graphical interface for configuring new parameters. The TDSFT can be downloaded from the following link: https://sourceforge.net/p/tdsft.

Prediction of TKI response in EGFR-mutant lung cancer patients-derived organoids using malignant pleural effusion.

Patient-derived organoids (PDOs) are valuable in predicting response to cancer therapy. PDOs are ideal models for precision oncologists. However, their practical application in guiding timely clinical decisions remains challenging. This study focused on patients with advanced EGFR-mutated non-small cell lung cancer and employed a cancer organoid-based diagnosis reactivity prediction (CODRP)-based precision oncology platform to assess the efficacy of EGFR inhibitor treatments. CODRP was employed to evaluate EGFR-tyrosine kinase inhibitors (TKI) drug sensitivity. The results were compared to those obtained using area under the curve index. This study validated this index by testing lung cancer-derived organoids in 14 patients with lung cancer. The CODRP index-based drug sensitivity test reliably classified patient responses to EGFR-TKI treatment within a clinically suitable 10-day timeline, which aligned with clinical drug treatment responses. This approach is promising for predicting and analyzing the efficacy of anticancer, ultimately contributing to the development of a precision medicine platform.

Correction: High-dose drug heat map analysis for drug safety and efficacy in multi-spheroid brain normal cells and GBM patient-derived cells.

[This corrects the article DOI: 10.1371/journal.pone.0251998.].

3D cell subculturing pillar dish for pharmacogenetic analysis and high-throughput screening.

A pillar dishe for subculture of 3D cultured cells on hydrogel spots (Matrigel and alginate) have been developed. Cells cultured in 3D in an extracellular matrix (ECM) can retain their intrinsic properties, but cells cultured in 2D lose their intrinsic properties as the cells stick to the bottom of the well. Previously, cells and ECM spots were dispensed on a conventional culture dish for 3D cultivation. However, as the spot shape and location depended on user handling, pillars were added to the dish to realize uniform spot shape and stable subculture, supporting 3D cell culture-based high-throughput screening (HTS). Matrigel and alginate were used as ECMs during 6-passage subculture. The growth rate of lung cancer cell (A549) was higher on Matrigel than on alginate. Cancer cell was subcultured in three dimensions in the proposed pillar dish and used for drug screening and differential gene expression analysis. Interestingly, stemness markers, which are unique characteristics of lung cancer cells inducing drug resistance, were upregulated in 3D-subcultured cells compared with those in 2D-subcultured cells. Additionally, the PI3K/Akt/mTOR, VEGFR1/2, and Wnt pathways, which are promising therapeutic targets for lung cancer, were activated, showing high drug sensitivity under 3D-HTS using the 3D-subcultured cells.

High-throughput organo-on-pillar (high-TOP) array system for three-dimensional ex vivo drug testing.

The development of organoid culture technologies has triggered industrial interest in ex vivo drug test-guided clinical response prediction for precision cancer therapy. The three-dimensional culture encapsulated with basement membrane (BM) components is extremely important in establishing ex vivo organoids and drug sensitivity tests because the BM components confer essential structures resembling tumor histopathology. Although numerous studies have demonstrated three-dimensional culture-based drug screening methods, establishing a large-scale drug-screening platform with matrix-encapsulated tumor cells is challenging because the arrangement of microspots of a matrix-cell droplet onto each well of a microwell plate is inconsistent and difficult to standardize. In addition, relatively low scales and lack of reproducibility discourage the application of three-dimensional organoid-based drug screening data for precision treatment or drug discovery. To overcome these limitations, we manufactured an automated organospotter-integrated high-throughput organo-on-pillar (high-TOP) drug-screening platform. Our system is compatible with various extracellular matrices, including BM extract, Matrigel, collagen, and hydrogel. In addition, it can be readily utilized for high-content analyses by simply exchanging the bottom plates without disrupting the domes. Our system demonstrated considerable robustness, consistency, reproducibility, and biological relevancy in three-dimensional drug sensitivity analyses using Matrigel-encapsulated ovarian cancer cell lines. We also demonstrated proof-of-concept cases representing the clinical feasibility of high-TOP-assisted ex vivo drug tests linked to clinical chemo-response in ovarian cancer patients. In conclusion, our platform provides an automated and standardized method for ex vivo drug-sensitivity-guided clinical response prediction, suggesting effective chemotherapy regimens for patients with cancer.

Cryobiopsy: A Breakthrough Strategy for Clinical Utilization of Lung Cancer Organoids.

One major challenge associated with lung cancer organoids (LCOs) is their predominant derivation from surgical specimens of patients with early-stage lung cancer. However, patients with advanced lung cancer, who are in need of chemotherapy, often cannot undergo surgery. Therefore, there is an urgent need to successfully generate LCOs from biopsy specimens. Conventional lung biopsy techniques, such as transthoracic needle biopsy and forceps biopsy, only yield small amounts of lung tissue, resulting in a low success rate for culturing LCOs from biopsy samples. Furthermore, potential complications, like bleeding and pneumothorax, make it difficult to obtain sufficient tissue. Another critical issue is the overgrowth of normal lung cells in later passages of LCO culture, and the optimal culture conditions for LCOs are yet to be determined. To address these limitations, we attempted to create LCOs from cryobiopsy specimens obtained from patients with lung cancer (n = 113). Overall, the initial success rate of establishing LCOs from cryobiopsy samples was 40.7% (n = 46). Transbronchial cryobiopsy enables the retrieval of significantly larger amounts of lung tissue than bronchoscopic forceps biopsy. Additionally, cryobiopsy can be employed for peripheral lesions, and it is aided via radial endobronchial ultrasonography. This study significantly improved the success rate of LCO culture and demonstrated that the LCOs retained characteristics that resembled the primary tumors. Single-cell RNA sequencing confirmed high cancer cell purity in early passages of LCOs derived from patients with advanced lung cancer. Furthermore, the three-dimensional structure and intracellular components of LCOs were characterized using three-dimensional holotomography. Finally, drug screening was performed using a specialized micropillar culture system with cryobiopsy-derived LCOs. LCOs derived from cryobiopsy specimens offer a promising solution to the critical limitations of conventional LCOs. Cryobiopsy can be applied to patients with lung cancer at all stages, including those with peripheral lesions, and can provide sufficient cells for LCO generation. Therefore, we anticipate that cryobiopsy will serve as a breakthrough strategy for the clinical application of LCOs in all stages of lung cancer.

Cancer organoid-based diagnosis reactivity prediction (CODRP) index-based anticancer drug sensitivity test in ALK-rearrangement positive non-small cell lung cancer (NSCLC).

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.

Personalized functional profiling using ex-vivo patient-derived spheroids points out the potential of an antiangiogenic treatment in a patient with a metastatic lung atypical carcinoid.

Lung carcinoids are neuroendocrine tumors representing 1 to 2% of lung cancers. This study outlines the case of a patient with a metastatic lung atypical carcinoid who presented with a pleural effusion and progression of liver metastases after developing resistance to conventional treatments. Personalized functional profiling (PFP), i.e. drug screening, was performed in ex-vivo spheroids obtained from the patient's liver metastasis to identify potential therapeutic options. The drug screening results revealed cediranib, an antiangiogenic drug, as a hit drug for this patient, from a library of 66 Food and Drug Administration (FDA)-approved and investigational drugs. Based on the PFP results and the reported evidence of clinical efficacy of bevacizumab and capecitabine combination in gastro-intestinal neuroendocrine tumors, this combination was given to the patient. Four months later, the pleural effusion and pleura carcinosis regressed and the liver metastasis did not progress. The patient experienced 2 years of a stable disease under the PFP-guided personalized treatment.