High-throughput ex vivo drug testing identifies potential drugs and drug combinations for NRAS-positive malignant melanoma

Abstract Insecticide resistance has recently become a serious problem in the agricultural field. Development of insecticides with new mechanisms of action is essential to overcome this limitation. Juvenile hormone (JH) is an insect-specific hormone that plays key roles in maintaining the larval stage of insects. Hence, JH signaling pathway is considered a suitable target in the development of novel insecticides; however, only a few JH signaling inhibitors (JHSIs) have been reported, and no practical JHSIs have been developed. Here, we established a high-throughput screening (HTS) system for exploration of novel JHSIs using a Bombyx mori cell line (BmN_JF&AR cells) and carried out a large-scale screening in this cell line using a chemical library. The four-step HTS yielded 69 compounds as candidate JHSIs. Topical application of JHSI48 to B. mori larvae caused precocious metamorphosis. In ex vivo culture of the epidermis, JHSI48 suppressed the expression of the Krüppel homolog 1 gene, which is directly activated by JH-liganded receptor. Moreover, JHSI48 caused a parallel rightward shift in the JH response curve, suggesting that JHSI48 possesses a competitive antagonist-like activity. Thus, large-scale HTS using chemical libraries may have applications in development of future insecticides targeting the JH signaling pathway.

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Rapid 3D BioPrinting of a human iPSC-derived cardiac micro-tissue for high-throughput drug testing

Organs-on-a-Chip ◽

10.1016/j.ooc.2021.100007 ◽

2021 ◽

Vol 3 ◽

pp. 100007

Author(s):

Kathleen L. Miller ◽

Yi Xiang ◽

Claire Yu ◽

Jacob Pustelnik ◽

Jerry Wu ◽

...

Keyword(s):

High Throughput ◽

Drug Testing ◽

3D Bioprinting ◽

Human Ipsc

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Evaluating Targeted Therapies in Ovarian Cancer Metabolism: Novel Role for PCSK9 and Second Generation mTOR Inhibitors

Cancers ◽

10.3390/cancers13153727 ◽

2021 ◽

Vol 13 (15) ◽

pp. 3727

Author(s):

Dafne Jacome Sanz ◽

Juuli Raivola ◽

Hanna Karvonen ◽

Mariliina Arjama ◽

Harlan Barker ◽

...

Keyword(s):

Ovarian Cancer ◽

Lipid Metabolism ◽

Cell Survival ◽

Drug Testing ◽

Cancer Metabolism ◽

Ex Vivo ◽

Specific Inhibitor ◽

Low Grade ◽

Serous Ovarian Cancer

Background: Dysregulated lipid metabolism is emerging as a hallmark in several malignancies, including ovarian cancer (OC). Specifically, metastatic OC is highly dependent on lipid-rich omentum. We aimed to investigate the therapeutic value of targeting lipid metabolism in OC. For this purpose, we studied the role of PCSK9, a cholesterol-regulating enzyme, in OC cell survival and its downstream signaling. We also investigated the cytotoxic efficacy of a small library of metabolic (n = 11) and mTOR (n = 10) inhibitors using OC cell lines (n = 8) and ex vivo patient-derived cell cultures (PDCs, n = 5) to identify clinically suitable drug vulnerabilities. Targeting PCSK9 expression with siRNA or PCSK9 specific inhibitor (PF-06446846) impaired OC cell survival. In addition, overexpression of PCSK9 induced robust AKT phosphorylation along with increased expression of ERK1/2 and MEK1/2, suggesting a pro-survival role of PCSK9 in OC cells. Moreover, our drug testing revealed marked differences in cytotoxic responses to drugs targeting metabolic pathways of high-grade serous ovarian cancer (HGSOC) and low-grade serous ovarian cancer (LGSOC) PDCs. Our results show that targeting PCSK9 expression could impair OC cell survival, which warrants further investigation to address the dependency of this cancer on lipogenesis and omental metastasis. Moreover, the differences in metabolic gene expression and drug responses of OC PDCs indicate the existence of a metabolic heterogeneity within OC subtypes, which should be further explored for therapeutic improvements.

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Impaired Alignment of Bone Matrix Microstructure Associated with Disorganized Osteoblast Arrangement in Malignant Melanoma Metastasis

Biomolecules ◽

10.3390/biom11020131 ◽

2021 ◽

Vol 11 (2) ◽

pp. 131

Author(s):

Aira Matsugaki ◽

Yumi Kimura ◽

Ryota Watanabe ◽

Fumihito Nakamura ◽

Ryo Takehana ◽

...

Keyword(s):

Malignant Melanoma ◽

Cell Activation ◽

Ex Vivo ◽

Bone Matrix ◽

Melanoma Metastasis ◽

Mineral Density ◽

High Fracture ◽

Matrix Microstructure ◽

Metastasis Model

Malignant melanoma favors spreading to bone, resulting in a weakened bone with a high fracture risk. Here, we revealed the disorganized alignment of apatite crystals in the bone matrix associated with the homing of cancer cells by developing an artificially controlled ex vivo melanoma bone metastasis model. The ex vivo metastasis model reflects the progressive melanoma cell activation in vivo, resulting in decreased bone mineral density and expression of MMP1-positive cells. Moreover, less organized intercellular connections were observed in the neighboring osteoblasts in metastasized bone, indicating the abnormal and randomized organization of bone matrix secreted by disconnected osteoblasts. Our study revealed that the deteriorated microstructure associated with disorganized osteoblast arrangement was a determinant of malignant melanoma-related bone dysfunction.

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Machine learning methodology for high throughput personalized neutron dose reconstruction in mixed neutron + photon exposures

Scientific Reports ◽

10.1038/s41598-021-83575-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Igor Shuryak ◽

Helen C. Turner ◽

Monica Pujol-Canadell ◽

Jay R. Perrier ◽

Guy Garty ◽

...

Keyword(s):

Machine Learning ◽

High Throughput ◽

Mean Squared Error ◽

Ex Vivo ◽

Probability Distributions ◽

Micronucleus Assay ◽

Neutron Dose ◽

Cell Probability ◽

Scanning Imaging ◽

Automated Scanning

AbstractWe implemented machine learning in the radiation biodosimetry field to quantitatively reconstruct neutron doses in mixed neutron + photon exposures, which are expected in improvised nuclear device detonations. Such individualized reconstructions are crucial for triage and treatment because neutrons are more biologically damaging than photons. We used a high-throughput micronucleus assay with automated scanning/imaging on lymphocytes from human blood ex-vivo irradiated with 44 different combinations of 0–4 Gy neutrons and 0–15 Gy photons (542 blood samples), which include reanalysis of past experiments. We developed several metrics that describe micronuclei/cell probability distributions in binucleated cells, and used them as predictors in random forest (RF) and XGboost machine learning analyses to reconstruct the neutron dose in each sample. The probability of “overfitting” was minimized by training both algorithms with repeated cross-validation on a randomly-selected subset of the data, and measuring performance on the rest. RF achieved the best performance. Mean R2 for actual vs. reconstructed neutron doses over 300 random training/testing splits was 0.869 (range 0.761 to 0.919) and root mean squared error was 0.239 (0.195 to 0.351) Gy. These results demonstrate the promising potential of machine learning to reconstruct the neutron dose component in clinically-relevant complex radiation exposure scenarios.

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High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method

Journal of Visualized Experiments ◽

10.3791/57241 ◽

2018 ◽

Cited By ~ 2

Author(s):

Morgan A. Wambaugh ◽

Jessica C. S. Brown

Keyword(s):

High Throughput ◽

Drug Combinations ◽

Synergistic Drug Combinations

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TMOD-29. STANDARDIZED GENERATION OF TUMOR-ORGANOIDS AS NOVEL DRUG SCREENING MODEL IN MENINGIOMA

Neuro-Oncology ◽

10.1093/neuonc/noab196.890 ◽

2021 ◽

Vol 23 (Supplement_6) ◽

pp. vi221-vi222

Author(s):

Gerhard Jungwirth ◽

Tao Yu ◽

Cao Junguo ◽

Catharina Lotsch ◽

Andreas Unterberg ◽

...

Keyword(s):

Drug Screening ◽

Cancer Biology ◽

Drug Testing ◽

Large Scale ◽

Ex Vivo ◽

Cell Types ◽

Cellular Heterogeneity ◽

Drug Responses ◽

Novel Drug ◽

Tumor Organoids

Abstract Tumor-organoids (TOs) are novel, complex three-dimensional ex vivo tissue cultures that under optimal conditions accurately reflect genotype and phenotype of the original tissue with preserved cellular heterogeneity and morphology. They may serve as a new and exciting model for studying cancer biology and directing personalized therapies. The aim of our study was to establish TOs from meningioma (MGM) and to test their usability for large-scale drug screenings. We were capable of forming several hundred TO equal in size by controlled reaggregation of freshly prepared single cell suspension of MGM tissue samples. In total, standardized TOs from 60 patients were formed, including eight grade II and three grade III MGMs. TOs reaggregated within 3 days resulting in a reducted diameter by 50%. Thereafter, TO size remained stable throughout a 14 days observation period. TOs consisted of largely viable cells, whereas dead cells were predominantly found outside of the organoid. H&E stainings confirmed the successful establishment of dense tissue-like structures. Next, we assessed the suitability and reliability of TOs for a robust large-scale drug testing by employing nine highly potent compounds, derived from a drug screening performed on several MGM cell lines. First, we tested if drug responses depend on TO size. Interestingly, drug responses to these drugs remained identical independent of their sizes. Based on a sufficient representation of low abundance cell types such as T-cells and macrophages an overall number of 25.000 cells/TO was selected for further experiments revealing FDA-approved HDAC inhibitors as highly effective drugs in most of the TOs with a mean z-AUC score of -1.33. Taken together, we developed a protocol to generate standardized TO from MGM containing low abundant cell types of the tumor microenvironment in a representative manner. Robust and reliable drug responses suggest patient-derived TOs as a novel drug testing model in meningioma research.

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High-Throughput 3D Tumor Spheroid Array Platform for Evaluating Sensitivity of Proton-Drug Combinations

International Journal of Molecular Sciences ◽

10.3390/ijms23020587 ◽

2022 ◽

Vol 23 (2) ◽

pp. 587

Author(s):

Dong Woo Lee ◽

Jung Eun Kim ◽

Ga-Haeng Lee ◽

Arang Son ◽

Hee Chul Park ◽

...

Keyword(s):

Cell Lines ◽

High Throughput ◽

High Throughput Screening ◽

Quantitative Data ◽

Survival Rates ◽

Drug Combinations ◽

Targeted Drugs ◽

Tumor Spheroid ◽

Array Platform ◽

Hnscc Cell

Proton beam therapy (PBT) is a critical treatment modality for head and neck squamous cell carcinoma (HNSCC). However, not much is known about drug combinations that may improve the efficacy of PBT. This study aimed to test the feasibility of a three-dimensional (3D) tumor-spheroid-based high-throughput screening platform that could assess cellular sensitivity against PBT. Spheroids of two HNSCC cell lines—Fadu and Cal27—cultured with a mixture of Matrigel were arrayed on a 384-pillar/well plate, followed by exposure to graded doses of protons or targeted drugs including olaparib at various concentrations. Calcein staining of HNSCC spheroids revealed a dose-dependent decrease in cell viability for proton irradiation or multiple targeted drugs, and provided quantitative data that discriminated the sensitivity between the two HNSCC cell lines. The combined effect of protons and olaparib was assessed by calculating the combination index from the survival rates of 4 × 4 matrices, showing that Cal27 spheroids had greater synergy with olaparib than Fadu spheroids. In contrast, adavosertib did not synergize with protons in both spheroids. Taken together, we demonstrated that the 3D pillar/well array platform was a useful tool that provided rapid, quantitative data for evaluating sensitivity to PBT and drug combinations. Our results further supported that administration of the combination of PBT and olaparib may be an effective treatment strategy for HNSCC patients.

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