Drug Screening Methods Research Articles

Cell-Based Glioma Models for Anticancer Drug Screening: From Conventional Adherent Cell Cultures to Tumor-Specific Three-Dimensional Constructs

Gliomas are a group of primary brain tumors characterized by their aggressive nature and resistance to treatment. Infiltration of surrounding normal tissues limits surgical approaches, wide inter- and intratumor heterogeneity hinders the development of universal therapeutics, and the presence of the blood–brain barrier reduces the efficiency of their delivery. As a result, patients diagnosed with gliomas often face a poor prognosis and low survival rates. The spectrum of anti-glioma drugs used in clinical practice is quite narrow. Alkylating agents are often used as first-line therapy, but their effectiveness varies depending on the molecular subtypes of gliomas. This highlights the need for new, more effective therapeutic approaches. Standard drug-screening methods involve the use of two-dimensional cell cultures. However, these models cannot fully replicate the conditions present in real tumors, making it difficult to extrapolate the results to humans. We describe the advantages and disadvantages of existing glioma cell-based models designed to improve the situation and build future prospects to make drug discovery comprehensive and more effective for each patient according to personalized therapy paradigms.

Evaluation of the Neuroprotective Effect of Total Glycosides of Cistanche deserticola and Investigation of Novel Brain-Targeting Natural MAO-B Inhibitors.

In this study, we investigated the role of total glycosides of Cistanche deserticola (TC) in MPTP-induced neuronal injury. Further, we screened potential inhibitory components of monoamine oxidase B (MAO-B). The study results indicate that TC may improve movement disorders and apoptosis of dopamine (DA) neurons by inhibiting MAO-B activity while reducing the number of glial cells, adjusting the metabolism level of monoamine neurotransmitters, and lowering inflammation and oxidative stress levels. Subsequently, a rapid screening method for drug-containing brain tissue was further constructed, and five candidate components that can cross the blood-brain barrier and bind to MAO-B were screened and submitted for biological activity evaluation and inhibition mechanism research. In summary, we discovered 2'-acetylacteoside as a promising and reversible mixed natural MAO-B inhibitor in TC and developed a rapid screening method for screening central nervous system drugs with blood-brain barrier permeability characteristics, providing potential candidates and an effective screening strategy for neurodegenerative diseases.

Ultrasensitive Chemiluminescence Probes Designed from Covalent Inhibitors for SRAS-CoV-2 Mpro Detection.

In the postpandemic era, the emergence of "long COVID" from SARS-CoV-2 has brought ongoing negative impacts on individual health and society. The development of more efficient methods for drug screening and monitoring viral activity remains a critical need. The main protease (Mpro), due to its important role in the virus lifecycle, high conservation, and specificity, is considered an ideal biomarker for SARS-CoV-2. Herein, we have developed several chemiluminescence probes based on different substrates modified from covalent inhibitors targeted at Mpro. Among these, the best probe, MPCL-2, exhibits a rapid response (<20 min), an extremely low limit of detection (LoD; 0.11 nM), great selectivity, and chemical stability. After validating the probe's mechanism of action, MPCL-2 can also be used for real-time, in-situ imaging of enzymes in cells infected with the authentic virus and has the potential for real-time, in-situ Mpro imaging in vivo. Compared to other methods reported to date, the probe demonstrates superior performance and broader applicability, such as in drug screening or virus activity monitoring. Further, the unique design strategy for the substrate can be adopted to develop sensitive probes for other pathogens.

UHPLC-QTOFMS Urine Drug Screening With Dilute-and-Shoot Sample Preparation and Vacuum-Insulated Probe-Heated Electrospray Ionization.

We developed a method for comprehensive urine drug screening by applying dilute-and-shoot extraction and vacuum-insulated probe-heated electrospray ionization with ultra-high performance liquid chromatography high-resolution quadrupole time-of-flight mass spectrometry (DS-UHPLC-VIP-HESI-QTOFMS). The method involved five-fold post-hydrolysis dilution of urine samples and chromatography on a C18 UHPLC column prior to QTOFMS analysis. The recently introduced VIP-HESI ion source was chosen due to its enhanced ionization efficiency and compatibility with UHPLC-QTOFMS. Extensive data was acquired in positive ion mode with a low collision energy (7 eV) and an elevated collision energy (30 eV), using the broadband collision-induced dissociation data acquisition scan mode that continuously generated high-resolution and accurate mass for parent and fragment qualifier ions, and parent ion isotopic patterns. Compound identification was performed against an in-house database with 1263 compound entries, using an automated post-run reverse target database search with preset identification criteria. Method validation with 56 different drugs showed acceptable results for the limit of identification (median 5 ng/mL), matrix effects (70-130%), repeatability of retention times (< 1%), mass accuracy (< 1 mDa), as well as for specificity and stability. As compared with an established UHPLC-QTOFMS method relying on solid-phase extraction and conventional electrospray ionization, DS-UHPLC-VIP-HESI-QTOFMS produced comparable results from authentic clinical urine samples for most drugs, but showed clearly improved detectability for pregabalin, gabapentin, and ritalinic acid. We anticipate that the new method will be a step forward for laboratories performing routine urine drug screening due to its fast turnaround time, reduced manual workload, cost efficiency, and broad substance coverage.

Modeling Drug Responses and Evolutionary Dynamics using Patient-Derived Xenografts Reveals Precision Medicine Strategies for Triple Negative Breast Cancer.

The inter- and intra-tumor heterogeneity of triple negative breast cancers (TNBC), which is reflected in diverse drug responses, interplays with tumor evolution. Here, we developed a preclinical experimental and analytical framework using treatment-naive TNBC patient-derived tumor xenografts (PDTX) to test their predictive value in personalized cancer treatment approaches. Patients and their matched PDTX exhibited concordant drug responses to neoadjuvant therapy using two trial designs and dosing schedules. This platform enabled analysis of non-genetic mechanisms involved in relapse dynamics. Treatment resulted in permanent phenotypic changes with functional and therapeutic consequences. High throughput drug screening methods in ex vivo patient derived tumor xenograft cells (PDTCs) revealed patient-specific drug response changes dependent on first-line therapy. This was validated in vivo, as exemplified by a change in olaparib sensitivity in tumors previously treated with clinically relevant cycles of standard-of-care chemotherapy. In summary, PDTXs provide a robust tool to test patient drug responses and therapeutic regimens and to model evolutionary trajectories. However, high inter-model variability and permanent non-genomic transcriptional changes constrain their use for personalized cancer therapy. This work highlights important considerations associated with preclinical drug response modeling and potential uses of the platform to identify efficacious and preferential sequential therapeutic regimens.

MIDF-DMAP: Multimodal information dynamic fusion for drug molecule activity prediction

BackgroundComputer-aided drug development can alleviate limitations in drug research and development processes, such as long cycles, high costs, and limited targeting. Deep learning models can be used to predict the activity of drug compound molecules. However, existing models still need to adequately address semantic redundancy, conflicts, and noise between different data modalities. It results in low accuracy in predicting molecular activity and many false positive results that need further resolution. ObjectiveThis study aims to design a parallel deep learning model for processing multimodal molecular information fusion, dynamically adjusting the weights of different modal features during the fusion process. This approach ensures that high-quality modal information is more significant in molecular activity prediction, improving the model’s predictive accuracy. MethodsFirst, three modal features of drug molecules are extracted: one-dimensional fingerprints, two-dimensional topological structures, and three-dimensional geometric structures. Then, a dynamic weighting mechanism is proposed to fuse these three modal features organically. Finally, the fused features are input into the model classifier to obtain molecular activity prediction results. ResultsExperimental results show that the proposed model improved the Receiver Operating Characteristic-Area Under the Curve (ROC-AUC) value by 29.96% compared to the Weave model and 26.38% compared to the GC model on the BBBP dataset. Compared to the GraphMVP model and the multi-channel substructure graph model MSGG, the ROC-AUC value increased by 20.44% and 15.80%, respectively. This method also achieved good results on imbalanced samples and small molecule datasets. ConclusionThis study provides an effective multimodal dynamic fusion method for virtual drug screening, enriching computer-aided drug development theory and improving drug research and development efficiency.

Identification of 5-aminometonitazene and 5-acetamidometonitazene in a postmortem case: are nitro-nitazenes unstable?

In recent years, the use of 2-benzylbenzimidazole opioids ('nitazenes') has increased with them becoming one of the most prominent synthetic opioid subclasses of novel psychoactive substances. With the increased prevalence, there is also a concern of the dangers to public health with the use of nitazenes due to their high potency especially with polypharmacy. To aid in the detection of such compounds, it is important that forensic toxicology laboratories maintain up-to-date compound libraries for drug screening methods and that sensitive analytical instrumentation is available to detect the low blood/plasma concentrations of more potent drugs. This includes not only the compounds themselves but also potential metabolites and/or degradation products. Metonitazene is a 'nitro-nitazene' with a nitro group at position 5 of the benzimidazole ring. As a nitro-nitazene, there is a potential for bacterial degradation of metonitazene to 5-aminometonitazene, as occurs with nitro-benzodiazepines. In this study, we provide evidence from a postmortem (PM) case of degradation of metonitazene in unpreserved PM blood using liquid chromatography-triple quadrupole mass spectrometry (LC-QQQ-MS), and putative identification of the degradation/metabolic products 5-aminometonitazene and 5-acetamidometonitazene by liquid chromatography-quadrupole time-of-flight mass spectrometry. The results from LC-QQQ-MS analysis indicated that there did not appear to be such degradation in preserved (fluoride/oxalate) blood. These results suggest that nitro-nitazenes may be subject to similar in vitro stability/degradation issues as nitro-benzodiazepines. These breakdown products should be added to instrument libraries to aid in the detection of the use of nitro-nitazenes, and nitro-nitazenes should be quantified in preserved blood samples where available.

High-performance liquid chromatography coupled to Orbitrap mass spectrometry for screening of common new psychoactive substances and other drugs in biological samples.

The complexity of the drug market and the constant updating of drugs have been challenging issues for drug regulatory authorities. With the emergence of new psychoactive substances (NPS) and the nonmedical use of prescription drugs, forensic and toxicology laboratories have had to adopt new drug screening methods and advanced instrumentation. Using high-performance liquid chromatography coupled with Orbitrap mass spectrometry, we developed a screening method for common NPS and other drugs. Two milliliters of mixed solvent of n-hexane and ethyl acetate (1:1, v:v) were added to 500 μL of blood or urine sample for liquid-liquid extraction, and methanol extraction was used for hair samples. The developed method was applied to 3897 samples (including 332 blood samples, 885 urine samples, and 2680 hair samples) taken from drug addicts in a province of China during 2019-2021. For urine and blood samples, the limits of detection (LODs) ranged from 1.68 pg/mL to 10.7 ng/mL. For hair samples, the LODs ranged from 3.30 × 10-5 to 4.21 × 10-3 ng/mg. The matrix effects of urine, blood, and hair samples were in the range of 47.6%-121%, 39.8%-139%, and 6.35%-118%, respectively. And the intra-day precision was 3.5%-6.0% and the inter-day precision was 4.18%-9.90%. Analysis of the actual samples showed an overall positive detection rate of 58.9%, with 5.32% of the samples indicating the use of multiple drugs.

Network Medicine: A Potential Approach for Virtual Drug Screening.

Traditional drug screening methods typically focus on a single protein target and exhibit limited efficiency due to the multifactorial nature of most diseases, which result from disturbances within complex networks of protein-protein interactions rather than single gene abnormalities. Addressing this limitation requires a comprehensive drug screening strategy. Network medicine is rooted in systems biology and provides a comprehensive framework for understanding disease mechanisms, prevention, and therapeutic innovations. This approach not only explores the associations between various diseases but also quantifies the relationships between disease genes and drug targets within interactome networks, thus facilitating the prediction of drug-disease relationships and enabling the screening of therapeutic drugs for specific complex diseases. An increasing body of research supports the efficiency and utility of network-based strategies in drug screening. This review highlights the transformative potential of network medicine in virtual therapeutic screening for complex diseases, offering novel insights and a robust foundation for future drug discovery endeavors.

A deep learning drug screening framework for integrating local-global characteristics: A novel attempt for limited data

At the beginning of the "Disease X" outbreak, drug discovery and development are often challenged by insufficient and unbalanced data. To address this problem and maximize the information value of limited data, we propose a drug screening model, LGCNN, based on convolutional neural network (CNN), which enables rapid drug screening by integrating features of drug molecular structures and drug-target interactions at both local and global (LG) levels. Experimental results show that LGCNN exhibits better performance compared to other state-of-the-art classification methods under limited data. In addition, LGCNN was applied to anti-SARS-CoV-2 drug screening to realize therapeutic drug mining against COVID-19. LGCNN transcends the limitations of traditional models for predicting interactions between single drug targets and shows new advantages in predicting multi-target drug-target interactions. Notably, the cross-coronavirus generalizability of the model is also implied by the analysis of targets, drugs, and mechanisms in the prediction results. In conclusion, LGCNN provides new ideas and methods for rapid drug screening in emergency situations where data are scarce.

In vitro throughput screening of anticancer drugs using patient-derived cell lines cultured on vascularized three-dimensional stromal tissues

The development of high-throughput anticancer drug screening methods using patient-derived cancer cell (PDC) lines that maintain their original characteristics in an in vitro three-dimensional (3D) culture system poses a significant challenge to achieving personalized cancer medicine. Because stromal tissue plays a critical role in the composition and maintenance of the cancer microenvironment, in vitro 3D-culture using reconstructed stromal tissues has attracted considerable attention. Here, a simple and unique in vitro 3D-culture method using heparin and collagen together with fibroblasts and endothelial cells to fabricate vascularized 3D-stromal tissues for in vitro culture of PDCs is reported. Whereas co-treatment with bevacizumab, a monoclonal antibody against vascular endothelial growth factor, and 5-fluorouracil significantly reduced the survival rate of 3D-cultured PDCs to 30%, separate addition of each drug did not induce comparable strong cytotoxicity, suggesting the possibility of evaluating the combined effect of anticancer drugs and angiogenesis inhibitors. Surprisingly, drug evaluation using eight PDC lines with the 3D-culture method resulted in a drug efficacy concordance rate of 75% with clinical outcomes. The model is expected to be applicable to in vitro throughput drug screening for the development of personalized cancer medicine. Statement of significanceTo replicate the cancer microenvironment, we constructed a cancer-stromal tissue model in which cancer cells are placed above and inside stromal tissue with vascular network structures derived from vascular endothelial cells in fibroblast tissue using CAViTs method. Using this method, we were able to reproduce the invasion and metastasis processes of cancer cells observed in vivo. Using patient-derived cancer cells, we assessed the possibility of evaluating the combined effect with an angiogenesis inhibitor.Further, primary cancer cells also grew on the stromal tissues with the normal medium. These data suggest that the model may be useful for new in vitro drug screening and personalized cancer medicine.

Therapeutic potential of targeting Nrf2 by panobinostat in pituitary neuroendocrine tumors

We aimed to identify the druggable cell-intrinsic vulnerabilities and target-based drug therapies for PitNETs using the high-throughput drug screening (HTS) and genomic sequencing methods. We examined 9 patient-derived PitNET primary cells in HTS. Based on the screening results, the potential target genes were analyzed with genomic sequencing from a total of 180 PitNETs. We identified and verified one of the most potentially effective drugs, which targeted the Histone deacetylases (HDACs) both in in vitro and in vivo PitNET models. Further RNA sequencing revealed underlying molecular mechanisms following treatment with the representative HDACs inhibitor, Panobinostat. The HTS generated a total of 20,736 single-agent dose responses which were enriched among multiple inhibitors for various oncogenic targets, including HDACs, PI3K, mTOR, and proteasome. Among these drugs, HDAC inhibitors (HDACIs) were, on average, the most potent drug class. Further studies using in vitro, in vivo, and isolated PitNET primary cell models validated HDACIs, especially Panobinostat, as a promising therapeutic agent. Transcriptional surveys revealed substantial alterations to the Nrf2 signaling following Panobinostat treatment. Moreover, Nrf2 is highly expressed in PitNETs. The combination of Panobinostat and Nrf2 inhibitor ML385 had a synergistic effect on PitNET suppression. The current study revealed a class of effective anti-PitNET drugs, HDACIs, based on the HTS and genomic sequencing. One of the representative compounds, Panobinostat, may be a potential drug for PitNET treatment via Nrf2-mediated redox modulation. Combination of Panobinostat and ML385 further enhance the effectiveness for PitNET treatment.

Recent advances in 3D printing for in vitro cancer models

3D printing techniques allow for the precise placement of living cells, biological substances, and biochemical components, establishing themselves as a promising approach in bioengineering. Recently, 3D printing has been applied to develop human-relevant in vitro cancer models with highly controlled complexity and as a potential method for drug screening and disease modeling. Compared to 2D culture, 3D-printed in vitro cancer models more closely replicate the in vivo microenvironment. Additionally, they offer a reduction in the complexity and ethical issues associated with using in vivo animal models. This focused review discusses the relevance of 3D printing technologies and the applied cells and materials used in cutting-edge in vitro cancer models and microfluidic device systems. Future prospective solutions were discussed to establish 3D-printed in vitro models as reliable tools for drug screening and understanding cancer disease mechanisms.

Abstract LB434: Rapid and reproducible expansion of rare tumor cells: The R3CE platform for personalized medicine

Abstract We have developed a novel single-cell derived 3D organoid culture platform, Rapid, Reproducible, Rare Cell 3D Expansion (R3CE), capable of generating 3D organoids from solid tumors and normal tissues obtained via surgical tissues and needle biopsies within one week. This method demonstrates over 90% success in banking for at least two passages with over 106 cells across various cancer types, including breast cancer, colorectal cancer, hepatoma cancer, and ovarian cancer. The organoids maintain high fidelity to original tissues, as evidenced by H&amp;E staining, WES, and protein marker analysis across generations. Notably, the R3CE platform can also cultivate circulating tumor cells (CTCs) from peripheral blood. The drug sensitivity profiles of RCE-cultured CTCs closely mirrored clinical outcomes in breast cancer patients. For a patient with stage IV HER2-positive breast cancer, our real-time assay results led to an adjustment in treatment from lapatinib/5-FU to lapatinib/Trastuzumab emtansine (TDM-1), which resulted in substantial clinical improvement. To our knowledge, the R3CE platform is the first 3D organoid system that does not require aggregation or 3D scaffold such as matrigel system. These advancements position the R3CE platform as a promising tool for personalized medicine, offering a rapid and accurate method for drug screening and therapeutic response prediction to guide clinical decision-making in cancer treatment. Citation Format: Wen-Hung Kuo, Yen-Jang Huang, Jia-Yang Chen, Yi-Chun Wu, Chia-Chun Chen, Mark D. Pegram, Ying-Chih Chang. Rapid and reproducible expansion of rare tumor cells: The R3CE platform for personalized medicine [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB434.

Development of a rapid-fire drug screening method by probe electrospray ionization tandem mass spectrometry for human urine (RaDPi-U).

Drug screening tests are mandatory in the search fordrugs in forensic biological samples, and immunological methods and mass spectrometry (e.g., gas chromatography-mass spectrometry and liquid chromatography-tandem mass spectrometry) are commonly used for that purpose. However, these methods have some drawbacks, and developing new screening methods is required. In this study, we develop a rapid-fire drug screening method by probe electrospray ionization tandem mass spectrometry (PESI-MS/MS), which is an ambient ionization mass spectrometrymethod, for human urine, named RaDPi-U. RaDPi-U is carried out in three steps: (1) mixing urine with internal standard (IS) solution and ethanol, followed by vortexing; (2) pipetting the mixture onto a sample plate for PESI; and (3) rapid-fire analysis by PESI-MS/MS. RaDPi-U targets 40 forensically important drugs, which include illegal drugs, hypnotics, and psychoactive substances. The analytical results were obtained within 3min because of the above-mentioned simple workflow of RaDPi-U. The calibration curves of each analyte were constructed using the IS method, and they were quantitatively valid, resulting in good linearity (0.972-0.999) with a satisfactory lower limit of detection and lower limit of quantitation (0.01-7.1ng/mL and 0.02-21ng/mL, respectively). Further, both trueness and precisions were 28% or less, demonstrating the high reliability and repeatability of the method. Finally, we applied RaDPi-U to three postmortem urine specimens and successfully detected different drugs in each urine sample. The practicality of the method is proven, and RaDPi-U will be a strong tool as a rapid-fire drug screening method not only in forensic toxicology but also in clinical toxicology.

Abstract 4243: Revolutionizing cancer research, new drug screening approach with vascularized cancer organoid platform mimicking patient tumor microenvironment

Abstract Patient-derived organoids (PDOs) are improving our understanding of cancer heterogeneity and personalized medicine. In particular, patients' intrinsic and acquired treatment resistance is being evaluated with PDOs, which has become an essential factor in developing new anticancer drugs and designing successful clinical trials. However, there are obstacles to cancer heterogeneity and patient-specific cancer therapy due to lack of understanding of tumoral diversity resulting from the tumor microenvironment (TME). Complex direct and indirect interactions between various types of TME cells and the resulting tumoral diversity are challenges that must be addressed for customized cancer therapy. Standard cancer therapy targets tumor cells without considering possible damage on the tumor microenvironment that could impair therapy response. Therefore, the construction and analysis of a platform for co-culturing cancer organoids with other cell types that make up the TME over a long period of time is necessary. We generated and performed characterization of blood vessel organoid (BVO). The BVO expressed endothelial marker CD31 and pericyte marker PDGFRβ. We attempted to co-culture with patient-derived lung cancer organoid (LCO) on Matrigel by dissociating the constructed BVO, and it was confirmed that BVO and LCO were interconnected after 10 days. This new platform was treated with Gefitinib and Poziotinib, and after 5 days of drug treatment, the IC50 value increased compared to LCO-only culture. Additionally, flow cytometry analysis confirmed that co-culturing with BVO during drug treatment resulted in a lower percentage of dead LCO cells compared to LCO-only culture. Image-based analysis also verified that co-culturing with blood vessels enhances the viability of LCOs when treated with drugs. Taken together, the co-culture of cancer organoids and BVOs present a platform that closely mimics the in vivo TME compared to the existing cancer organoid culture method. This innovative platform demonstrates higher drug resistance than existing approaches, offering a novel method for drug screening. Citation Format: Mingyun Lee, Yeo-Joon Yoon, Yong-Soo Lee, Jinguen Rheey. Revolutionizing cancer research, new drug screening approach with vascularized cancer organoid platform mimicking patient tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4243.

Abstract 667: Identification of biomarkers of response to MDM2 inhibition in solid tumours using computational, multi-omics approaches

Abstract Background High-throughput drug screening and computational methods to associate genomic features of cell lines to drug sensitivity are valuable tools for predicting biomarkers of sensitivity. In addition, integrating genomic features to expression-based patterns could improve biomarker prediction and patient stratification. Particularly weighted gene co-expression networks represent an effective approach to identify key modules and possible biological mechanisms of sensitivity. Using a combination of cell panel screening and gene co-expression networks, we predicted markers of sensitivity to ASTX295 (MDM2i) in cancer cell lines and confirmed expression-based signatures in publicly available clinical datasets. Method ASTX295 was screened in a panel of 210 p53 wild-type cancer cell lines derived from a range of tumor tissues. ANOVA was used to identify significant associations of genomics features of cell lines to drug response. Transcriptomics profiling of apoptotic and non-apoptotic patient-derived cell lines was performed and significant differentially expressed genes were identified. Further, pathway enrichment and expression-based signatures identified in cell lines were further confirmed in TCGA patient data using weighted gene co-expression network analysis (WGCNA). Expression modules identified by WGCNA were correlated to genomic features and clinical parameters to identify potentially clinically relevant biomarkers. Results Analysis of the cell panel data identified CDKN2A loss as a statistically significant biomarker predictive of sensitivity to ASTX295. As mesothelioma is one of the indications with high prevalence of loss of CDKN2A, the anti-proliferative activity of ASTX295 was further confirmed in an independent panel of p53 wild-type, patient-derived mesothelioma cell lines. Further, pathway and transcriptional regulator analysis identified the Interferon signalling as significantly enriched in apoptotic cell lines and was confirmed in a TCGA mesothelioma patient data set and the module was found to be significantly correlated with a subgroup of P53 wild-type patients with CDKN2A loss. In conclusion, combining cell panel drug screening with co-expression networks helped to identify biomarkers associated with ASTX295 sensitivity, and provided new insights into the underlying mechanism of ASTX295 response. Citation Format: Harpreet Kaur Saini, Maria Ahn, George Ward, Justyna Kucia-Tran, Christina Gewinner, Nicola Ferrari, Jessica Brothwood, Luke Bevan, Matthew Davis, Lynsey Fazal, Martin Sims, Marc O'Reilly, Gianni Chessari, Roberta Ferraldeschi, John Lyons, Nicola Wallis, Neil Thompson. Identification of biomarkers of response to MDM2 inhibition in solid tumours using computational, multi-omics approaches [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 667.

Development of a novel seized drug screening method utilizing DART-MS and used weigh paper

The conventional analytical scheme for seized drug analysis utilizes quick and cost-effective presumptive testing, such as color tests, followed by more discriminatory techniques, such as gas chromatography-mass spectrometry (GC–MS). Before the seized drug evidence is analyzed, the evidence is weighed using an appropriate weighing matrix and balance. Typically, the weighing matrix is discarded as chemical waste; however, the process of weighing the evidence leads to the deposition of drug residue onto the weighing matrix, which is then amenable to rapid analysis using ambient ionization approaches, such as direct analysis in real time mass spectrometry (DART-MS). This study demonstrates a DART-MS method for the rapid screening of seized drug evidence using filter paper and glassine paper weighing matrices commonly found in forensic laboratories. Validation experiments were performed using filter paper and glassine paper and compared to the results obtained using glass capillaries to assess the effectiveness of each weighing matrix. A total of 40 authentic samples, 20 filter papers and 20 glassine papers, were analyzed and the resulting spectra were searched using the National Institute of Standards and Technology (NIST) DART-MS Forensics Database and Data Interpretation Tool (DIT). When compared to the ground truth GC–MS results, the developed approach had a 90% correct identification rate, with all misidentifications being due to the presence of tablets rather than powder. The developed DART-MS screening method provides the seized drug community with a method to rapidly screen seized drug residue remaining from the weighing process and to improve the overall laboratory efficiency.

Digital light processing-based bioprinting of microtissue hydrogel arrays using dextran-induced aqueous emulsion ink

As a microscale three-dimensional bionic model, a microtissue array is a promising method for disease modeling and drug screening. Digital light processing (DLP) 3D bio-printing technology with the capabilities of excellent printing speed and resolution shows great potential for fabricating microtissue arrays. However, the outcomes of the microtissue arrays using DLP are limited by the shortage of biomaterials. In this work, we prepare hydrogel microtissues by combining DLP printing technology with biphasic bio-ink consisting of gelatin methacrylate (GelMA) and dextran. GelMA/ dextran is mixed to form bio-inks with different volume ratios, which can achieve high-precision printing of various patterns. Due to the presence of dextran, the bio-inks form the internal porous structure of the hydrogel in the printed patterns. The pore size is related to the proportion of dextran in bio-inks, and the pore size of hydrogel becomes smaller with the increase of dextran ratio. In addition, the adipose-derived stem cells (ADSCs) cells encapsulated in the porous hydrogels can maintain a high survival rate of 98.01% after 3 days of culture, and the larger pore size in the hydrogels promotes cell migration. Combining the DLP printing system with the porous hydrogel allows multiple micro-size geometric pattern hydrogels to be printed simultaneously to form microtissue arrays. In this study, a new bio-ink suitable for microtissue arrays is proposed, and a simple, accurate, and high-throughput biological manufacturing method for microtissue arrays is developed, thus providing a valuable tool for drug screening and tissue engineering.

Droplet Microfluidics for Current Cancer Research: From Single-Cell Analysis to 3D Cell Culture.

Cancer is the second leading cause of death worldwide. Differences in drug resistance and treatment response caused by the heterogeneity of cancer cells are the primary reasons for poor cancer therapy outcomes in patients. In addition, current in vitro anticancer drug-screening methods rely on two-dimensional monolayer-cultured cancer cells, which cannot accurately predict drug behavior in vivo. Therefore, a powerful tool to study the heterogeneity of cancer cells and produce effective in vitro tumor models is warranted to leverage cancer research. Droplet microfluidics has become a powerful platform for the single-cell analysis of cancer cells and three-dimensional cell culture of in vitro tumor spheroids. In this review, we discuss the use of droplet microfluidics in cancer research. Droplet microfluidic technologies, including single- or double-emulsion droplet generation and passive- or active-droplet manipulation, are concisely discussed. Recent advances in droplet microfluidics for single-cell analysis of cancer cells, circulating tumor cells, and scaffold-free/based 3D cell culture of tumor spheroids have been systematically introduced. Finally, the challenges that must be overcome for the further application of droplet microfluidics in cancer research are discussed.