The advancement of personalized treatments in oncology has garnered increasing attention, particularly for rare and aggressive cancer with low survival rates like the bone tumors osteosarcoma and chondrosarcoma. This study introduces a novel PDMS-agarose microfluidic device tailored for generating patient-derived tumor spheroids and serving as a reliable tool for personalized drug screening. Using this platform in tandem with a custom imaging index, we evaluated the impact of the anticancer agent doxorubicin on spheroids from both tumor types. The device produces 20 spheroids, each around 300 µm in diameter, within a 24 h timeframe, facilitating assessments of characteristics and reproducibility. Following spheroid generation, we measured patient-derived spheroid diameters in bright-field images, calcein AM-positive areas/volume, and the binary fraction area, a metric analyzing fluorescence intensity. By employing a specially developed equation that combines viability signal extension and intensity, we observed a substantial decrease in spheroid viability of around 75% for both sarcomas at the highest dosage (10 µM). Osteosarcoma spheroids exhibited greater sensitivity to doxorubicin than chondrosarcoma spheroids within 48 h. This approach provides a reliable in vitro model for aggressive sarcomas, representing a personalized approach for drug screening that could lead to more effective cancer treatments tailored to individual patients, despite some implementation challenges.
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http://dx.doi.org/10.3390/mi15121521 | DOI Listing |
Brief Bioinform
November 2024
Department of Automation, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District, Shanghai 200240, China.
Studying the changes in cellular transcriptional profiles induced by small molecules can significantly advance our understanding of cellular state alterations and response mechanisms under chemical perturbations, which plays a crucial role in drug discovery and screening processes. Considering that experimental measurements need substantial time and cost, we developed a deep learning-based method called Molecule-induced Transcriptional Change Predictor (MiTCP) to predict changes in transcriptional profiles (CTPs) of 978 landmark genes induced by molecules. MiTCP utilizes graph neural network-based approaches to simultaneously model molecular structure representation and gene co-expression relationships, and integrates them for CTP prediction.
View Article and Find Full Text PDFHepatology
January 2025
Genome Medical Science Project, National Center for Global Health and Medicine, Ichikawa, Japan.
Background Aims: Hepatitis B virus (HBV) leads to severe liver diseases, such as cirrhosis and hepatocellular carcinoma. Identification of host factors that regulate HBV replication can provide new therapeutic targets. The discovery of sodium taurocholate cotransporting polypeptide (NTCP) as an HBV entry receptor has enabled the establishment of hepatic cell lines for analyzing HBV infection and propagation.
View Article and Find Full Text PDFAnn Surg Oncol
January 2025
Department of Surgery, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
Background: Three dimensional (3D) cell cultures can be effectively used for drug discovery and development but there are still challenges in their general application to high-throughput screening. In this study, we developed a novel high-throughput chemotherapeutic 3D drug screening system for gastric cancer, named 'Cure-GA', to discover clinically applicable anticancer drugs and predict therapeutic responses.
Methods: Primary cancer cells were isolated from 143 fresh surgical specimens by enzymatic treatment.
Mol Divers
January 2025
School of Applied Material Sciences, Central University of Gujarat, Gandhinagar, Gujarat, India.
Cancer, a leading global cause of death, presents considerable treatment challenges due to resistance to conventional therapies like chemotherapy and radiotherapy. Cyclin-dependent kinase 11 (CDK11), which plays a pivotal role in cell cycle regulation and transcription, is overexpressed in various cancers and is linked to poor prognosis. This study focused on identifying potential inhibitors of CDK11 using computational drug discovery methods.
View Article and Find Full Text PDFDiabetologia
January 2025
Department of Chemical and Biological Engineering, Colorado School of Mines, Golden, CO, USA.
Type 1 diabetes is an autoimmune disease characterised by the destruction of pancreatic beta cells, resulting in lifelong insulin dependence. Although exogenous insulin can maintain glycaemic control, this approach does not protect residual or replacement pancreatic beta cells from immune-mediated death. Current therapeutics designed to protect functional beta cell mass or promote beta cell proliferation and regeneration can have off-target effects, resulting in higher dose requirements and adverse side effects.
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