Single-cell-level screening method for migratory cancer cells and its potential feasibility in high-throughput manner
Source abstract
Abstract
Abstract High-throughput screening (HTS) is a well-established approach for tumor-specific drug development because of its high efficiency and customizable selection of antineoplastic drugs. However, there is still a lack of an appropriate cell-based HTS specific for migratory cancer cells. In the study presented here, we created a novel assay (mHTS): a single-cell-level screening method targeting migratory cancer cells and can be applied in a high-throughput manner. This mHTS platform is based on microchannel devices (providing physical confinement during cell migration and limit migrating cells’ proliferation rate) assembled 96-well plate (fitting to HTS manner). To determine the feasibility of this assay, we quantified the anti-migratory and anti-viability effects of several molecules (Cytochalasin D, Doxorubicin and AZD-6244) on migrating (creeping inside microchannel) glioblastoma multiforme (GBM) cells. After analyzing migration screening data that was collected on a single-cell-level, we were able to compare those drug’s effects on cancer cells’ migration velocity and uncovered the migration inhibiting potential of AZD (500 nM and 1000 nM). Viability data based on single-cell-level screening also allowed us to further understand the same drug’s different lethality toward migrating and normal 2D cultured cancer cells. The Pre-classification of subpopulations enables us to study the heterogeneity of cancer and ensures our method’s feasibility for a high-throughput manner. All these results proved our mHTS platform is suitable for single-cell-level anti-migration drug screening and has potential feasibility in promoting the development of anti-migratory-cancer-drug in a high-throughput manner.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: 3D Printing in Biomedical Research · Cell Image Analysis Techniques · Microfluidic and Bio-sensing Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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