PlumX Metrics
Embed PlumX Metrics

A simple high-throughput approach identifies actionable drug sensitivities in patient-derived tumor organoids

Communications Biology, ISSN: 2399-3642, Vol: 2, Issue: 1, Page: 78
2019
  • 185
    Citations
  • 0
    Usage
  • 335
    Captures
  • 5
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

Most Recent News

Article High-Throughput Technologies: Exploring Advances and Key Applications This article will explore how high-throughput technologies are continuing to advance research in the life sciences. It will also and highlight various areas directly benefiting,

Technological advances have been pivotal in expanding scientific research and contributing to an exponential increase in data output. A primary factor contributing to the rise

Article Description

Tumor organoids maintain cell–cell interactions, heterogeneity, microenvironment, and drug response of the sample they originate from. Thus, there is increasing interest in developing tumor organoid models for drug development and personalized medicine applications. Although organoids are in principle amenable to high-throughput screenings, progress has been hampered by technical constraints and extensive manipulations required by current methods. Here we introduce a miniaturized method that uses a simplified geometry by seeding cells around the rim of the wells (mini-rings). This allows high-throughput screenings in a format compatible with automation as shown using four patient-derived tumor organoids established from two ovarian and one peritoneal high-grade serous carcinomas and one carcinosarcoma of the ovary. Using our automated screening platform, we identified personalized responses by measuring viability, number, and size of organoids after exposure to 240 kinase inhibitors. Results are available within a week from surgery, a timeline compatible with therapeutic decision-making.

Bibliographic Details

Phan, Nhan; Hong, Jenny J; Tofig, Bobby; Mapua, Matthew; Elashoff, David; Moatamed, Neda A; Huang, Jin; Memarzadeh, Sanaz; Damoiseaux, Robert; Soragni, Alice

Springer Science and Business Media LLC

Medicine; Biochemistry, Genetics and Molecular Biology; Agricultural and Biological Sciences

Provide Feedback

Have ideas for a new metric? Would you like to see something else here?Let us know