A 3D cancer-biofilm microfluidic model for disease modelling and drug screening

Yanlin Deng, Song Lin Chua*, Bee Luan Khoo*

*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

We developed an in vitro Platform to investigate how intratumoral bacteria (IB) and extratumoral bacteria (EB) (PIEB) affect tumor progression. Pathogen-cancer cell co-culture models were established to mimic the infecting and colonization states of bacteria in the cancer microenvironment. Based on this microwell-based microfluidic chip, various in situ downstream assays of tumor cell clusters can be applied, and the cancer-protecting effects of extracellular biofilms formed by EB were proved to have protective effects on cancer cells. We further proposed a combinational triple-drug therapy, which could destroy the biofilm structure and kill cancer cells simultaneously to achieve an effective treatment effect.
Original languageEnglish
Title of host publicationMicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences
PublisherChemical and Biological Microsystems Society
Pages79-80
ISBN (Print)978-1-7334190-3-1
Publication statusPublished - Oct 2021
Event25th International Conference on Miniaturized Systems for Chemistry and Life Sciences (µTAS 2021) - Hybrid, Palm Springs, United States
Duration: 10 Oct 202114 Oct 2021
https://microtas2021.org
https://www.cbmsociety.org/conference/proceedings_archive.html
http://www.microtas2021.org

Publication series

NameMicroTAS - International Conference on Miniaturized Systems for Chemistry and Life Sciences

Conference

Conference25th International Conference on Miniaturized Systems for Chemistry and Life Sciences (µTAS 2021)
Abbreviated titleMicroTAS 2021
Country/TerritoryUnited States
CityPalm Springs
Period10/10/2114/10/21
Internet address

Research Keywords

  • biofilms
  • combinational cancer therapy
  • Microfluidics
  • tumor models

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