Seminar

3D Multicellular Cancer Microenvironment Platform for High-throughput Personalized Drug Screening - Acute Myeloid Leukemia (AML) and Neuroblastoma (NB) as examples

Speaker

Miss CHEUNG Hoi Lam

Mphil candidate in the Mechanical Engineering Dept.

Date & Time

Wednesday, 5 May 2021

6:30 am

Venue

Room 7-35 and via Zoom

Abstract:

Cancer is the second primary cause of death worldwide. The poor therapeutic outcomes are mainly caused by the generic approaches in choosing treatment modalities. Due to tumor heterogeneity and the difficulty in optimal drug selection, there is an emerging shift towards personalized cancer treatment. Anti-cancer drugs can be rapidly screened using 3D tumoroids made up of patient’s cancer cells to provide timely results for clinicians to make decisions on patient-specific treatment regimen. However, traditional drug screening platforms based on monolayer cultures of cancer cells are non-physiological owing to the lack of the tumor microenvironment, which was found to cause resistance in therapy. Our laboratory has been developing a 3D microencapsulation platform using naturally occurring extracellular matrix to fabricate physiologically relevant and extracellular matrix-based 3D microtissues including those derived from stem cells, normal somatic cells and cancer cells. In this transfer seminar, I will update the progress in using the microencapsulation platform to reconstitute tumor matrix microenvironment, using acute myeloid leukemia and neuroblastoma as examples. Specifically, miniaturized multi-cellular cancer models which are composed of primary cancer cells, stromal cells, extracellular matrix components, and/or endothelium have been fabricated and characterized. Moreover, I will discuss my plan for the PhD study in further optimizing these models and using them for high-throughput screening of cytotoxic or anti-metastatic drugs, with the ultimate goal to implement personalized medicine in the future.

Research Areas:

Contact for

Information

Prof. B. Chan

+(852) 3917 2632

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