Identification of hypoxia biomarkers in insulin-secreting microtissues for diabetes therapy

• Main Author: Cheng, Trina Shinn Yinn
• Other Authors: Dang Thuy Tram
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Engineering; Bioengineering
• Online Access: https://hdl.handle.net/10356/178221
• Institution: Nanyang Technological University

The global prevalence of people suffering from Type 1 Diabetes Mellitus (T1DM) have been on a continuous rise, posing as a significant concern given its incurable nature and association with life-threatening complications. Despite islet transplantation being able to help restore glucose homeostasis, its effectiveness is hindered by obstacles, such as limited islet availability and the requirement for long-term immunosuppressive drugs. Immunoisolation presents as a promising approach to overcome the need for immunosuppression by introducing a shielding barrier. However, this barrier limits oxygen access to the cells, thereby causing a loss in beta cell viability. It has been found that toroid-shaped microtissues have improved cellular viability as compared to spheroid-shaped microtissues. It is hypothesised that this enhanced viability is due to improved oxygen accessibility facilitated by the toroidal geometry, potentially reducing hypoxia-induced apoptosis. Hence, this study aims to identify suitable hypoxia-related biomarkers namely BAX, BCL-2, CHOP and HIF-1ɑ for the quantification of hypoxia at the genetic level. Quantitative reverse transcription polymerase chain reaction (RT-qPCR) was used as a method to quantify the gene expression of these biomarkers. BAX and BCL-2 showed potential to be effective hypoxia biomarkers. HIF-1ɑ mRNA quantification suggests a lack of correspondence between the gene and protein expression of HIF-1ɑ. The mRNA quantification of CHOP showed significant attenuation under hypoxia, which does not align with expected outcome. Additional timepoints and expanding sample size can be explored to obtain a more accurate understanding of the dynamics of the gene expression of hypoxia-related biomarkers in response to hypoxia.