2025. 08.27 (수) ~ 2025. 08.29 (금)
부산항국제전시컨벤션센터(BPEX)
| 한국질량분석학회 여름학술대회 및 총회 Brief Oral Presentaionof Selected Posters | |
제목 | Comparative Profiling of N-Glycans in Brain Organoids and Human Brain Tissue Using NanoLC-MS |
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작성자 | 정수민 (충남대학교 분석과학기술대학원) |
발표구분 | 포스터발표 |
발표분야 | 4. Medical / Pharmaceutical Science |
발표자 |
정수민 (분석과학기술대학원) |
주저자 | 정수민 (분석과학기술대학원) |
교신저자 |
안현주 (분석과학기술대학원) |
저자 |
정수민 (분석과학기술대학원) 김솔 (분석과학기술대학원) 오명진 (분석과학기술대학원) 안현주 (분석과학기술대학원) |
Organoids are 3D cellular models that replicate the structural and functional features of human tissues and are increasingly recognized as next-generation preclinical alternatives to animal testing. Reliable application of organoids in drug efficacy and toxicity evaluation requires assessing their molecular similarity to native human tissues. However, systematic analytical platforms remain limited. N-glycans on the cell surface are sensitive indicators of physiological states, with expression patterns that vary in response to biological conditions. These properties make N-glycans a promising marker for evaluating the biological similarity and maturity of organoids. In this study, we performed N-glycan profiling of brain organoids and compared their glycan patterns with those of human brain tissues using nanoLC-MS. Additionally, brain organoids cultured for 30, 50, 78, and 123 days were analyzed to investigate glycan pattern changes associated with the maturation process over time. Comparative analysis revealed that while major N-glycans were largely similar between brain organoids and human brain tissues, the tissues exhibited greater structural diversity, specifically in branching and fucosylation. Moreover, prolonged culture led to a progressive increase in immunogenic glycan structures such as Neu5Gc and α-Gal. This study suggests the potential of using N-glycans as indicators to assess the tissue similarity of brain organoids, offering insight into developing glycomics-based platforms for organoid quality assessment. In parallel, our ongoing efforts are focused on optimizing sample preparation workflows to enable reliable analysis from small-quantity organoid samples. |