參展商

<span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">The plasma of individuals contains cell-free DNA (cfDNA) fragments released by various tissues in the body. These cfDNA fragments possess molecular characteristics, such as DNA methylation status, that reflect their cellular origins. The fragmentation of plasma DNA is influenced by factors such as nucleosomal organization, chromatin structure, gene expression, and nuclease content in the tissue of origin. As a result, characteristic signatures in the form of fragment size, nucleotide motifs at the fragment ends, single-stranded jagged ends, and the genomic locations of the fragmentation endpoints are observed.&nbsp; <span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Professor Lo's research team discovered that these cfDNA fragment patterns contain rich genetic and epigenetic information and are not randomly fragmented. Expanding on this finding, Professor Lo's team published a paper titled "Epigenetic analysis of cell-free DNA by fragmentomic profiling" in PNAS in 2022. This research overcame the limitations of bisulfite sequencing and demonstrated the potential to infer cfDNA methylation patterns from cfDNA fragment patterns. By analyzing the cleavage profiles of cfDNA around cytosine-phosphate-guanine (CpG) sites and utilizing deep learning algorithms, the team successfully determined the methylation status from specific regions to individual CpGs. This confirmed that genetic and epigenetic information in cfDNA can be obtained through a single non-invasive testing method. The team elucidated the feasibility of using cfDNA cleavage patterns to deduce CpG methylation at single CpG resolution using a deep learning algorithm and achieved an AUC of 0.93 This fragmentomic-based methylation analysis (FRAGMA) opens up new possibilities for non-invasive prenatal screening, cancer detection, and organ transplant evaluation. Professor Lo's research in this area has deepened our understanding of the biology and generation of cell-free DNA, shedding light on the roles of nucleases in plasma DNA biology. This comprehensive approach to analyzing cell-free DNA fragments has the potential to impact clinical practice by enabling targeted DNA methylation, fragmentomic, and topologic analyses on a genome-wide scale. This advancement holds promise for improving early cancer detection and guiding personalized treatment approaches.

展會概覽

參展商名單

產品目錄

展覽廳切面圖

成功故事

展會場刊

重要公佈

展會資訊

申請展位

參展費用及形式

展會資料下載

廣告服務

中小企業市場推廣基金

資訊中心

參展資訊

買家網上登記

電子通訊

香港貿發局商貿平台APP及e-Badge

訪客規則及法規

請小心處理由第三者提供之推廣優惠

參觀資訊

新聞稿

照片廊

展覽視頻

社交媒體/網絡動態

合作媒體

新聞中心

傳媒資訊

活動

香港的旅遊簽證和入境規例

辦理中國內地入境簽證及安排行程

特惠酒店

特惠機票

香港跨境現金管制措施

前往會場

暢遊香港

惡劣天氣的安排

訪港資訊

大會商務中心

中小企支援服務

大會服務

優惠券

綠色小貼士

實用貼士

查詢

常見問題

貿發局活動

網上預先登記

額外設施及服務申請表格

參展商手冊

初次參展須知

主頁

通告

國泰航空機票優惠

與會人士快速過關安排

聯繫我們

穿梭巴士

衞生措施及健康資訊

社交媒體/網絡動態 - 2021

社交媒體/網絡動態 - 2019

社交媒體/網絡動態 - 2018

社交媒體/網絡動態- 2017

社交媒體/網絡動態 - 2016

Virtual Booths

Press Release

Agenda

研討會及論壇

保健護理世界

保健護理世界 - 一般資料

保健護理世界 - 聯繫我們

保健護理世界 - 概覽

保健護理世界 - 展品類別介紹

社交媒體/網絡動態 - 2022

重要通告 (一)