Modeling clinical radioiodine uptake by using organoids derived from differentiated thyroid cancer

类有机物 甲状腺癌 甲状腺 医学 内科学 癌症研究 病理 内分泌学 生物 化学 细胞生物学 有机化学
作者
Xinyue Zhang,Jiaye Liu,Yinyun Ni,Ying Yang,Tian Tian,Xiaofeng Zheng,Zhihui Li,Rui Huang
出处
期刊:Endocrinology [The Endocrine Society]
卷期号:166 (1) 被引量:4
标识
DOI:10.1210/endocr/bqae162
摘要

Abstract Radioiodine-refractory differentiated thyroid cancer (RAI-R DTC) accounts for the vast majority of thyroid-related mortality and, until recently, there were limited preclinical models for iodine uptake prediction. In the current study, we aim to establish a primary tumor-derived organoid model of DTC and predict radioiodine (RAI) uptake of tumor residue. The genotypic and phenotypic features between organoid and parental tissue were compared. The RAI uptake assay was used to evaluate the organoid's RAI uptake capacity, and related patients' RAI whole-body scans were used to verify the assay's predictive sensitivity. A total of 20 patient-derived DTC organoids have been established. Whole-exome sequencing and immunofluorescence analysis demonstrated that organoids faithfully recapitulated main features of the original tumor tissue. RAI-avid organoids (n = 11) presented significantly higher RAI uptake than the RAI-refractory (RAI-R) group (n = 9; 384.4 ± 102.7 vs 54.2 ± 13.2 cpm/105 cells, P < .0001). A threshold value in organoids of less than 250 cpm/105 cell was found to have a predictive sensitivity of 95.0% for distinguishing RAI-R from RAI-avid patients when paired to clinical information. Notably, we found that several tyrosine kinase inhibitors moderately re-sensitize iodine uptake by using organoids derived from 3 patients with different genetic mutation backgrounds. In conclusion, patient-derived DTC organoids recapitulated the main characteristics of their parental tissues and preserved ability to uptake radioiodine, showing potential in the development of novel drugs to boost iodine avidity.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
舒适虔完成签到,获得积分10
刚刚
刚刚
小北发布了新的文献求助10
刚刚
1秒前
Master发布了新的文献求助10
1秒前
Danboard完成签到,获得积分10
1秒前
jami-yu发布了新的文献求助10
1秒前
2秒前
2秒前
dslhxwlkm发布了新的文献求助10
2秒前
CodeCraft应助研友_Lpvx3Z采纳,获得10
2秒前
所所应助工头工头采纳,获得50
2秒前
烜66发布了新的文献求助10
3秒前
柠溪发布了新的文献求助10
3秒前
3秒前
眯眯眼的嘉熙完成签到,获得积分10
3秒前
小二郎应助skinnylove采纳,获得10
3秒前
3秒前
Hilda007应助nczpf2010采纳,获得10
3秒前
Y1311完成签到,获得积分10
3秒前
4秒前
4秒前
4秒前
5秒前
乐乐应助小溶氧采纳,获得10
5秒前
舒适虔发布了新的文献求助10
5秒前
5秒前
科研通AI2S应助端庄的亦丝采纳,获得10
5秒前
丹妮发布了新的文献求助10
6秒前
6秒前
上官若男应助zhou采纳,获得30
6秒前
kilion发布了新的文献求助10
6秒前
huzj发布了新的文献求助10
7秒前
科研通AI6.1应助普通椰子采纳,获得10
7秒前
风清扬发布了新的文献求助30
7秒前
8秒前
8秒前
8秒前
8秒前
在水一方应助植保匠人采纳,获得10
8秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Modern Epidemiology, Fourth Edition 5000
Kinesiophobia : a new view of chronic pain behavior 5000
Molecular Biology of Cancer: Mechanisms, Targets, and Therapeutics 3000
Digital Twins of Advanced Materials Processing 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
Signals, Systems, and Signal Processing 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 纳米技术 化学工程 生物化学 物理 计算机科学 内科学 复合材料 催化作用 物理化学 光电子学 电极 冶金 细胞生物学 基因
热门帖子
关注 科研通微信公众号,转发送积分 6016908
求助须知:如何正确求助?哪些是违规求助? 7600204
关于积分的说明 16154242
捐赠科研通 5164682
什么是DOI,文献DOI怎么找? 2764737
邀请新用户注册赠送积分活动 1745819
关于科研通互助平台的介绍 1635022