Multiplex Digital PCR Assay to Detect Multiple KRAS and GNAS Mutations Associated with Pancreatic Carcinogenesis from Minimal Specimen Amounts

GNAS复合轨迹 克拉斯 数字聚合酶链反应 放大器 多路复用 胰腺癌 癌变 分子生物学 生物 突变 底漆(化妆品) 遗传学 癌症研究 病理 癌症 聚合酶链反应 医学 基因 化学 有机化学
作者
Chiho Maeda,Yoshio Ono,Akira Hayashi,Kenji Takahashi,Kenzui Taniue,Rika Kakisaka,Masayuki Mori,Takahiro Ishii,Hiroki Sato,Tetsuhiro Okada,Hidemasa Kawabata,Takuma Goto,Nobue Tamamura,Yuko Omori,Kuniyuki Takahashi,Akio Katanuma,Hidenori Karasaki,Andrew S. Liss,Yusuke Mizukami
出处
期刊:The Journal of Molecular Diagnostics [Elsevier BV]
卷期号:25 (6): 367-377 被引量:3
标识
DOI:10.1016/j.jmoldx.2023.02.007
摘要

Digital PCR (dPCR) allows for highly sensitive quantification of low-frequency mutations and facilitates early detection of cancer. However, low-throughput targeting of single hotspots in dPCR hinders variant specification when multiple probes are used. We developed a dPCR method to simultaneously identify major variants related to pancreatic carcinogenesis. Using a two-dimensional plot of droplet fluorescence under the optimized concentration of two fluorescent probe pools, the absolute quantification of different KRAS and GNAS variants was determined. Successful detection of the multiple driver mutations was verified in 24 surgically resected tumor samples from 19 patients and 22 fine-needle aspiration samples from patients with pancreatic ductal adenocarcinoma. Precise quantification of the variant allele frequency was optimized by using template DNA at a concentration as low as 1 to 10 ng. Furthermore, amplicons targeting multiple hotspots were successfully enriched with fewer false-positive findings using high-fidelity polymerase, allowing for the detection of various KRAS and GNAS mutations with high probability in small amount of cell/tissue specimens. Using this target enrichment, mutations at a rate of 90% in small residual tissues, such as the fine-needle aspiration needle flush and microscopic lesions in resected specimens, were successfully identified. The proposed method allows for low-cost, accurate detection of driver mutations to diagnose cancers, even with minimal tissue collection.

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
诸葛半雪发布了新的文献求助10
1秒前
orixero应助Tom采纳,获得30
1秒前
1秒前
1秒前
2秒前
molihuakai应助科研通管家采纳,获得30
2秒前
星辰大海应助科研通管家采纳,获得10
2秒前
脑洞疼应助科研通管家采纳,获得10
2秒前
Jasper应助科研通管家采纳,获得10
2秒前
研友_VZG7GZ应助科研通管家采纳,获得10
2秒前
共享精神应助科研通管家采纳,获得10
2秒前
英姑应助科研通管家采纳,获得50
2秒前
NexusExplorer应助科研通管家采纳,获得10
2秒前
酷波er应助科研通管家采纳,获得10
2秒前
英姑应助科研通管家采纳,获得10
2秒前
wansida完成签到,获得积分10
3秒前
3秒前
3秒前
3秒前
含蓄不言完成签到,获得积分10
4秒前
瞿寒发布了新的文献求助10
5秒前
rabbit发布了新的文献求助10
5秒前
5秒前
6秒前
6秒前
8秒前
9秒前
NexusExplorer应助XY采纳,获得10
9秒前
li18382589708发布了新的文献求助10
10秒前
陆南七发布了新的文献求助30
10秒前
猫头小鹰发布了新的文献求助10
11秒前
淳于安筠发布了新的文献求助10
11秒前
ying应助积极的惋清采纳,获得10
12秒前
顾矜应助CC采纳,获得10
13秒前
14秒前
Aries完成签到,获得积分10
15秒前
15秒前
Accept完成签到,获得积分10
15秒前
妍妍完成签到,获得积分10
16秒前
田様应助练习者采纳,获得10
16秒前
高分求助中
Overcoming Stigma and Bias in Obesity Management 1200
Signals, Systems, and Signal Processing 610
Software that combines deep learning,3D reconstruction and CFD to analyze the state of carotid arteries from ultrasound imaging 500
Bounds for Statistical Estimation in Semiparametric Models 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
Ideology and Meaning-Making under the Putin Regime 450
Adhesion Science: Principles & Practice 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6492034
求助须知:如何正确求助?哪些是违规求助? 8289811
关于积分的说明 17689167
捐赠科研通 5583614
什么是DOI,文献DOI怎么找? 2915194
邀请新用户注册赠送积分活动 1892356
关于科研通互助平台的介绍 1750269