Comparison of matched formalin‐fixed paraffin embedded and fresh frozen meningioma tissue reveals bias in proteomic profiles

赖氨酸 分子生物学 蛋白质组 生物 化学 生物化学 氨基酸
作者
Hanan Schoffman,Yishai Levin,Ayelet Itzhaki‐Alfia,Lea Tselekovits,Lior Gonen,Gilad W. Vainer,Goni Hout‐Siloni,Iris Barshack,Zvi R. Cohen,Nevo Margalit,Tal Shahar
出处
期刊:Proteomics [Wiley]
卷期号:22 (21): e2200085-e2200085 被引量:9
标识
DOI:10.1002/pmic.202200085
摘要

Abstract Tissue biopsies are most commonly archived in a paraffin block following tissue fixation with formaldehyde (FFPE) or as fresh frozen tissue (FFT). While both methods preserve biological samples, little is known about how they affect the quantifiable proteome. We performed a ‘bottom‐up’ proteomic analysis ( N = 20) of short and long‐term archived FFPE surgical samples of human meningiomas and compared them to matched FFT specimens. FFT facilitated a similar number of proteins assigned by MetaMorpheus compared with matched FFPE specimens (5378 vs. 5338 proteins, respectively ( p = 0.053), regardless of archival time. However, marked differences in the proteome composition were apparent between FFPE and FFT specimens. Twenty‐three percent of FFPE‐derived peptides and 8% of FFT‐derived peptides contained at least one chemical modification. Methylation and formylation were most prominent in FFPE‐derived peptides (36% and 17% of modified FFPE peptides, respectively) while, most of phosphorylation and iron modifications appeared in FFT‐derived peptides ( p < 0.001). A mean 14% (± 2.9) of peptides identified in FFPE contained at least one modified Lysine residue. Importantly, larger proteins were significantly overrepresented in FFT specimens, while FFPE specimens were enriched with smaller proteins.
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
1秒前
乐乐应助彩色的鸡翅采纳,获得10
1秒前
Serena完成签到,获得积分20
1秒前
3秒前
6秒前
尼尼完成签到,获得积分10
6秒前
xyy102发布了新的文献求助10
6秒前
英俊的铭应助欢呼的白玉采纳,获得10
8秒前
平常盼易完成签到,获得积分10
8秒前
我小怂怂006完成签到 ,获得积分10
10秒前
10秒前
完美世界应助阳炎采纳,获得10
10秒前
10秒前
FashionBoy应助momolalala采纳,获得10
10秒前
羡羡发布了新的文献求助10
11秒前
fmy完成签到,获得积分10
12秒前
熹微发布了新的文献求助10
12秒前
coini发布了新的文献求助10
13秒前
于啊完成签到,获得积分10
14秒前
HH发布了新的文献求助10
15秒前
蓝天发布了新的文献求助10
15秒前
Caius完成签到 ,获得积分10
16秒前
18秒前
milv5完成签到,获得积分10
19秒前
20秒前
李爱国应助熹微采纳,获得10
21秒前
Yzy发布了新的文献求助10
21秒前
FashionBoy应助欢呼的白玉采纳,获得10
22秒前
coini完成签到,获得积分10
23秒前
阳炎发布了新的文献求助10
23秒前
尊敬凝荷完成签到,获得积分10
23秒前
隐形曼青应助HH采纳,获得10
23秒前
djxdjt发布了新的文献求助10
23秒前
乐观秋荷应助科研通管家采纳,获得10
24秒前
24秒前
orixero应助科研通管家采纳,获得10
24秒前
乐观秋荷应助科研通管家采纳,获得10
24秒前
乐观秋荷应助科研通管家采纳,获得10
24秒前
赘婿应助科研通管家采纳,获得10
24秒前
深情安青应助科研通管家采纳,获得10
24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
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Photodetectors: From Ultraviolet to Infrared 500
Cancer Targets: Novel Therapies and Emerging Research Directions (Part 1) 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 6359533
求助须知:如何正确求助?哪些是违规求助? 8173538
关于积分的说明 17214642
捐赠科研通 5414565
什么是DOI,文献DOI怎么找? 2865530
邀请新用户注册赠送积分活动 1842866
关于科研通互助平台的介绍 1691062