亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Transcriptome sequencing of archived lymphoma specimens is feasible and clinically relevant using exome capture technology

转录组 外显子组测序 生物 外显子组 基因 计算生物学 RNA序列 管家基因 基因表达谱 弥漫性大B细胞淋巴瘤 基因表达 遗传学 突变 化疗
作者
Aron Skaftason,Ying Qu,Maysaa Abdulla,Jessica Nordlund,Mattias Berglund,Susanne Bram Ednersson,Per‐Ola Andersson,Gunilla Enblad,Rose‐Marie Amini,Richard Rosenquist,Larry Mansouri
出处
期刊:Genes, Chromosomes and Cancer [Wiley]
卷期号:61 (1): 27-36 被引量:5
标识
DOI:10.1002/gcc.23002
摘要

Abstract Formalin‐fixed, paraffin‐embedded (FFPE) specimens are an underutilized resource in medical research, particularly in the setting of transcriptome sequencing, as RNA from these samples is often degraded. We took advantage of an exome capture‐based RNA‐sequencing protocol to explore global gene expression in paired fresh–frozen (FF) and FFPE samples from 16 diffuse large B‐cell lymphoma (DLBCL) patients. While FFPE samples generated fewer mapped reads compared to their FF counterparts, these reads captured the same library complexity and had a similar number of genes expressed on average. Furthermore, gene expression demonstrated a high correlation when comparing housekeeping genes only or across the entire transcriptome ( r = 0.99 for both comparisons). Differences in gene expression were primarily seen in lowly expressed genes and genes with small or large coding sequences. Using cell‐of‐origin classifiers and clinically relevant gene expression signatures for DLBCL, FF, and FFPE samples from the same biopsy paired nearly perfectly in clustering analysis. This was further confirmed in a validation cohort of 50 FFPE DLBCL samples. In summary, we found the biological differences between tumors to be far greater than artifacts created as a result of degraded RNA. We conclude that exome capture transcriptome sequencing data from archival samples can confidently be used for cell‐of‐origin classification of DLBCL samples.
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
科研通AI6.4应助zzz采纳,获得10
1秒前
8秒前
搜集达人应助科研通管家采纳,获得10
8秒前
六六完成签到 ,获得积分10
21秒前
xxx完成签到,获得积分20
23秒前
34秒前
xxx关注了科研通微信公众号
38秒前
xxx关注了科研通微信公众号
38秒前
38秒前
43秒前
43秒前
43秒前
44秒前
44秒前
44秒前
45秒前
45秒前
47秒前
47秒前
48秒前
48秒前
48秒前
48秒前
48秒前
48秒前
49秒前
49秒前
49秒前
49秒前
49秒前
49秒前
50秒前
50秒前
50秒前
xuan发布了新的文献求助10
50秒前
xuan发布了新的文献求助10
50秒前
50秒前
50秒前
xuan发布了新的文献求助10
50秒前
50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
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1500
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
Scientific Writing and Communication: Papers, Proposals, and Presentations 500
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 6371605
求助须知:如何正确求助?哪些是违规求助? 8185225
关于积分的说明 17271303
捐赠科研通 5426013
什么是DOI,文献DOI怎么找? 2870525
邀请新用户注册赠送积分活动 1847432
关于科研通互助平台的介绍 1694042