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!

Genomic characterisation of diffuse large B-cell lymphoma

计算生物学 弥漫性大B细胞淋巴瘤 淋巴瘤 生物 病理 癌症研究 医学
作者
Francesca Harrington,Mark Greenslade,Dipti Talaulikar,Greg Corboy
出处
期刊:Pathology [Elsevier BV]
卷期号:53 (3): 367-376 被引量:15
标识
DOI:10.1016/j.pathol.2020.12.003
摘要

Diffuse large B-cell lymphoma (DLBCL) is a genomically heterogenous disease comprised of many subtypes that display significantly different clinical outcomes, in the context of treatment with conventional immunochemotherapy. Poor clinical outcomes in some subtypes, and imperfect identification of high risk individuals in otherwise low risk subgroups, demonstrate there is room for improvement in the subclassification and risk stratification of DLBCL. In addition, more comprehensive profiling may lead to improved molecular testing guided treatment selection. Existing characterisation and risk stratification strategies, such as division of DLBCL into activated B-cell (ABC) and germinal centre B-cell (GCB) subtypes, although prognostically useful, may oversimplify the underlying biology and have proven to be less useful in improving therapy selection. Several groups have proposed more predictive molecular testing based prognostic models with potentially more relevance to therapy choice. These alternative approaches use more resource intensive comprehensive genomic profiling strategies which present practical challenges to implement in diagnostic laboratories. The addition of genomic testing to the subclassification of DLBCL shows promise, but laboratories must identify testing strategies relevant to clinical practice. A consensus on optimal molecular profiling techniques is yet to be achieved. In this article we review various next generation sequencing-based analytical techniques and molecular classification models proposed recently. Emerging therapeutics where molecular profiling may guide patient selection are also reviewed. The potential utility of genomic testing in DLBCL is discussed, in addition to practical considerations when considering introducing genomics into the diagnostic laboratory. Diffuse large B-cell lymphoma (DLBCL) is a genomically heterogenous disease comprised of many subtypes that display significantly different clinical outcomes, in the context of treatment with conventional immunochemotherapy. Poor clinical outcomes in some subtypes, and imperfect identification of high risk individuals in otherwise low risk subgroups, demonstrate there is room for improvement in the subclassification and risk stratification of DLBCL. In addition, more comprehensive profiling may lead to improved molecular testing guided treatment selection. Existing characterisation and risk stratification strategies, such as division of DLBCL into activated B-cell (ABC) and germinal centre B-cell (GCB) subtypes, although prognostically useful, may oversimplify the underlying biology and have proven to be less useful in improving therapy selection. Several groups have proposed more predictive molecular testing based prognostic models with potentially more relevance to therapy choice. These alternative approaches use more resource intensive comprehensive genomic profiling strategies which present practical challenges to implement in diagnostic laboratories. The addition of genomic testing to the subclassification of DLBCL shows promise, but laboratories must identify testing strategies relevant to clinical practice. A consensus on optimal molecular profiling techniques is yet to be achieved. In this article we review various next generation sequencing-based analytical techniques and molecular classification models proposed recently. Emerging therapeutics where molecular profiling may guide patient selection are also reviewed. The potential utility of genomic testing in DLBCL is discussed, in addition to practical considerations when considering introducing genomics into the diagnostic laboratory.
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
6秒前
小6s完成签到,获得积分10
6秒前
7秒前
14秒前
暖树发布了新的文献求助10
15秒前
风止何安完成签到,获得积分10
18秒前
自觉的猕猴桃完成签到,获得积分10
18秒前
成就的翠芙完成签到,获得积分10
19秒前
21秒前
开心每一天完成签到,获得积分20
26秒前
ss完成签到 ,获得积分10
30秒前
30秒前
32秒前
科研通AI6.4应助jie采纳,获得10
43秒前
悦耳的城完成签到,获得积分10
43秒前
丘比特应助科研通管家采纳,获得10
45秒前
Nole应助科研通管家采纳,获得10
45秒前
Hello应助科研通管家采纳,获得10
45秒前
烟花应助科研通管家采纳,获得10
45秒前
Nole应助科研通管家采纳,获得10
45秒前
uui完成签到,获得积分20
49秒前
50秒前
NexusExplorer应助前方的菜鸟采纳,获得10
54秒前
56秒前
暖树发布了新的文献求助10
59秒前
1分钟前
1分钟前
99发布了新的文献求助10
1分钟前
Otis完成签到,获得积分10
1分钟前
1分钟前
Youy完成签到 ,获得积分10
1分钟前
1分钟前
fuz关闭了fuz文献求助
1分钟前
1分钟前
Yummy完成签到 ,获得积分10
1分钟前
无限的水香完成签到,获得积分10
1分钟前
优美的烙完成签到,获得积分10
1分钟前
99发布了新的文献求助10
1分钟前
1分钟前
1分钟前
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
Nine new races of Peronospora manshurica found on soybeans in the Midwest 1000
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 600
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Eudora Welty and Modern Media 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 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7772344
求助须知:如何正确求助?哪些是违规求助? 9314705
关于积分的说明 20339640
捐赠科研通 7357725
什么是DOI,文献DOI怎么找? 3316905
关于科研通互助平台的介绍 2465414
邀请新用户注册赠送积分活动 2331910