相关实验视频

Updated: Jul 1, 2025

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Published on: November 11, 2014

在预测蛋白质表达和生存预测中的RNA-Seq和微阵列的比较

Won-Ji Kim¹, Bo Ram Choi², Joseph J Noh¹

¹Department of Obstetrics and Gynecology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.

Frontiers in genetics

|March 11, 2024

概括

RNA测序 (RNA-seq) 和微阵列基因表达造型在预测癌症蛋白质水平和临床结果方面表现相似. 然而,特定的基因差异和不同癌症类型的生存模型准确性需要进一步调查.

科学领域:

基因组学就是基因组学.
癌症研究癌症研究
生物标志物发现发现

背景情况:

基因表达特征分析对于识别癌症生物标志物至关重要.
为此目的,RNA测序 (RNA-seq) 和微阵列是常见的技术.
将它们的性能进行比较对于可靠的临床终点预测至关重要.

研究的目的:

为了比较RNA-seq和微阵列在预测蛋白质表达和临床终点方面的性能.
通过反相蛋白阵列 (RPPA) 评估基因表达与蛋白质水平的相关性.
评估不同平台和癌症类型的生存预测模型准确性.

主要方法:

利用癌症基因组图谱 (TCGA) 数据集用于肺癌,结直肠癌,脏癌,乳腺癌,子宫内膜癌和卵巢癌.
计算了RNA-seq/microarray基因表达和RPPA蛋白表达之间的相关系数.
开发并比较使用前103个生存相关基因的随机森林生存预测模型.

主要成果:

通过RPPA测量的mRNA水平和蛋白质表达之间的高度相关性被观察到.
大多数基因在RNA-seq和microarray之间显示了类似的表达相关性.
在16个基因中发现了显著的差异;BAX和PIK3CA在特定癌症中显示出反复的关联.
生存模型的性能各不相同,微阵列在某些癌症 (结肠直肠,脏,肺) 中表现优于RNA-seq,而在其他癌症 (卵巢,子宫内膜) 中则相反.

结论:

RNA-seq和微阵列都对基因表达概况有价值,与蛋白质水平有很好的相关性.
确定了两种方法之间具有差异性表达模式的特定基因.
生存预测模型的性能取决于平台和癌症类型,需要仔细考虑临床应用.

关键词:

在RNA-seqqq.RPPA RPPA RPPA RPPA RPPA RPPA RPPA RPPA RPPA RPPA RPPA RPPA RPPA RPPA RPPA RPPA RPPA RPPA RPPA RPPA RPPA RPPA RPPA RPPA RPPA RPPA 在TCGA中,TCGA就是TCGA.生物标志物生物标志物微阵列的微阵列蛋白质表达蛋白质表达

更多相关视频

Analysis of Combinatorial miRNA Treatments to Regulate Cell Cycle and Angiogenesis

Analysis of Combinatorial miRNA Treatments to Regulate Cell Cycle and Angiogenesis

Published on: March 30, 2019

Profiling of Estrogen-regulated MicroRNAs in Breast Cancer Cells

Profiling of Estrogen-regulated MicroRNAs in Breast Cancer Cells

Published on: February 21, 2014

相关概念视频

DNA Microarrays

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

Ribosome Profiling

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...