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组织基因表达分析方法在高度技术和生物异质性的背景下

Evan Bagley^1,2, Souvik Seal^1,2, Lauren R Fanning²

¹Hollings Cancer Center, Medical University of South Carolina, Charleston, SC, USA.

BMC research notes

|July 22, 2025

概括

我们开发了一种新的NanoString方法,用于分析各种结直肠病变中的免疫基因表达,改善样本质量控制和差异表达分析,以获得更好的抗瘤免疫洞察力.

科学领域:

免疫学免疫学免疫学
基因组学就是基因组学.
生物信息学是一种生物信息学.

背景情况:

结直肠病变中的免疫表达概况提供了对抗瘤免疫力和衰老的见解.
从异质病变中分析低质量的RNA需要优化方法.
一个基于NanoString nCounter的方法被开发用于质量控制,规范化和FFPE样本的差异表达分析.

研究的目的:

开发和评估一种基于NanoString nCounter的方法,用于在异质结直肠病变中分析免疫基因表达.
为优化FFPE样本的质量控制,规范化和差异表达分析.
为了比较不同规范化方法的性能.

主要方法:

一个结肠特异性的阳性控制基因组被纳入,以尽量减少样本排除.
在100个结直肠病变样本 (SSL,TV,TA) 上使用277基因免疫小组评估了三个正常化方法 (RUVg,NSDiff,nSolver).
使用FDR校正的q值评估了I型错误率,计算效率和基因显著性.

主要成果:

与标准方法相比,结肠特异性QC集减少了63%的样本排除.
所有方法都确定了在状状病变 (SSL) 和管状腺瘤 (TA) 之间差异表达的基因.
RUVg和NanoStringDiff (NSDiff) 检测到管状/状腺瘤 (TVs) 和TA之间的显著差异性表达,表明免疫基因表达不足. 与RUVg相比,NSDiff显示出更高的灵敏度,但也显示出更高的I型错误率和更高的计算需求.

结论:

在免疫基因分析中,RUVg提供了计算效率和低I型错误的平衡.
NSDiff更敏感,但在计算上要求更高的I型错误率.
开发的NanoString方法为异质结直肠病变中的免疫基因分析提供了强大的框架.

关键词:

免疫表达的表达方式在NanoString中使用.在RUV和RUV中.状状病变是一种状病变.

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