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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 Bagley¹, Souvik Seal¹, Lauren R Fanning¹

¹Medical University of South Carolina.

Research square

|April 29, 2025

概括

一种新的NanoString nCounter方法改善了各种结直肠病变中的免疫基因概况. 这种方法提高了质量控制,减少了样本排除,为分析FFPE样本提供了强大的框架.

科学领域:

在瘤学瘤学.
免疫学免疫学免疫学
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.
嵌入式固定 (FFPE) 样本由于生物异质性而存在独特的挑战.

研究的目的:

开发和验证基于NanoString nCounter的质量控制 (QC),规范化和微分表达式 (DE) 分析方法.
优化对FFPE样本的分析,其中含有来自分子多样性结直肠病变的低质量RNA.
在具有挑战性的样本类型中提高免疫基因分析的准确性和效率.

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基因免疫面板评估了三个正常化方法 (RUVg,NanoStringDiff,nSolver).
分析的重点是通过FDR校正的q值来研究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.
所有方法都在状状病变 (SSL) 和管状腺瘤 (TA) 之间确定了DE基因.
删除不需要的变异 (RUVg) 和NanoStringDiff (NSDiff) 在管状/状腺瘤 (TVs) 和TA之间检测到DE基因,表明免疫基因的广泛表达不足. NSDiff显示出更高的灵敏度,但也显示出更高的I型错误率和计算需求.

结论:

RUVg提供了计算效率和较低的I型错误之间的平衡.
NSDiff提供了更高的灵敏度,但在计算上更苛刻,并且具有更高的I型错误率.
开发的NanoString nCounter方法为异质结直肠病变中的免疫基因分析提供了一个强大的框架.

关键词:

在NanoString中使用.在RUV和RUV中.免疫表达免疫表达状状病变的病变可能是状的.

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