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Updated: May 9, 2025

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment

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Published on: March 25, 2020

在转录学中透露复杂组织和瘤的免疫微环境,通过解卷方法

Shu-Hwa Chen¹, Bo-Yi Yu², Wen-Yu Kuo³

¹TMU Research Center of Cancer Translational Medicine, Taipei Medical University, 250 Wu-Xing Street, Taipei, Taiwan.

|April 30, 2025

概括

分析瘤透白细胞是癌症免疫治疗的关键. 我们开发了DOCexpress_fastqc和mySORT,这是一个生物信息工作流,可以从RNA测序数据中准确地描述免疫细胞组成,从而改善免疫疗法研究.

科学领域:

计算生物学是一种计算生物学.
生物信息学是一种生物信息学.
免疫学免疫学免疫学

背景情况:

对瘤透白细胞的准确分析对于推进癌症免疫治疗至关重要.
目前用于免疫微环境分析的生物信息学方法复杂且具有挑战性.
了解免疫细胞的组成对于预测治疗反应至关重要.

研究的目的:

开发一种简化生物信息学工作流程,用于从RNA测序数据分析免疫细胞组成.
为了创建一个用户友好的工具包 (DOCexpress_fastqc) 和网络应用程序 (mySORT) 增强免疫分析.
为解读瘤免疫微环境提供更准确和更容易使用的方法.

主要方法:

开发了一种集成DOCexpress_fastqc (Galaxy/Docker中的hisat2-stringtie管道) 的两步工作流程,用于RNA测序基因表达概况.
使用mySORT,一个使用解卷算法的网络应用程序,以确定21个子类的免疫细胞含量.
使用来自单细胞RNA测序 (scRNA-seq) 数据集的合成伪批量数据验证了mySORT.

主要成果:

mySORT与基本真相免疫细胞组成有很强的一致性 (皮尔森的r=0.871用于黑色素瘤,0.775用于头癌).
mySORT在免疫细胞解体的准确性方面超过了CIBERSORT等现有方法.
该工具包为大量RNA测序数据提供了增强的分辨率,并包括数据可视化功能.

结论:

开发的工作流和mySORT工具为分析癌症免疫细胞组成提供了准确有效的方法.
这种方法有助于更深入地了解瘤免疫微环境,这对于免疫疗法开发至关重要.
免费可用的工具包和网络应用程序使研究人员能够推进癌症免疫治疗策略.

关键词:

阿尔法多样性的多样性贝塔多样性贝塔多样性癌症癌症癌症癌症解体解体是一种解体.免疫微环境是一个微环境.免疫治疗是一种免疫疗法.精准医学是一门精准的医学.

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