Protocol to analyze immune cells in the tumor microenvironment by transcriptome using machine learning

Summary: Immunotherapy is a promising strategy to treat cancer. Here, we present a protocol for analyzing the transcriptome-based phenotypic alterations and immune cell infiltration in the tumor microenvironment. We describe steps for integrating single-cell RNA sequencing (scRNA-seq) data, comparin...

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Bibliographic Details
Main Authors: Yunxi Liao, Ziyan Rao, Shaodong Huang, Dongyu Zhao
Format: Article
Language:English
Published: Elsevier 2024-03-01
Series:STAR Protocols
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2666166723006512
Description
Summary:Summary: Immunotherapy is a promising strategy to treat cancer. Here, we present a protocol for analyzing the transcriptome-based phenotypic alterations and immune cell infiltration in the tumor microenvironment. We describe steps for integrating single-cell RNA sequencing (scRNA-seq) data, comparing phenotypes and origins of mononuclear phagocytes, inferring the differentiation trajectory and infiltration process, and identifying infiltration-associated genes using machine learning. We then detail procedures for exploring the impact of these genes in prognosis through the integrated microarray and bulk RNA-seq data to obtain potential drug targets.For complete details on the use and execution of this protocol, please refer to Liao et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.
ISSN:2666-1667