Protocol for using scCURE to construct an immunotherapy outcome prediction model

It is challenging to predict the immunotherapy outcome from the baseline status of patients with cancer. Here, we introduce a protocol for constructing an immunotherapy prediction model utilizing single-cell RNA sequencing (scRNA-seq)-based changed and unchanged cell recognition during immunotherapy (scCURE). Initially, we describe the steps for using scCURE to discriminate unchanged cells with similar cellular and molecular functions from whole scRNA-seq data. Subsequently, we demonstrate ways to construct immunotherapy outcome prediction models using either scRNA-seq or bulk RNA sequencing (RNA-seq) data, predicated on the unchanged cells identified by scCURE. For complete details on the use and execution of this protocol, please refer to Zou et al.<sup>1</sup>.

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Publication Details

Journal
STAR Protocols
Published
2024-12-01
DOI
https://doi.org/10.1016/j.xpro.2024.103476
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00

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article

Protocol for using scCURE to construct an immunotherapy outcome prediction model

Liang Tan, Henry H. Y. Tong, Xin Zou, Yuan Ji et al.
STAR Protocols
Single-cell and spatial transcriptomics
article

Protocol for using scCURE to construct an immunotherapy outcome prediction model

Liang Tan, Henry H. Y. Tong, Xin Zou, Yuan Ji, Yujun Liu, Jie Hao
article en

Abstract

It is challenging to predict the immunotherapy outcome from the baseline status of patients with cancer. Here, we introduce a protocol for constructing an immunotherapy prediction model utilizing single-cell RNA sequencing (scRNA-seq)-based changed and unchanged cell recognition during immunotherapy (scCURE). Initially, we describe the steps for using scCURE to discriminate unchanged cells with similar cellular and molecular functions from whole scRNA-seq data. Subsequently, we demonstrate ways to construct immunotherapy outcome prediction models using either scRNA-seq or bulk RNA sequencing (RNA-seq) data, predicated on the unchanged cells identified by scCURE. For complete details on the use and execution of this protocol, please refer to Zou et al.<sup>1</sup>.

STAR ProtocolsVol. 5(4)
Fudan University (CN), Fudan University Shanghai Cancer Center (CN), Shanghai Ninth People's Hospital (CN), Zhongshan Hospital (CN), Macao Polytechnic University (MO), Shanghai Institute of Technology (CN)
National Natural Science Foundation of China, Shanghai Jiao Tong University
Openalex Percentile: Top 80%
Single-cell and spatial transcriptomics
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