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>.
Authors
- Liang Tan (ORCID: https://orcid.org/0000-0002-9014-5371)
- Henry H. Y. Tong (ORCID: https://orcid.org/0000-0003-2687-741X)
- Xin Zou (ORCID: https://orcid.org/0000-0003-3695-0465)
- Yuan Ji (ORCID: https://orcid.org/0000-0002-2631-9082)
- Yujun Liu
- Jie Hao (ORCID: https://orcid.org/0000-0002-0273-8047)
Institutions
- 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)
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
Funders
- National Natural Science Foundation of China
- Shanghai Jiao Tong University