Protocol for decoding immune predictors of response to immunotherapy through pan-cancer multiomics analysis
Year: 2025
Type: article
Abstract: Here, we present a protocol for analyzing T cell dynamics in multiple cancers through single-cell RNA sequencing (scRNA-seq), single-cell immune profiling, and mass cytometry/cytometry by time-of-flight (CyTOF). We describe steps for performing gene-regulatory network analysis to identify key transcription factors and cell-cell interaction analysis to explore immune signaling. This protocol facilitates the identification of T cell subsets associated with immune checkpoint blockade (ICB) response and the development of predictive biomarkers. For complete details on the use and execution of this protocol, please refer to Li et al. 1 • Steps for integrating multi-omics data to analyze T cell dynamics across cancers • Instructions for single-cell RNA sequencing from sample collection to data analysis • Guidance on TCR clonality analysis to track T cell response to ICB therapy • Steps for building a response prediction model and response index (RI) for ICB therapy Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. Here, we present a protocol for analyzing T cell dynamics in multiple cancers through single-cell RNA sequencing (scRNA-seq), single-cell immune profiling, and mass cytometry (CyTOF). We describe steps for performing gene-regulatory network analysis to identify key transcription factors and cell-cell interaction analysis to explore immune signaling. This protocol facilitates the identification of T cell subsets associated with immune checkpoint blockade (ICB) response and the development of predictive biomarkers.
Source: STAR Protocols
Authors: Xinyue Jian, Xu Zheng, Kun Jiao, Weiyuan Li, Xuexin Li
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,550
OpenAlex ID: W4415901448