Functional single-cell multi-omics in cancer immunology

The advent of single-cell omics technologies has revolutionized our understanding of the complex cellular landscape in cancer. Traditional bulk sequencing often masks rare cell populations and stochastic gene expression patterns that drive immune evasion and therapeutic resistance. By integrating single-cell RNA sequencing, single-cell ATAC-seq, and spatial transcriptomics, researchers can now dissect the heterogeneity of immune cells with unprecedented resolution. These high-dimensional approaches have uncovered novel subsets of exhausted T cells and intricate communication networks. As the field moves toward precision oncology, characterizing these molecular signatures is essential for identifying biomarkers of treatment response and discovering next-generation therapeutic targets. This Research Topic aims to synthesize breakthroughs in single-cell methodologies to provide a comprehensive view of cancer immunology beyond simple descriptive mapping.The primary challenge in modern cancer immunology is the high degree of heterogeneity which leads to inconsistent responses to immunotherapies. While we have identified various immune phenotypes, the functional consequences and dynamic transitions of these cells during treatment remain poorly understood. The goal of this Research Topic is to address how multi-omic integration and advanced computational modeling can bridge the gap between descriptive single-cell atlases and functional clinical insights. We seek to explore how trajectory inference, metabolic profiling, and spatial architecture analysis can predict patient outcomes. Recent advances in CITE-seq and CRISPR-based single-cell screening offer powerful ways to validate the functional roles of genetic variants. By gathering high-quality research, this topic aims to define the rules of immune cell plasticity and identify actionable mechanisms to overcome immunosuppressive barriers in cancer.This Research Topic focuses on the integration of single-cell multi-omics and cancer immunology with an emphasis on deciphering the complex dynamics of immune responses and therapeutic outcomes. We welcome innovative studies that transition from descriptive observations to functional, predictive models. Our goal is to gather research that leverages single-cell resolution to address critical clinical challenges in immuno-oncology, including predictive modeling of immunotherapy response, functional validation of novel immune states, and the use of spatial transcriptomics to define prognostic immune neighborhoods. We encourage submissions supported by robust experimental or clinical validation. We welcome all manuscript types accepted by the journal, including original research, bioinformatics methods, reviews, and experimental studies that showcase the latest advances and future directions in this field. Topic editors: Wenxing Li, Shaoxing Dai Source: https://www.frontiersin.org/research-topics/79087/functional-single-cell-multi-omics-in-cancer-immunology