Single-Cell and Multi-Omics in Precision Oncology: Decoding Tumor Heterogeneity, Microenvironment States and Therapy Resistance

Cancer is a highly heterogeneous disease driven by complex interactions between genetic, epigenetic, transcriptional, and metabolic alterations within tumor cells and their surrounding microenvironment. Conventional bulk profiling approaches mask this cellular diversity, limiting the understanding of tumor evolution, therapy resistance, and disease progression. Recent advances in single-cell and multi-omics technologies have enabled high-resolution dissection of tumor ecosystems, allowing simultaneous characterization of malignant cells, immune populations, stromal components, and their dynamic states. Integrating single-cell genomics, transcriptomics, epigenomics, proteomics, and metabolomics provides a comprehensive framework to uncover molecular drivers of heterogeneity and resistance mechanisms. These approaches are transforming precision oncology by enabling more accurate tumor stratification, identification of predictive biomarkers, and development of personalized therapeutic strategies tailored to individual tumor biology.

Despite significant advances in cancer genomics, clinical decision-making remains limited by an incomplete understanding of tumor heterogeneity, dynamic microenvironmental interactions, and mechanisms of therapy resistance. Current diagnostic and prognostic approaches often rely on bulk molecular analyses that obscure rare but clinically relevant cellular populations and fail to capture spatial and temporal tumor evolution. The primary goal of this Research Topic is to decode the cellular and molecular complexity of cancer using integrated single-cell and multi-omics approaches to advance precision oncology. This project aims to systematically characterize malignant, immune, and stromal cell populations, define functional tumor microenvironment states, and identify molecular pathways driving treatment resistance and disease progression. By integrating genomic, transcriptomic, epigenomic, proteomic, and metabolomic data, this study seeks to identify robust biomarkers and actionable targets that enable refined patient stratification, guide therapeutic selection, and inform the development of personalized treatment strategies.

This Research Topic focuses on the application of single-cell and multi-omics technologies to advance precision oncology by elucidating tumor heterogeneity, microenvironmental states, and mechanisms of therapy resistance. We welcome contributions addressing integrative analyses of single-cell genomics, transcriptomics, epigenomics, proteomics, metabolomics, and spatial omics across diverse cancer types. Topics of interest include tumor evolution and clonal dynamics, immune–tumor interactions, biomarkers of response and resistance, molecular predictors of treatment outcome, and translational applications informing personalized therapeutic strategies. Studies incorporating innovative computational frameworks for multi-omics integration and clinically annotated datasets are particularly encouraged. We invite submissions in the form of original research articles, brief research reports, systematic reviews, meta-analyses, perspectives, and methodological papers that advance the understanding of tumor biology and enable clinically actionable insights in precision oncology.




***Please note: Manuscripts consisting solely of bioinformatics, computational analysis, or predictions of public databases which are not accompanied by validation (independent clinical or patient cohort, or biological validation in vitro or in vivo, which are not based on public databases) are not suitable for publication in this journal.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Systematic Review
• Technology and Code

Keywords: Single-Cell Sequncing, Multi-Omics Precision Oncology, Tumor Heterogeneity, Tumor Microenvironment, Therapy resistance mechanisms

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.