1616-Statescope: Multi-Omics Deconvolution for Tumor States

The paper introduces Statescope, a novel Bayesian framework designed to identify cell states and composition within tumors by analyzing bulk RNA-seq data. This computational tool improves upon existing methods by integrating DNA-derived malignant cell purity and modeling inter-sample variation, allowing for more precise multi-omic deconvolution. Through rigorous benchmarking, the authors demonstrate that the system can accurately detect cellular states, including those frequently missed by single-cell sequencing or absent from reference signatures. When applied to clinical trial data, Statescope successfully identified specific immune cell signatures that predict how patients will respond to immunotherapy. Ultimately, the platform transforms widely available genomic data into a powerful resource for discovering biomarkers and understanding the complex tumor microenvironment.

References:

• Janssen J, Steketee M F B, Bose A, et al. Statescope: an integrative deconvolution framework for discovering cell states in tumors[J]. Nature Communications, 2026.