Body composition predicts immunotherapy outcomes in advanced oesophagogastric cancer with cross-species mechanistic insights

Description This dataset contains quantitative metabolomic profiles generated for the study “Body composition predicts immunotherapy outcomes in advanced oesophagogastric cancer with cross-species mechanistic insights.” The data include targeted and untargeted metabolite measurements from both preclinical mouse models and a human patient cohort, supporting the analysis of muscle mass, systemic metabolism, and treatment response. Mouse dataMetabolomic measurements were obtained from mouse skeletal muscle tissue and plasma samples collected under controlled experimental conditions. Both targeted and untargeted profiling approaches were used to capture metabolites relevant to muscle composition and one-carbon metabolic pathways. These data were used to explore mechanistic links between muscle loss and anti-tumor immunity. Human cohort dataThe human plasma dataset includes anonymized quantitative metabolite measurements from patients with advanced oesophagogastric cancer undergoing immunotherapy. These data were generated to assess metabolic signatures associated with body composition and clinical outcomes. All human biospecimens were collected in accordance with institutional ethical approvals, and no identifiable personal information is included in this repository. Purpose and usageThe dataset provides the quantitative foundation for cross-species analyses performed in the manuscript, enabling reproducibility of key findings related to skeletal muscle metabolism, systemic metabolic status, and immunotherapy response. Users may employ these data for validation, re-analysis, or integrative modeling. Data formatAll files are provided in CSV/XLSX formats containing normalized metabolite abundance values. Variable names and sample identifiers correspond to experimental groups or patient study IDs without personal identifiers. Ethics and privacyHuman data have been fully de-identified and comply with ethical and privacy regulations. Raw clinical information and protected health data are not included. Additional access to restricted clinical variables, if required, may be requested from the corresponding author subject to institutional approval. Funding and acknowledgmentsThis dataset was generated as part of research conducted at Peking University Cancer Hospital & Institute.