Multi-Omics-Based Prognosis and Precision Therapy in Esophageal Cancer, Mediastinal Tumors, and other Thoracic Diseases

Thoracic malignancies—particularly esophageal cancer and mediastinal tumors—present complex clinical challenges characterized by significant molecular heterogeneity, variable postoperative trajectories, and high recurrence rates. Despite advances in surgical techniques and perioperative care, traditional clinical staging systems often fall short in accurately predicting individual patient outcomes or guiding adjuvant therapeutic strategies. The rapid evolution of multi-omics technologies (genomics, transcriptomics, proteomics, metabolomics, and epigenomics) alongside spatial profiling and radiomics offers an unprecedented opportunity to dissect the molecular landscapes of these diseases, identify high-risk postoperative phenotypes, and tailor precision therapies.This Research Topic aims to bridge the gap between high-throughput multi-omics discovery and clinical thoracic surgical practice. We seek to highlight cutting-edge translational research that integrates multi-modal omics datasets with clinical, pathological, and longitudinal outcome data to improve postoperative prognostic prediction, refine risk stratification, and uncover novel therapeutic targets for patients with esophageal cancer and mediastinal tumors.We welcome Original Research, Systematic Reviews, Mini-Reviews, Clinical Trials, Methods, and Perspective articles focusing on, but not limited to, the following themes:• Multi-omics integration (genomics, transcriptomics, proteomics, metabolomics) for postoperative risk stratification and survival prediction in esophageal cancer and mediastinal neoplasms.• Liquid biopsy biomarkers (circulating tumor DNA, microRNAs, extracellular vesicles) for postoperative minimal residual disease (MRD) monitoring and early recurrence detection.• Spatial omics, single-cell sequencing, and tumor microenvironment profiling to understand treatment resistance and postoperative therapeutic response.• Radiomics and pathomics integration with omics data (radiogenomics) for non-invasive prognostic modeling and precision treatment planning.• Identification and clinical validation of novel actionable targets for precision adjuvant/neoadjuvant immunotherapy, targeted therapy, or combination regimens.• Machine learning and artificial intelligence models for multi-modal data fusion and clinical decision-support systems in thoracic surgical oncology.By assembling high-quality clinical and translational contributions, this collection aims to establish robust multi-omics frameworks that advance personalized postoperative management and elevate long-term outcomes for patients with thoracic diseases. Topic editors: Shenghui Li, Xichun Qin, Aikeliyaer Ainiwaer, Hao Qin Source: https://www.frontiersin.org/research-topics/84409/multi-omics-based-prognosis-and-precision-therapy-in-esophageal-cancer-mediastinal-tumors-and-other-thoracic-diseases