From Multi-Omics to Clinical Utility: Biomarker Discovery and Validation in Solid Tumors

The field of cancer genetics and oncogenomics has been transformed by advancements in multi-omics technologies, enabling comprehensive analyses of solid tumors at genomic, transcriptomic, epigenomic, proteomic, and metabolomic levels. Despite the accelerated pace of biomarker discovery, significant challenges persist in translating these molecular signatures into clinically useful tools. Critical gaps remain in ensuring that biomarkers are robust, reproducible, and applicable across diverse patient populations and tumor microenvironments. Recent research has highlighted the promise of integrating high-throughput multi-omic data with advanced computational models, including artificial intelligence and machine learning, to identify biomarker candidates with high diagnostic, prognostic, or predictive value. However, few biomarkers have advanced to routine clinical adoption due to hurdles in analytical and clinical validation, standardization, and regulatory approval.This Research Topic aims to bridge the gap between biomarker discovery and clinical utility by focusing on multidisciplinary approaches that drive robust validation and real-world implementation in solid tumor oncology. We seek contributions that address key questions such as: Which multi-omic signatures best predict treatment response, resistance, or disease progression? How can integrative analytics and AI improve the identification and validation of clinically relevant biomarkers? What are the best practices for designing and validating assays that can transition from research to clinical laboratories? We encourage studies that not only develop novel biomarkers but also rigorously test their reproducibility, generalizability, and readiness for clinical deployment, fostering a direct impact on precision medicine.To gather further insights in the biomarker discovery and validation continuum for solid tumors, we welcome articles addressing, but not limited to, the following themes:• Multi-omic integration for biomarker identification and prioritization• Methodological advances in single-cell and spatial omics for tumor profiling• Analytical and clinical validation of biomarker assays• AI and machine learning applications in biomarker modeling and interpretation• Translational workflows from biomarker discovery to real-world clinical utility• Regulatory, ethical, and implementation challenges for clinical omics• Biomarker performance Article types may include original research, reviews, brief research reports, methods, perspectives, and case studies. Topic editors: Salima Akter, Muhammad Shahid Source: https://www.frontiersin.org/research-topics/78954/from-multi-omics-to-clinical-utility-biomarker-discovery-and-validation-in-solid-tumors