Cancer biomarker discovery and validation.

TLDR

Genomic profiling and targeted therapies have elevated biomarkers as key tools for cancer management, yet a substantial gap remains between discovery and clinical translation due to development challenges. The review outlines the steps of biomarker development, highlights key validation and implementation issues, and presents representative oncology examples. It also discusses regulatory considerations and future directions in big‑data‑driven precision medicine.

Abstract

With the emergence of genomic profiling technologies and selective molecular targeted therapies, biomarkers play an increasingly important role in the clinical management of cancer patients. Single gene/protein or multi-gene "signature"-based assays have been introduced to measure specific molecular pathway deregulations that guide therapeutic decision-making as predictive biomarkers. Genome-based prognostic biomarkers are also available for several cancer types for potential incorporation into clinical prognostic staging systems or practice guidelines. However, there is still a large gap between initial biomarker discovery studies and their clinical translation due to the challenges in the process of cancer biomarker development. In this review we summarize the steps of biomarker development, highlight key issues in successful validation and implementation, and overview representative examples in the oncology field. We also discuss regulatory issues and future perspectives in the era of big data analysis and precision medicine.