Advancing biomarkers from discovery to clinical use requires rigor, scale, and audit-ready data. There is high demand for assays that quantify targets in complex matrices, survive method transfer, and meet GCLP (Good Clinical Laboratory Practices) expectations. Mass spectrometry enables that path with sensitivity, specificity, and flexible panel design.
In this Q&A, Casey Coutelin Johnson, Operations Manager at Precision Biomarker Laboratories, part of the Proteomics and Metabolomics Core Facility at Cedars-Sinai Medical Center, explains how a Contract Research Organization (CRO) readies assays for the clinic. He discusses study design, automated prep, instrument access, peptide standards, and compliant reporting.
What are the biggest challenges researchers face today in advancing biomarkers from discovery to clinical application?
Some sponsors looking to use biomarkers in their clinical applications, whether it is an assay or a medical device, can have a difficult time finding the right CRO. Factors such as project turnaround, instrument availability, and quality work that is auditable by regulatory bodies are important aspects of a CRO that sponsors assess. Precision Biomarker Laboratories at Cedars-Sinai operates as a CRO, and our mission is to use our cutting-edge technology and expertise to identify biomarkers of interest to our clients in a manner that is easily incorporated into their organizational knowledge base. From meeting our clients to sending final reports, our workflows and processes are performed with a level of rigor and detail that complies with GCLP.
How is mass spectrometry helping to overcome key limitations in biomarker discovery and validation?
Mass spectrometry provides high sensitivity, specificity, comprehensive coverage, and the ability to perform quantitative and unbiased analyses. This makes it an indispensable tool in the identification and validation of biomarkers for disease diagnosis, prognosis, and therapeutic monitoring.
What technical or workflow innovations have most improved the reproducibility and scalability of proteomics-based biomarker analysis?
Automated liquid handlers, colloquially known as ‘robots’, have significantly reduced variance in data between samples as well as between runs. Implementing separation techniques onto these robots, such as positive pressure units for solid state elution or magnetic beads with selective binding abilities, reliably streamlines the workflow overall.
What hurdles still need to be addressed to enable broader clinical adoption of proteomics-based biomarkers?
Despite the power and sophistication of mass spectrometers, their initial cost, maintenance, and supporting infrastructure requirements can prevent widespread accessibility. The synthesis of peptide standards required for validated assays can also be time-consuming and expensive. Mass spectrometry technology is constantly improving, so new technology that is readily available in a research laboratory may be more difficult to set up in a clinical laboratory.
Looking ahead, what trends or emerging technologies do you see as most promising for the future of biomarker discovery?
The future of biomarker discovery is being transformed by several promising trends and emerging technologies. Multi-omics approaches, which integrate genomics, transcriptomics, proteomics, and metabolomics, provide a comprehensive understanding of biological systems, thereby enhancing biomarker discovery. Single-cell analysis enables the study of cellular heterogeneity and the identification of cell-specific biomarkers, especially in cancer research. Machine learning and artificial intelligence analyze large datasets to uncover novel patterns and refine biomarkers. Spatial omics technologies map biomolecules within tissues, offering insights into disease pathology and spatially resolved biomarkers. Liquid biopsy, a non-invasive method for detecting biomarkers in bodily fluids, shows promise for cancer diagnosis and monitoring. Advances in mass spectrometry improve biomarker characterization, while CRISPR and gene-editing technologies study the functional roles of biomarkers. Wearable and implantable biosensors offer real-time monitoring for personalized medicine. Additionally, blockchain technology is being explored for secure data sharing, facilitating collaborative biomarker discovery. These trends and technologies are poised to accelerate biomarker discovery and validation, ultimately leading to enhanced diagnostics and more effective therapeutic strategies.