Tutorial: best practices and considerations for mass-spectrometry-based protein biomarker discovery and validation

Area of Science:

• Biochemistry
• Proteomics
• Biomarker Discovery

Background:

• Mass-spectrometry-based proteomic analysis is vital for identifying disease biomarkers.
• Key study design elements like cohort selection and quality control are often overlooked.
• Lack of rigor in experimental design can hinder biomarker discovery and validation.

Purpose of the Study:

• To provide a comprehensive tutorial on designing and implementing liquid-chromatography-mass-spectrometry-based biomarker discovery studies.
• To highlight critical considerations and potential pitfalls in each study phase.
• To offer guidance for improving the rigor and reproducibility of biomarker development.

Main Methods:

• Discusses experimental design, including cohort selection, statistical power, blinding, and randomization.
• Details sample collection, processing, and data collection procedures.
• Provides guidance on data processing and statistical analysis for biological interpretation.

Main Results:

• Identifies common oversights in proteomic biomarker study design.
• Outlines essential steps for robust experimental design and execution.
• Includes examples of successful biomarker studies to illustrate best practices.

Conclusions:

• Adherence to rigorous study design is crucial for reliable proteomic biomarker discovery.
• This tutorial serves as a reference for improving the quality of biomarker development studies.
• Emphasizes the importance of careful planning from study inception through data interpretation.