The clinical promise of mass spectrometry-based single-cell proteomics: from bedside to bench

Single-cell proteomics (SCP) is entering into a transformative phase, moving beyond technically demanding benchmarking studies toward robust and reproducible workflows capable of quantifying thousands of proteins per cell. These advances highlight SCP's potential to address clinically relevant questions by resolving cellular and pathological heterogeneity that remains obscured in bulk proteomics.

This review discusses current advances, challenges, and clinical applications of SCP based on literature identified through searches in major scientific databases. Many clinically relevant samples remain underexplored in SCP studies, in part because their application requires careful evaluation of pre-analytical variables that can strongly influence proteomic readouts. Current SCP methodologies vary according to sample type, experimental conditions, and available resources. Compared with single-cell RNA sequencing, SCP remains limited in cellular throughput, making it challenging to define optimal sample sizes and to reliably detect both abundant and rare cell populations. These limitations also make dataset integration difficult, as reduced cellular coverage and sampling depth increase data sparsity. Moreover, implementing quality control strategies across sequential SCP experiments is essential to ensure data robustness, comparability, and accurate biological interpretation.

Applying SCP to clinical samples advances our understanding of biological complexity and holds potential to drive progress in translational and precision medicine.