Advancing single-cell proteomics for profiling tumour heterogeneity

Tumour heterogeneity is the mayor cause of ineffective cancer therapies, contributing to treatment resistance and metastatic progression. The intricate cellular diversity within tumours, metastases, and patient populations underscores the need advanced measurement technologies at single cell resolution. Despite significant progress in genomic and transcriptomic analyses, the comprehensive characterization of tumour proteomic heterogeneity remains elusive. Contemporary methodologies, particularly in single-cell proteomics (SCP), are facing diverse challenges. Technical barries are the ultra-low sample amounts, lack of sample amplification and very limited high throughput sample acquisition options. Biological challenges include sample complexity and heterogeneity. As a prerequisite for biological meaningful and technical reliable (single cell) sample experiments tackling the tumour heterogeneity new methods for the acquisition of thousands of single (cell) samples are needed.

To meet this technical demand, we exploited current state-of-the-art single-cell mass spectrometry acquisition methods and ultra-low sample processing workflows to overcome these challenges. By overcoming existing barriers, we established a robust and automated framework for single-cell mass spectrometry-based proteomics allowing mass spectrometry-based proteomics experiments of heterogeneous tumour samples. The established SCP workflow enables identification of more than 3000 protein ID from a single cell. Furthermore, usage of low- binding 1536 well culture microplates and semi-automated sample loading allows processing of hundreds of single cell samples in a robust and time-efficient manner. Finally, exploiting the concept of dimethyl labeling of single cell samples and the miniaturization of the labeling workflow doubles sample throughput without any significant decrease in protein identification.

The presented advancements in mass spectrometry-based SCP like automated sample processing, advanced mass spectrometry-based workflows and multiplexed sample acquisition methods hold promise for future translational cancer research. The presented improvements may contribute to a more complete understanding of proteomic tumour heterogeneity at a single cell resolution. In addition, implemented automation and enhanced throughput capabilities will further expedite the analysis of large cohorts of heterogeneous tumour samples.