Finding the sweet spot – the pursuit of single cell glycomics by CE-MS

Introduction

There is still an urgent clinical need for new specific molecular targets that can be utilized to establish better diagnostic, prognostic as well as therapeutic treatments for cancer patients. A hallmark of many diseases, including cancer, are alterations in glycosylation (e.g. covalent attachment of sugar moieties to proteins or lipids), providing new opportunities for better patient stratification. This is not surprising as glycosylation is involved in many biological processes, and glycan structures cover our cells in a dense layer and contribute to the malignant phenotype of cancer cells by promoting proliferation, metastasis, and immunosuppression. However, a more thorough investigation is needed on the glycomic intratumoral heterogeneity (e.g. primary versus metastatic tumors), as tumors consist of a network of cell populations that are interconnected in tissue matrix. Therefore, it is of utmost importance that analytical workflows are used that can distinguish between these populations, and reveal the relevant cells by single cell analysis. However, current glycomic methods still require a large amount of cells (20,000 up to 100,000 cells). Here, we present an innovative and miniaturized high-sensitivity glycomics workflow (capillary electrophoresis coupled to mass spectrometry; CE-MS).

Methods

Various conditions of the 96-well polyvinylidene difluoride (PVDF) membrane approach were evaluated (e.g. membrane blocking and N-glycan release conditions). By implementing the release on the membrane as well as using a hydrazide labeling procedure, no additional purification steps were required. Analysis was performed on a CE-MS platform and the complete workflow was further evaluated by its application for the characterization of the N-glycome from total plasma, extracellular vesicles and two cell lines (PaTu-S and JY) using various amount of lysed cells (1 – 200,000 cells).

Results

A highly diverse N-glycome was observed for all samples and the CE-MS demonstrated its ability to separate isomeric structures, in particular differently linked sialic acids, without the need of an additional derivatization step. A total of 72 N-glycans could be relatively quantified from 5,000 PaTu-S cells using the optimized protocol. The five most abundant N-glycans could still be detected using ~1 cell after cell lysis.

Conclusions

In this study we achieved an exceptional sensitivity for glycomic analysis that only requires minimal sample amounts (e.g., up to a single cell or 100 pg of protein weight). Future endeavors will focus on using the workflow for isolated single cells (sorted by the CellenONE system) as well as to apply it on laser-capture microdissected samples. In time, this will allow us to gain in-depth insights into the role of glycosylation in tumor progression and how these alterations can be exploited for personalized treatment strategies through improved diagnosis and prognosis of cancer patients.