In clinical settings, biopsies are routinely used to determine cancer type and grade based on tumor cell morphology, as determined via histochemical or immunohistochemical staining. Unfortunately, in a significant number of cases, biopsy results are inconclusive. Moreover, even when primary cancer origin can be identified, phenotypic subtypes are rarely differentiated, often leading to inefficient or ineffective treatment. Glycomic profiling of the cell membrane offers an alternate route towards cancer diagnosis. In this study, isomer-sensitive nano-LC/MS and -LCMS/MS were used to obtain a detailed, structure-specific profile of the different N-glycan structures present on cancer cell membranes. Application of this method to biopsy samples may provide complementary or supplementary information that can be used to aid cancer diagnosis and guide treatment.
Cells were harvested from cell lines representing various subtypes of breast, lung, cervical, ovarian, and lymph node cancer. After gentle lysing, cell membranes were isolated by ultracentrifugation. N-glycans were released enzymatically, and then enriched by graphitized carbon solid phase extraction.
Chip-based nano-LC/MS analysis of the cell membrane N-glycomes provided high retention time reproducibility and quantitative precision. Structure-sensitive N-glycan profiling identified hundreds of glycan peaks per cell line, including multiple isomers for most compositions.
To demonstrate the diagnostic possibilities of this method, simple dichotomous keys were created. Based simply on the relative abundances of broad glycan classes (e.g. high mannose, complex/hybrid fucosylated, complex/hybrid sialylated, etc.) most cell lines were readily differentiated and identified. More closely-related cell lines were differentiated based on several-fold differences in the abundances of individual glycans. For example, lung carcinoma cell lines NCI-H358 and A549 were differentiated by parallel six-fold differences between the abundances of biosynthetically-related N-glycans Hex3HexNAc2Fuc, Hex3HexNAc3Fuc, and Hex3HexNAc4Fuc (which each differ from the next by only one HexNAc). In clinical settings, similar keys might allow a diagnostician to quickly and rapidly identify different cancer cell types based on a glycomic profile.