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Gan Y, Johnson EJ, Tran V, Spitler K, Liang Y, et al.
mAbs •
Alpha-galactosylation, galactose-α-1,3-galactose (α-Gal), is always regarded as a critical quality attribute due to its potential to provoke immunogenic responses in patients. Consequently, monitoring alpha-galactosylation in therapeutic proteins is essential, but current analytical techniques fall short in terms of identification sensitivity and quantification accuracy. Specifically, the released glycan assay by hydrophilic interaction liquid chromatography-fluorescence-mass spectrometry, the gold standard for glycan separation/identification, faces challenges due to ambiguities with isomeric glycan structures. To address these challenges, we developed a comprehensive analytical method that enhances both the identification sensitivity and quantification accuracy for α-Gal. We developed an integrated workflow that combines an advanced mass spectrometry technique - parallel reaction monitoring triple-stage mass spectrometry - with exoglycosidase sample treatment. This approach generates structurally specific signature ions, enhances identification sensitivity, enables the separation of α-Gal from its isomers, and improves quantification accuracy. By employing this more sensitive analytical approach without ambiguity in assignment for common glycan structures found in monoclonal antibodies, the safety of therapeutic proteins can be better assured, effectively minimizing the risk of α-Gal-induced immunogenicity.
Early diagnosis is paramount for enhancing survival rates and prognosis in the context of malignant diseases. Hepatocellular carcinoma (HCC), the second leading cause of cancer-related deaths worldwide, poses significant challenges for its early detection. In this study, we present an innovative approach which contributed to the early diagnosis of HCC. By lanthanide encoding signal amplification to map glycan-linkages at the single-cell level, the minute quantities of "soft" glycan-linkages on single cell surface were converted into "hard" elemental tags through the use of an MS2 signal amplifier. Harnessing the power of lanthanides encoded within MS2, we achieve nearly three orders of magnitude signal amplification. These encoded tags are subsequently quantified using single-cell inductively coupled plasma mass spectrometry (SC-ICP-MS). Linear discriminant analysis (LDA) identifies seven specific glycan-linkages (α-2,3-Sia, α-Gal, α-1,2-Fuc, α-1,6-Fuc, α-2,6-Sia, α-GalNAc, and Gal-β-1,3-GalNAc) as biomarkers. Our methodology is initially validated at the cellular level with 100% accuracy in discriminating between hepatic carcinoma HepG2 cells and their normal HL7702 cells. We apply this approach to quantify and classify glycan-linkages on the surfaces of 55 clinical surgical HCC specimens. Leveraging these seven glycan-linkages as biomarkers, we achieve precise differentiation between 8 normal hepatic specimens, 40 early HCC specimens, and 7 colorectal metastasis HCC specimens. This pioneering work represents the first instance of employing single-cell glycan-linkages as biomarkers promising for the early diagnosis of HCC with a remarkable 100% predictive accuracy rate, which holds immense potential for enhancing the feasibility and precision of HCC diagnosis in clinical practice.