Vaccine-induced immune thrombotic thrombocytopenia (VITT) - a novel clinico-pathological entity with heterogeneous clinical presentations.

Vaccine-induced immune thrombotic thrombocytopenia (VITT) is a novel entity that emerged in March 2021 following reports of unusual thrombosis after ChAdOx1 nCoV-19, (AstraZeneca) vaccination. Following the recognition of this syndrome, multiple consensus guidelines have been released to risk stratify patients presenting with possible symptoms after ChAdOx1 nCoV-19 vaccination. All guidelines rapidly identify VITT in patients with the complete triad of thrombocytopenia, thrombosis and elevated D-dimers after ChAdOx1 nCoV-19 vaccination. However, with earlier recognition of the associated symptoms, the clinical manifestations are likely to be more heterogeneous and represent an evolving spectrum of disease. In this setting, current guidelines may lack the sensitivity to detect early cases of VITT and risk missed or delayed diagnoses. The broad clinical phenotype and challenges associated with diagnosis of VITT are highlighted in our present case series of four patients with confirmed VITT. Dependent on the guidance used, each patient could have been classified as a low probability of VITT at presentation. The present study highlights the issues associated with the recognition of VITT, the limitations of current guidance and the need for heightened clinical vigilance as our understanding of the pathophysiology of this novel condition evolves.

Current and future biomarkers for risk-stratification and treatment personalisation in multiple myeloma.

Multiple myeloma, an incurable malignancy of the plasma cells in the bone marrow, has a complex pathogenesis due to clonal heterogeneity. Over the years, many clinical trials and researches have led to the development of effective myeloma treatments, resulting in survival prolongation. Molecular prognostic markers for risk-stratification to predict survival, and predictive markers for treatment response are being extensively explored. This review discusses the current risk-adaptive strategies based on genetic and molecular risk signatures that are in practice to predict survival and describes the future prognostic and predictive biomarkers across the fields of genomics, proteomics, and glycomics in myeloma. Gene expression profiling and next generation sequencing are coming to the forefront of risk-stratification and therapeutic-response prediction. Similarly, proteomic and glycomic-based platforms are gaining momentum in biomarker discovery to predict drug resistance and disease progression.

Polyclonal Immunoglobulin G N-Glycosylation in the Pathogenesis of Plasma Cell Disorders.

The pathological progression from benign monoclonal gammopathy of undetermined significance (MGUS) to smoldering myeloma (SMM) and finally to active myeloma (MM) is poorly understood. Abnormal immunoglobulin G (IgG) glycosylation in myeloma has been reported. Using a glycomic platform composed of hydrophilic interaction UPLC, exoglycosidase digestions, weak anion-exchange chromatography, and mass spectrometry, polyclonal IgG N-glycosylation profiles from 35 patients [MGUS (n = 8), SMM (n = 5), MM (n = 8), complete-response (CR) post-treatment (n = 5), relapse (n = 4), healthy age-matched control (n = 5)] were characterized to map glycan structures in distinct disease phases of multiple myeloma. N-Glycan profiles from MGUS resembled normal control. The abundance of neutral glycans containing terminal galactose was highest in SMM, while agalactosylated glycans and fucosylated glycans were lowest in MM. Three afucosyl-biantennary-digalactosylated-sialylated species (A2G2S1, A2BG2S1, and A2BG2S2) decreased 2.38-, 2.4-, and 4.25-fold, respectively, from benign to active myeloma. Increased light chain sialylation was observed in a longitudinal case of transformation from MGUS to MM. Bisecting N-acetylglucosamine was lowest in the CR group, while highest in relapsed disease. Gene expression levels of FUT 8, ST6GAL1, B4GALT1, RECK, and BACH2 identified from publicly available GEP data supported the glycomic changes seen in MM compared to control. The observed differential glycosylation underlined the heterogeneity of the myeloma spectrum. This study demonstrates the feasibility of mapping glycan modifications on the IgG molecule and provides proof of principle that differential IgG glycosylation patterns can be successfully identified in plasma cell disorders.