Abnormal glycosylation patterns are known to occur in cancerous cells, becoming those glycans a biomarker for cancer detection. However, the complexity and array of glycoforms structurally similar to each other that can be present in cells, makes a challenge the identification of the ones actually involved in tumour growth. Rates of 50% and 25% of false positive and negative results -respectively- in early detection of Prostate Cancer (as an example) are a good proof for the need of an enhanced detection technology. This project aims to develop the methodology to accurately, efficiently, and selectively find receptors for such glycans. We employ Dynamic Combinatorial Chemistry (DCC). DCC allows you, not only to synthesise a number of receptors, but also to identify the best one among them. The library members for DCC were meticulously chosen/synthesised in order to gather a variety of functionalities that would enrich the library and therefore benefit the final ligand. Boronic Acids and Benzoboroxoles are perhaps our best candidates as they can bind saccharides, which are present in our target glycans. This methodology already gave us some preliminary promising results that will be further confirmed by Isothermal Titration Calorimetry (ITC). We are already working on the development of a second generation library, with more complex building blocks and larger library sizes, that will hopefully bring even better receptors to be employed for the effective early detection of cancer.

Glycan-binding entities for the early detection of cancer

ACS Spring 2022

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