Mostly because it is discovered much later in life, pancreatic cancer is one of the deadliest types of the disease. For screens aimed at early detection, the current markers are too ambiguous and insensitive. Now, a study team has published a novel technique in the journal Angewandte Chemie that may result in a diagnosis that is far more exact and trustworthy. The methodology relies on the targeted identification of particular antibodies within blood specimens.
Pancreatic cancer is one of the deadliest forms of the disease, mostly because it is detected significantly later in life. The present markers are overly sensitive and confusing for screenings intended for early detection. Recently, a research team released a unique technique in the journal Angewandte Chemie that could lead to a diagnostic that is much more reliable and accurate. The technology is predicated on the specific identification of antibodies present in blood sample.
They chose to use autoantibodies directed against the tumor-associated form of mucin-1 (TA-MUC1). Mucin-1 is a heavily glycosylated protein (a protein with sugar components) that occurs, for example, in glandular tissue. In many types of tumors, including pancreatic cancer, it is found in significantly elevated concentrations. In addition, the pattern of glycosylation is different from the normal form. The team’s goal was to detect autoantibodies that are directed specifically against TA-MUC1 and are a clear indicator of pancreatic cancer.
Based on structural analyses and computer simulations of known antibodies against TA-MUC1 (SM3 and 5E5), the team designed a collection of synthetic glycopeptides that mimic different segments (epitopes) of TA-MUC1. They also made unnatural modifications to increase the chances of identifying autoantibody subgroups indicative of the disease. The team immobilised these model antigens on gold nanoparticles achieving probes suitable for a serological assay (dot-blot assay). The diagnostic assay was validated with real samples from patients with pancreatic cancer and a healthy control group. Some of the nanoparticle probes could differentiate very well between samples from diseased and healthy individuals demonstrating they detected tumor associated autoantibodies. Notably, these specific autoantibodies displayed significantly better correct positive/false positive ratios than current clinical biomarkers for pancreatic cancer.
Probes with smaller glycopeptide antigens that correspond to only a single epitope, gave better results than larger probes that mimic multiple epitopes–an advantage for easier synthetic production. A short glycopeptide with an unnatural modification to its sugar component was found to be particularly effective for the detection of discriminating autoantibodies. This new structure-based approach could help in the selection of autoantibody subgroups with higher tumor specificity.
(with inputs from ANI)
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