Current pancreatic cancer (PC) markers are too insensitive and unspecific for early detection screenings. Now, an international research team has now reported on the development of a new pancreatic cancer test that uses nanoparticle probes to selectively detect tumor associated autoantibodies against mucin-1 (MUC1) in blood sera. The team, headed by Roberto Fiammengo, PhD, and Giovanni Malerba, PhD, at the University of Verona, together with Alfredo Martínez, PhD, at the Center for Biomedical Research of La Rioja, and Francisco Corzana, PhD, at the Universidad de La Rioja, reported on development of the new assay, and the results of tests on blood samples from pancreatic cancer patients. The team suggests their test strategy could lead to significantly more precise and reliable pancreatic cancer diagnosis.
In their published paper in Angewandte Chemie, the investigators wrote, “The autoantibodies detected by this probe show significantly better true and false positive rates for PC identification than current clinical biomarkers and are suggested as an independent biomarker that could improve disease diagnosis.”
The biomarker CA-19-9, is considered a good diagnostic biomarker in symptomatic patients, and may be used for monitoring benign pancreatic diseases and screening high PC risk individuals, the team stated, but to date no biomarker or panel of biomarkers with sufficient diagnostic accuracy has been approved for the early diagnosis of PC. “Therefore, finding alternative, possibly more sensitive and specific, biomarkers is crucial to improve early detection, allowing for prompt medical intervention and higher patient survival rates.”
One potential and “appealing” possibility is to exploit circulating tumor-associated autoantibodies that can be detected readily in serum samples. Tumors produce certain tumor-associated antigens that draw the attention of the body’s constantly patrolling immune system and trigger an immune response. As a consequence, antibodies directed against the tumors—tumor-associated autoantibodies—are formed, circulating in the blood at very early stages of the disease—which makes them useful for early detection. “Tumor-associated autoantibodies effectively represent a natural amplification mechanism and can be identified at a very early stage of the disease before tumor-associated antigens can be detected, thus being ideally suited for early diagnosis.”
The new pancreatic cancer diagnostic approach developed by Fiammengo, Malerba and colleagues is based on the detection of tumor-associated autoantibodies directed against the tumor-associated form of mucin-1 (TA-MUC1). Mucin-1 is a heavily glycosylated protein 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 that of 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. “We used a structure-guided approach to develop unnatural glycopeptides as model antigens for tumor-associated MUC1,” they wrote. They also made unnatural modifications to increase the chances of identifying autoantibody subgroups indicative of the disease. The team immobilized these model antigens on gold nanoparticles (AuNPs) to create 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. The team found that 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. “Our work shows that it is possible to exploit structurally engineered unnatural glycopeptides to develop a nanoparticle-based diagnostic assay that detects subsets of autoantibodies associated with the tumoral state,” they commented.
This novel structure-based approach could help in the selection of autoantibody subgroups with higher tumor specificity. “… our approach has allowed the development of TA-MUC1 model antigens that are short and simple glycopeptides significantly reducing the synthetic effort and increasing their attractivity for clinical diagnostic applications,” the team further stated. “Future work is focused on the development of more selective glycopeptide nanoparticle probes and on the application of our diagnostic assay in suitable validation cohorts.”
