This research is dedicated to the development and clinical validation of a serum-based diagnostic test for early detection of cancer and cancer risk. We have developed a printed glycan array (PGA) that detects a robust panel of cancer-specific anti-glycan autoantibodies in sera from cancer patients and at-risk patients. Aberrant glycosylation of proteins and lipids during malignant transformation results in the appearance of specific glycan structures known as Tumor Associated Carbohydrate Antigens, or TACAs, on cell surfaces and serum components. Combinations of TACAs are always present during malignant transformation and we have already demonstrated that multiple serum autoantibodies against these TACAs can be simultaneously detected using a PGA for patients with all stages of breast cancer including individuals with premalignant diseases. Using dedicated statistical and machine learning methods, we have identified sets of autoantibodies allowing differentiation of patients with metastatic breast cancer from healthy individuals. Although preliminary, these results allow us to conclude that PGAs together with our dedicated data processing methods can be used as a tool for the discovery of glyco-biomarkers, for the development of clinical serum-based screening tests for early detection of cancer and cancer risk, and for the evaluation of malignancy status. The three key components for advancing research have been established in our labratory: (1) in-house printing of custom glycan arrays, (2) PGA-dedicated mathematical data processing tools and (3) tumor-associated glycan discovery tools. The continued research will use the printed glycan array as a major biomarker-discovery technique. Further, the combined expertise of our team of investigators including glycobiologists, oncologists, mathematicians, clinical immunologists and chemists will use PGAs in large population-based studies with the following Specific Aims: 1. To identify and validate anti-glycan autoantibody signatures of the specific stages of breast cancer disease, including: increased breast cancer risk, pre-invasive (DCIS) and early breast cancer, breast cancer progression. 2. To expand the study to the identification and validation of anti-glycan autoantibody signatures for at least three other major malignancies, including ovarian, melanoma and Non-Small Cell Lung Cancer (NSCLC). 3. To identify, isolate and/or synthesize, and perform preliminary testing of novel tumor-associated glycans in serum and cellular materials as cancer-diagnostic antigens. ? ? ?
|Jacob, Francis; Goldstein, Darlene R; Bovin, Nicolai V et al. (2012) Serum antiglycan antibody detection of nonmucinous ovarian cancers by using a printed glycan array. Int J Cancer 130:138-46|
|Bovin, Nicolai; Obukhova, Polina; Shilova, Nadezhda et al. (2012) Repertoire of human natural anti-glycan immunoglobulins. Do we have auto-antibodies? Biochim Biophys Acta 1820:1373-82|
|Pochechueva, Tatiana; Jacob, Francis; Goldstein, Darlene R et al. (2011) Comparison of printed glycan array, suspension array and ELISA in the detection of human anti-glycan antibodies. Glycoconj J 28:507-17|
|Vuskovic, Marko I; Xu, Hongyu; Bovin, Nicolai V et al. (2011) Processing and analysis of serum antibody binding signals from Printed Glycan Arrays for diagnostic and prognostic applications. Int J Bioinform Res Appl 7:402-26|
|Huflejt, Margaret E; Vuskovic, Marko; Vasiliu, Daniela et al. (2009) Anti-carbohydrate antibodies of normal sera: findings, surprises and challenges. Mol Immunol 46:3037-49|