Khaldi, N., et al. (2014). “Predicting the important enzyme players in human breast milk digestion.” J Agric Food Chem.
Human milk is known to contain several proteases, but little is known about whether these enzymes are active, which proteins they cleave and their relative contribution to milk protein digestion in vivo. We analyzed the mass spectrometry-identified protein fragments found in pooled human milk by comparing their cleavage sites with the enzyme specificity patterns of an array of enzymes. The results indicate that several enzymes are actively taking part in the digestion of human milk proteins within the mammary gland, including plasmin and/or trypsin, elastase, cathepsin D, pepsin, chymotrypsin, a glutamyl endopeptidase-like enzyme and proline endopeptidase. Two proteins were most affected by enzyme hydrolysis: beta-casein and polymeric immunoglobulin receptor. In contrast, other highly abundant milk proteins such as alpha-lactalbumin and lactoferrin appear to have undergone no proteolytic cleavage. We also show that a peptide sequence containing a known anti-microbial peptide is released in breast milk by elastase and cathepsin D.

Kim, K., et al. (2014). “Evaluation of Glycomic Profiling as a Diagnostic Biomarker for Epithelial Ovarian Cancer.” Cancer Epidemiol Biomarkers Prev.
BACKGROUND: Prior studies suggested that glycans were differentially expressed in patients with ovarian cancer and controls. We hypothesized that glycan-based biomarkers might serve as a diagnostic test for ovarian cancer and evaluated the ability of glycans to distinguish ovarian cancer cases from matched controls. METHODS: Serum samples were obtained from the tissue-banking repository of the Gynecologic Oncology Group, and included healthy female controls (n = 100), women diagnosed with low malignant potential (LMP) tumors (n = 52), and epithelial ovarian cancers (EOC) cases (n = 147). Cases and controls were matched on age at enrollment within +/-5 years. Serum samples were analyzed by glycomics analysis to detect abundance differences in glycan expression levels. A two-stage procedure was carried out for biomarker discovery and validation. Candidate classifiers of glycans that separated cases from controls were developed using a training set in the discovery phase and the classification performance of the candidate classifiers was assessed using independent test samples that were not used in discovery. RESULTS: The patterns of glycans showed discriminatory power for distinguishing EOC and LMP cases from controls. Candidate glycan-based biomarkers developed on a training set (sensitivity, 86% and specificity, 95.8% for distinguishing EOC from controls through leave-one-out cross-validation) confirmed their potential use as a detection test using an independent test set (sensitivity, 70% and specificity, 86.5%). CONCLUSION: Formal investigations of glycan biomarkers that distinguish cases and controls show great promise for an ovarian cancer diagnostic test. Further validation of a glycan-based test for detection of ovarian cancer is warranted. IMPACT: An emerging diagnostic test based on the knowledge gained from understanding the glycobiology should lead to an assay that improves sensitivity and specificity and allows for early detection of ovarian cancer. Cancer Epidemiol Biomarkers Prev; 1-11. (c)2014 AACR.