Anti-VNN1 monoclonal antibody, clone 3C21

In our previous study, we detected a QTL for the oleic acid percentage (C18:1) on BTA9 in Japanese Black cattle through a genome-wide association study (GWAS). In this study, we performed whole-genome resequencing on eight animals with higher and lower C18:1 to identify candidate polymorphisms for the QTL. A total of 39,658 polymorphisms were detected in the candidate region, which were narrowed to 1993 polymorphisms within 23 genes based on allele differences between the high and low C18:1 groups. We subsequently selected three candidate genes, that is, CYB5R4, MED23, and VNN1, among the 23 genes based on their function in fatty acid metabolism. In each candidate gene, three SNPs, that is, CYB5R4 c.*349G > T, MED23 c.3700G > A, and VNN1 c.197C > T, were selected as candidate SNPs to verify their effect on C18:1 in a Japanese Black cattle population (n = 889). The statistical analysis showed that these SNPs were significantly associated with C18:1 (p < 0.05), suggesting that they were candidates for the QTL. In conclusion, we successfully narrowed the candidates for the QTL by detecting possible polymorphisms located within the candidate region. It is expected that the responsible polymorphism can be identified by demonstrating their effect on the gene's function.

Colorectal cancer (CRC) is often curable and preventable using current screening modalities. Unfortunately, screening compliance remains low, partly due to patient dissatisfaction with faecal/endoscopic testing. Recent guidelines advise CRC screening should begin with risk stratification. A blood-based test providing clinically actionable CRC risk information would likely improve screening compliance and enhance clinical decision making. We analyzed 196 gene expression profiles to select candidate CRC biomarkers. qRT-PCR was performed on 642 samples to develop a 7-gene biomarker panel using 112 CRC/120 controls (training set) and 202 CRC/208 controls (independent, blind test set). Panel performance characteristics and disease prevalence (0.7%) were then used to develop a scale assessing an individual's current risk of having CRC based on his/her gene signature. A 7-gene panel (ANX43, CLEC4D, LMNB1, PRRG4, TNFAIP6, VNN1 and IL2RB) discriminated CRC in the training set (area under the receiver-operating-characteristic curve (ROC AUC), 0.80; accuracy, 73%; sensitivity, 82%; specificity 64%). The independent blind test set confirmed performance (ROC AUC, 0.80; accuracy, 71%; sensitivity, 72%; specificity, 70%). Individual gene profiles were compared against the population results and used to calculate the current relative risk for CRC. We have developed a 7-gene, blood-based biomarker panel that can stratify subjects according to their current relative risk across a broad range in an average-risk population. Across the continuous spectrum of risk as defined by the current relative risk scale, it is possible to identify clinically meaningful reference points that can assist patients and physicians in CRC screening decision making.