Anti-MS4A1 Monoclonal antibody, clone 3I8 [PE/Cy5.5®]

Purpose: We applied a unique method to identify genes expressed in whole blood that can serve as biomarkers to detect colorectal cancer (CRC). Experimental Design:Total RNA was isolated from 211 blood samples (110 non-CRC, 101 CRC). Microarray and quantitative real-time PCR were used for biomarker screening and validation, respectively. Results: From a set of 31 RNA samples (16 CRC, 15 controls), we selected 37 genes from analyzed microarray data that differed significantly between CRC samples and controls (P < 0.05). We tested these genes with a second set of 115 samples (58 CRC, 57 controls) using quantitative real-time PCR, validating 17 genes as differentially expressed. Five of these genes were selected for logistic regression analysis, of which two were the most up-regulated (CDA and MGC20553) and three were the most down-regulated (BANK1, BCNP1, and MS4A1) in CRC patients. Logit (P) of the five-gene panel had an area under the curve of 0.88 (95% confidence interval, 0.81-0.94). At a cutoff of logit (P) >+0.5 as disease (high risk), <-0.5 as control (low risk), and in between as an intermediate zone, the five-gene biomarker combination yielded a sensitivity of 94% (47 of 50) and a specificity of 77% (33 of 43). The intermediate zone contained 22 samples. We validated the predictive power of these five genes with a novel third set of 92 samples, correctly identifying 88% (30 of 34) of CRC samples and 64% (27 of 42) of non-CRC samples. The intermediate zone contained 16 samples. Conclusion: Our results indicate that the five-gene biomarker panel can be used as a novel blood-based test for CRC.

Gene expression profiling has emerged as a powerful strategy to define transcriptional mechanism activated in organ transplantation. We performed a pilot feasibility study of mRNA-based pancreas transplant biopsy stratification. The mRNAs expression of 32 genes, observed in renal transplant dysfunction, and 10 pancreas-specific genes were evaluated in 26 pancreas transplant biopsy specimens by quantitative real-time polymerase chain reaction using TaqMan Low Density Array technology. Unsupervised 2D hierarchical clustering segregated the biopsies in two main cluster branches, A and B. Six of seven patients (85.7%) in cluster A and 6 of 19 (31.6%) in cluster B retained functioning pancreas allograft. CD20/MS4A1 mRNA and protein, in addition to CD 3 protein, were detected in four specimens in cluster B. Three of those four pancreas transplants were subsequently lost. Our study demonstrates the potential association of gene expression with clinical outcome of pancreas transplants and justifies further studies in an independent cohort.