Amplification and over-expression of MAP3K3 gene in human breast cancer promotes formation and survival of breast cancer cells.

Gene amplifications in the 17q chromosomal region are observed frequently in breast cancers. An integrative bioinformatics analysis of this region nominated the MAP3K3 gene as a potential therapeutic target in breast cancer. This gene encodes mitogen-activated protein kinase kinase kinase 3 (MAP3K3/MEKK3), which has not yet been reported to be associated with cancer-causing genetic aberrations. We found that MAP3K3 was amplified in approximately 8-20% of breast cancers. Knockdown of MAP3K3 expression significantly inhibited cell proliferation and colony formation in MAP3K3-amplified breast cancer cell lines MCF-7 and MDA-MB-361 but not in MAP3K3 non-amplified breast cancer cells. Knockdown of MAP3K3 expression in MAP3K3-amplified breast cancer cells sensitized breast cancer cells to apoptotic induction by TNFα and TRAIL, as well as doxorubicin, VP-16 and fluorouracil, three commonly used chemotherapeutic drugs for treating breast cancer. In addition, ectopic expression of MAP3K3, in collaboration with Ras, induced colony formation in both primary mouse embryonic fibroblasts and immortalized human breast epithelial cells (MCF-10A). Combined, these results suggest that MAP3K3 contributes to breast carcinogenesis and may endow resistance of breast cancer cells to cytotoxic chemotherapy. Therefore, MAP3K3 may be a valuable therapeutic target in patients with MAP3K3-amplified breast cancers, and blocking MAP3K3 kinase activity with a small molecule inhibitor may sensitize MAP3K3-amplified breast cancer cells to chemotherapy.

Host heterogeneous ribonucleoprotein K (hnRNP K) as a potential target to suppress hepatitis B virus replication.

BACKGROUND: Hepatitis B virus (HBV) infection results in complications such as cirrhosis and hepatocellular carcinoma. Suppressing viral replication in chronic HBV carriers is an effective approach to controlling disease progression. Although antiviral compounds are available, we aimed to identify host factors that have a significant effect on viral replication efficiency. METHODS AND FINDINGS: We studied a group of hepatitis B carriers by associating serum viral load with their respective HBV genomes, and observed a significant association between high patient serum viral load with a natural sequence variant within the HBV enhancer II (Enh II) regulatory region at position 1752. Using a viral fragment as an affinity binding probe, we isolated a host DNA-binding protein belonging to the class of heterogeneous nuclear ribonucleoproteins--hnRNP K--that binds to and modulates the replicative efficiency of HBV. In cell transfection studies, overexpression of hnRNP K augmented HBV replication, while gene silencing of endogenous hnRNP K carried out by small interfering RNAs resulted in a significant reduction of HBV viral load. CONCLUSION: The evidence presented in this study describes a wider role for hnRNP K beyond maintenance of host cellular functions and may represent a novel target for pharmacologic intervention of HBV replication.

An integrated proteomic approach to identifying circulating biomarkers in high-risk neuroblastoma and their potential in relapse monitoring.

PURPOSE: Despite intensive treatment regimens, overall survival for high-risk neuroblastoma (HRNB) is still poor. This is in part due to an inability to cure the disease once a patient has reached clinical relapse. Identifying plasma biomarkers of active disease may provide a way of relapse monitoring in HRNB. EXPERIMENTAL DESIGN: In this study, we developed an integrated proteomic approach to identify plasma biomarkers for HRNB. RESULTS: We identified seven candidate biomarkers (SAA, APOA1, IL-6, EGF, MDC, sCD40L and Eotaxin) for HRNB. These biomarkers were then used to create a multivariate classifier of HRNB, which showed a specificity of 90% (95% confidence interval (CI), 73%, 98%), and a sensitivity of 81% (95%CI, 54%, 96%) for classifying HRNB in a training set. When evaluated on independent test samples, the classifier exhibited 86% accuracy (95% CI, 42%, 100%) of identifying diagnostic samples, and 86% accuracy (95% CI, 70%, 100%) of detecting post-diagnosis longitudinal samples that having active disease. CONCLUSION AND CLINICAL RELEVANCE: Further validation of these biomarkers may improve patients' outcomes by developing a simple blood test for the detection of relapse prior to the development of clinically evident disease. Understanding the role of these biomarkers in immune surveillance of neuroblastoma may also provide a new direction of therapeutic strategies.

Genome-wide high-density SNP linkage search for glioma susceptibility loci: results from the Gliogene Consortium.

Gliomas, which generally have a poor prognosis, are the most common primary malignant brain tumors in adults. Recent genome-wide association studies have shown that inherited susceptibility plays a role in the development of glioma. Although first-degree relatives of patients exhibit a two-fold increased risk of glioma, the search for susceptibility loci in familial forms of the disease has been challenging because the disease is relatively rare, fatal, and heterogeneous, making it difficult to collect sufficient biosamples from families for statistical power. To address this challenge, the Genetic Epidemiology of Glioma International Consortium (Gliogene) was formed to collect DNA samples from families with two or more cases of histologically confirmed glioma. In this study, we present results obtained from 46 U.S. families in which multipoint linkage analyses were undertaken using nonparametric (model-free) methods. After removal of high linkage disequilibrium single-nucleotide polymorphism, we obtained a maximum nonparametric linkage score (NPL) of 3.39 (P = 0.0005) at 17q12-21.32 and the Z-score of 4.20 (P = 0.000007). To replicate our findings, we genotyped 29 independent U.S. families and obtained a maximum NPL score of 1.26 (P = 0.008) and the Z-score of 1.47 (P = 0.035). Accounting for the genetic heterogeneity using the ordered subset analysis approach, the combined analyses of 75 families resulted in a maximum NPL score of 3.81 (P = 0.00001). The genomic regions we have implicated in this study may offer novel insights into glioma susceptibility, focusing future work to identify genes that cause familial glioma.