Edoxaban: an update on the new oral direct factor Xa inhibitor.

Edoxaban is a once-daily oral anticoagulant that rapidly and selectively inhibits factor Xa in a concentration-dependent manner. This review describes the extensive clinical development program of edoxaban, including phase III studies in patients with non-valvular atrial fibrillation (NVAF) and symptomatic venous thromboembolism (VTE). The ENGAGE AF-TIMI 48 study (N = 21,105; mean CHADS2 score 2.8) compared edoxaban 60 mg once daily (high-dose regimen) and edoxaban 30 mg once daily (low-dose regimen) with dose-adjusted warfarin [international normalized ratio (INR) 2.0-3.0] and found that both regimens were non-inferior to warfarin in the prevention of stroke and systemic embolism in patients with NVAF. Both edoxaban regimens also provided significant reductions in the risk of hemorrhagic stroke, cardiovascular mortality, major bleeding and intracranial bleeding. The Hokusai-VTE study (N = 8,292) in patients with symptomatic VTE had a flexible treatment duration of 3-12 months and found that following initial heparin, edoxaban 60 mg once daily was non-inferior to dose-adjusted warfarin (INR 2.0-3.0) for the prevention of recurrent VTE, and also had a significantly lower risk of bleeding events. Both studies randomized patients at moderate-to-high risk of thromboembolic events and were further designed to simulate routine clinical practice as much as possible, with edoxaban dose reduction (halving dose) at randomisation or during the study if required, a frequently monitored and well-controlled warfarin group, a well-monitored transition period at study end and a flexible treatment duration in Hokusai-VTE. Given the phase III results obtained, once-daily edoxaban may soon be a key addition to the range of antithrombotic treatment options

MyosinVIIa Interacts with Twinfilin-2 at the Tips of Mechanosensory Stereocilia in the Inner Ear

In vertebrates hearing is dependent upon the microvilli-like mechanosensory stereocilia and their length gradation. The staircase-like organization of the stereocilia bundle is dynamically maintained by variable actin turnover rates. Two unconventional myosins were previously implicated in stereocilia length regulation but the mechanisms of their action remain unknown. MyosinXVa is expressed in stereocilia tips at levels proportional to stereocilia length and its absence produces staircase-like bundles of very short stereocilia. MyosinVIIa localizes to the tips of the shorter stereocilia within bundles, and when absent, the stereocilia are abnormally long. We show here that myosinVIIa interacts with twinfilin-2, an actin binding protein, which inhibits actin polymerization at the barbed end of the filament, and that twinfilin localization in stereocilia overlaps with myosinVIIa. Exogenous expression of myosinVIIa in fibroblasts results in a reduced number of filopodia and promotes accumulation of twinfilin-2 at the filopodia tips. We hypothesize that the newly described interaction between myosinVIIa and twinfilin-2 is responsible for the establishment and maintenance of slower rates of actin turnover in shorter stereocilia, and that interplay between complexes of myosinVIIa/twinfilin-2 and myosinXVa/whirlin is responsible for stereocilia length gradation within the bundle staircase

Loss of Ep-CAM (CO17-1A) expression predicts survival in patients with gastric cancer

Preoperative staging of gastric cancer is difficult and not optimal. The TNM stage is an important prognostic factor, but it can only be assessed reliably after surgery. Therefore, there is need for additional, reliable prognostic factors that can be determined preoperatively in order to select patients who might benefit from (neo) adjuvant treatment. Expression of immunohistochemical markers was demonstrated to be associated with tumour progression and metastasis. The expression of p53, CD44 (splice variants v5, v6 and v9), E-cadherin, Ep-CAM (CO17-1A antigen) and c-erB2/neu were investigated in tumour tissues of 300 patients from the Dutch Gastric Cancer Trial, investigating the value of extended lymphadenectomy compared to that of limited lymphadenectomy). The expression of tumour markers was analysed with respect to patient survival. Patients without loss of Ep-CAM-expression of tumour cells (19%) had a significantly better 10-year survival (P<0.0001) compared to patients with any loss: 42% (s.e.=7%) vs 22% (s.e.=3%). Patients with CD44v6 (VFF18) expression in more than 25% of the tumour cells (69% of the patients) also had a significantly better survival (P=0.01) compared to patients with expression in less than 25% of the tumour cells: 10 year survival rate of 29% (s.e.=3%) vs 19% (s.e.=4%). The prognostic value of both markers was stronger in stages I and II, and independent of the TNM stage. Ep-CAM and CD44v6-expression provides prognostic information additional to the TNM stage. Loss of Ep-CAM-expression identifies aggressive tumours especially in patients with stage I and II disease. This information may be helpful in selecting patients suitable for surgery or for additional treatment pre- or postoperatively

L2-norm multiple kernel learning and its application to biomedical data fusion

<p>Abstract</p> <p>Background</p> <p>This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields different extensions of multiple kernel learning (MKL) such as <it>L</it>_∞, <it>L</it>₁, and <it>L</it>₂MKL. In particular, <it>L</it>₂MKL is a novel method that leads to non-sparse optimal kernel coefficients, which is different from the sparse kernel coefficients optimized by the existing <it>L</it>_∞MKL method. In real biomedical applications, <it>L</it>₂MKL may have more advantages over sparse integration method for thoroughly combining complementary information in heterogeneous data sources.</p> <p>Results</p> <p>We provide a theoretical analysis of the relationship between the <it>L</it>₂optimization of kernels in the dual problem with the <it>L</it>₂coefficient regularization in the primal problem. Understanding the dual <it>L</it>₂problem grants a unified view on MKL and enables us to extend the <it>L</it>₂method to a wide range of machine learning problems. We implement <it>L</it>₂MKL for ranking and classification problems and compare its performance with the sparse <it>L</it>_∞and the averaging <it>L</it>₁MKL methods. The experiments are carried out on six real biomedical data sets and two large scale UCI data sets. <it>L</it>₂MKL yields better performance on most of the benchmark data sets. In particular, we propose a novel <it>L</it>₂MKL least squares support vector machine (LSSVM) algorithm, which is shown to be an efficient and promising classifier for large scale data sets processing.</p> <p>Conclusions</p> <p>This paper extends the statistical framework of genomic data fusion based on MKL. Allowing non-sparse weights on the data sources is an attractive option in settings where we believe most data sources to be relevant to the problem at hand and want to avoid a "winner-takes-all" effect seen in <it>L</it>_∞MKL, which can be detrimental to the performance in prospective studies. The notion of optimizing <it>L</it>₂kernels can be straightforwardly extended to ranking, classification, regression, and clustering algorithms. To tackle the computational burden of MKL, this paper proposes several novel LSSVM based MKL algorithms. Systematic comparison on real data sets shows that LSSVM MKL has comparable performance as the conventional SVM MKL algorithms. Moreover, large scale numerical experiments indicate that when cast as semi-infinite programming, LSSVM MKL can be solved more efficiently than SVM MKL.</p> <p>Availability</p> <p>The MATLAB code of algorithms implemented in this paper is downloadable from <url>http://homes.esat.kuleuven.be/~sistawww/bioi/syu/l2lssvm.html</url>.</p

Polychlorinated biphenyls, cytochrome P450 1A1 (CYP1A1) polymorphisms, and breast cancer risk among African American women and white women in North Carolina: a population-based case-control study

INTRODUCTION: Epidemiologic studies have not shown a strong relationship between blood levels of polychlorinated biphenyls (PCBs) and breast cancer risk. However, two recent studies showed a stronger association among postmenopausal white women with the inducible M2 polymorphism in the cytochrome P450 1A1 (CYP1A1) gene. METHODS: In a population-based case-control study, we evaluated breast cancer risk in relation to PCBs and the CYP1A1 polymorphisms M1 (also known as CYP1A1*2A), M2 (CYP1A1*2C), M3 (CYP1A1*3), and M4 (CYP1A1*4). The study population consisted of 612 patients (242 African American, 370 white) and 599 controls (242 African American, 357 white). RESULTS: There was no evidence of strong joint effects between CYP1A1 M1-containing genotypes and total PCBs in African American or white women. Statistically significant multiplicative interactions were observed between CYP1A1 M2-containing genotypes and elevated plasma total PCBs among white women (P value for likelihood ratio test = 0.02). Multiplicative interactions were also observed between CYP1A1 M3-containing genotypes and elevated total PCBs among African American women (P value for likelihood ratio test = 0.10). CONCLUSIONS: Our results confirm previous reports that CYP1A1 M2-containing genotypes modify the association between PCB exposure and risk of breast cancer. We present additional evidence suggesting that CYP1A1 M3-containing genotypes modify the effects of PCB exposure among African American women. Additional studies are warranted, and meta-analyses combining results across studies will be needed to generate more precise estimates of the joint effects of PCBs and CYP1A1 genotypes

Genomic Profiling of Submucosal-Invasive Gastric Cancer by Array-Based Comparative Genomic Hybridization

Genomic copy number aberrations (CNAs) in gastric cancer have already been extensively characterized by array comparative genomic hybridization (array CGH) analysis. However, involvement of genomic CNAs in the process of submucosal invasion and lymph node metastasis in early gastric cancer is still poorly understood. In this study, to address this issue, we collected a total of 59 tumor samples from 27 patients with submucosal-invasive gastric cancers (SMGC), analyzed their genomic profiles by array CGH, and compared them between paired samples of mucosal (MU) and submucosal (SM) invasion (23 pairs), and SM invasion and lymph node (LN) metastasis (9 pairs). Initially, we hypothesized that acquisition of specific CNA(s) is important for these processes. However, we observed no significant difference in the number of genomic CNAs between paired MU and SM, and between paired SM and LN. Furthermore, we were unable to find any CNAs specifically associated with SM invasion or LN metastasis. Among the 23 cases analyzed, 15 had some similar pattern of genomic profiling between SM and MU. Interestingly, 13 of the 15 cases also showed some differences in genomic profiles. These results suggest that the majority of SMGCs are composed of heterogeneous subpopulations derived from the same clonal origin. Comparison of genomic CNAs between SMGCs with and without LN metastasis revealed that gain of 11q13, 11q14, 11q22, 14q32 and amplification of 17q21 were more frequent in metastatic SMGCs, suggesting that these CNAs are related to LN metastasis of early gastric cancer. In conclusion, our data suggest that generation of genetically distinct subclones, rather than acquisition of specific CNA at MU, is integral to the process of submucosal invasion, and that subclones that acquire gain of 11q13, 11q14, 11q22, 14q32 or amplification of 17q21 are likely to become metastatic